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    "# Agricultural market intelligence for an irrigated valley: a weekly price-monitoring system\n",
    "\n",
    "**Worked example by Ahmed Beddi, on synthetic data.** Every price in this notebook is generated below from a seeded model. Prices are in a generic local currency unit (LCU) per kg. The harvest calendars, costs, margins and shocks are illustrative. They are not the prices of any real country, market, agency or programme, and no public dataset is used.\n",
    "\n",
    "**Setting.** An irrigated river valley in the Sahel that produces paddy rice (a wet-season and an off-season crop) and onion (a cold dry-season crop). Four markets are followed for each crop: farm gate in the valley, Valley market A, a regional wholesale market and the capital wholesale market. For rice, an illustrative port import-parity price is added.\n",
    "\n",
    "**What the system answers each week.**\n",
    "1. Is this week's price abnormal for the season? (seasonal norm, band, alert rule)\n",
    "2. Do valley prices follow the capital, and how fast? (spreads, error-correction model)\n",
    "3. How much of the wholesale price reaches the farm gate? (marketing margin)\n",
    "4. Does holding stock from harvest to the lean season pay? (storage calculator)\n",
    "5. Where are prices likely to be in the next 12 weeks, with what uncertainty? (forecast bands, backtested)\n",
    "\n",
    "The code cell below is the full module `market_intelligence.py`, also published as a separate script. The website demo uses the same formulas and defaults."
   ]
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   "source": [
    "\"\"\"\n",
    "market_intelligence.py\n",
    "----------------------\n",
    "Worked example by Ahmed Beddi: a weekly agricultural market-intelligence system for one\n",
    "irrigated cereal (paddy and milled local rice) and one horticultural crop (onion) in an\n",
    "irrigated river valley in the Sahel.\n",
    "\n",
    "ALL DATA ARE SYNTHETIC. The generator below produces six years of weekly prices\n",
    "(312 weeks, 16 Nov 2020 to 2 Nov 2026) for four markets per crop, plus an illustrative\n",
    "import-parity price for rice. Prices are in a generic local currency unit (LCU) per kg.\n",
    "Harvest calendars, costs, margins and shocks are illustrative; they are not the prices of\n",
    "any real country, market, agency or programme.\n",
    "\n",
    "Pipeline\n",
    "  1. generate()            synthetic weekly prices with seasonality, trend, shocks\n",
    "  2. seasonal_norms()      robust STL on log prices over the 5-year reference period\n",
    "                           (weeks 0-259); norm frozen and projected for the monitoring\n",
    "                           year (weeks 260-311); band = norm x exp(+/- k sigma)\n",
    "  3. alerts()              flag when the price is outside the band on the same side for\n",
    "                           n consecutive weeks (default k = 2, n = 2)\n",
    "  4. spreads_margins()     valley-capital spread and farm-gate-to-wholesale margin\n",
    "  5. transmission()        Engle-Granger cointegration and error-correction model,\n",
    "                           Valley market A on Capital wholesale market\n",
    "  6. storage()             net margin per tonne of holding from a buy month to a sell\n",
    "                           month, after losses, financing and storage fees\n",
    "  7. backtest(), forecast() seasonal naive vs SARIMA vs STL+ETS, rolling-origin backtest\n",
    "                           (MAPE, interval coverage), 12-week prediction bands\n",
    "\n",
    "Run:  python market_intelligence.py                 (writes CSVs and PNGs next to it)\n",
    "      python market_intelligence.py --ts-out PATH   (also writes the demo data file)\n",
    "\n",
    "The website demo (MarketPriceMonitor.tsx) reads the series, norms and forecasts exported by\n",
    "this script and recomputes the band, alert rule, spreads, margins and storage calculator\n",
    "with the same formulas and defaults (components/demos/lib/marketPriceMonitor.ts).\n",
    "\"\"\"\n",
    "from __future__ import annotations\n",
    "\n",
    "import argparse\n",
    "import json\n",
    "import math\n",
    "import warnings\n",
    "from dataclasses import dataclass, asdict\n",
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "SEED = 20261106\n",
    "N_WEEKS = 312                       # six years of weekly observations\n",
    "N_REF = 260                         # five-year reference period (weeks 0-259)\n",
    "START = pd.Timestamp(\"2020-11-16\")  # Monday; the last week starts 2026-11-02\n",
    "PERIOD = 52\n",
    "\n",
    "SERIES = [\n",
    "    # key, crop, market, label\n",
    "    (\"rice_farmgate\", \"rice\", \"farmgate\", \"Paddy, farm gate (valley)\"),\n",
    "    (\"rice_valley\", \"rice\", \"valley\", \"Milled local rice, Valley market A\"),\n",
    "    (\"rice_regional\", \"rice\", \"regional\", \"Milled local rice, Regional wholesale market\"),\n",
    "    (\"rice_capital\", \"rice\", \"capital\", \"Milled local rice, Capital wholesale market\"),\n",
    "    (\"rice_parity\", \"rice\", \"parity\", \"Imported rice, port import parity (capital)\"),\n",
    "    (\"onion_farmgate\", \"onion\", \"farmgate\", \"Onion, farm gate (valley)\"),\n",
    "    (\"onion_valley\", \"onion\", \"valley\", \"Onion, Valley market A\"),\n",
    "    (\"onion_regional\", \"onion\", \"regional\", \"Onion, Regional wholesale market\"),\n",
    "    (\"onion_capital\", \"onion\", \"capital\", \"Onion, Capital wholesale market\"),\n",
    "]\n",
    "KEYS = [s[0] for s in SERIES]\n",
    "\n",
    "\n",
    "@dataclass(frozen=True)\n",
    "class GenParams:\n",
    "    \"\"\"Generator parameters. All illustrative unless stated otherwise in the notebook.\"\"\"\n",
    "    inflation: float = 0.04           # general price drift per year (LCU)\n",
    "    # Import parity for rice: IPP = (FOB + freight) * FX / 1000 * (1 + duty) * (1 + margin) + port + haul\n",
    "    fob0: float = 480.0               # world FOB price, US$/t, week 0\n",
    "    freight: float = 55.0             # ocean freight and insurance, US$/t\n",
    "    fx0: float = 100.0                # LCU per US$, week 0\n",
    "    fx_drift: float = 0.03            # depreciation per year\n",
    "    duty: float = 0.10                # import duty and taxes, share of CIF\n",
    "    importer_margin: float = 0.06     # importer and wholesale margin, share\n",
    "    port_cost: float = 2.5            # port handling, LCU/kg (week-0 prices)\n",
    "    haul_cost: float = 1.5            # port-to-capital haulage, LCU/kg (week-0 prices)\n",
    "    # Local rice\n",
    "    quality_discount: float = 0.85    # local milled rice at capital, ratio to import parity (long run)\n",
    "    ipp_passthrough: float = 0.6      # share of import-parity movements passed to local rice (log)\n",
    "    milling_ratio: float = 0.65       # kg milled rice per kg paddy\n",
    "    milling_cost: float = 3.0         # LCU per kg paddy (week-0 prices)\n",
    "    # Valley-capital arbitrage (error-correction generator)\n",
    "    rice_transfer: float = 7.0        # transport + trader cost valley -> capital, LCU/kg (week 0)\n",
    "    onion_transfer: float = 5.0\n",
    "    rice_alpha: float = 0.25          # speed of adjustment of Valley market A to capital\n",
    "    onion_alpha: float = 0.35\n",
    "    rice_gamma: float = 0.30          # same-week pass-through of capital price changes\n",
    "    onion_gamma: float = 0.40\n",
    "    # Onion\n",
    "    onion_base: float = 26.0          # capital wholesale, LCU/kg, week 0 level (deseasonalised)\n",
    "    onion_farm_share: float = 0.80    # farm gate as share of Valley market A price\n",
    "    onion_farm_cost: float = 1.0      # field-to-market cost, LCU/kg (week 0)\n",
    "\n",
    "\n",
    "# Shock episodes injected by the generator (used to evaluate the alert rule).\n",
    "# start date, weeks, what it hits, size\n",
    "SHOCKS = [\n",
    "    dict(id=\"S1\", start=\"2022-08-29\", weeks=10, crop=\"onion\", where=\"capital\", kind=\"supply shortfall\", size=+0.35),\n",
    "    dict(id=\"S2\", start=\"2023-02-06\", weeks=6, crop=\"rice\", where=\"parity\", kind=\"exchange-rate depreciation (persistent)\", size=+0.12),\n",
    "    dict(id=\"S3\", start=\"2023-08-07\", weeks=14, crop=\"rice\", where=\"parity\", kind=\"world price spike\", size=+0.30),\n",
    "    dict(id=\"S4\", start=\"2024-08-12\", weeks=8, crop=\"both\", where=\"valley\", kind=\"road cut: transfer cost up\", size=+8.0),\n",
    "    dict(id=\"S5\", start=\"2025-03-10\", weeks=8, crop=\"onion\", where=\"capital\", kind=\"bumper harvest glut\", size=-0.25),\n",
    "    dict(id=\"S6\", start=\"2025-12-08\", weeks=6, crop=\"rice\", where=\"valley\", kind=\"harvest glut, late paddy payments\", size=-0.10),\n",
    "    dict(id=\"S7\", start=\"2026-09-14\", weeks=8, crop=\"onion\", where=\"capital\", kind=\"storage losses, early stock-out\", size=+0.30),\n",
    "]\n",
    "\n",
    "\n",
    "def dates() -> pd.DatetimeIndex:\n",
    "    return pd.date_range(START, periods=N_WEEKS, freq=\"7D\")\n",
    "\n",
    "\n",
    "def _seasonal_profile(harvests, smooth_days: float = 12.0) -> np.ndarray:\n",
    "    \"\"\"Daily log-price seasonal profile (365 values, mean zero).\n",
    "\n",
    "    Each harvest k pulls the price down by A_k at its peak-arrival day H_k; the effect\n",
    "    decays with time constant lam_k days as stocks are drawn down. A circular Gaussian\n",
    "    smoother (sd smooth_days) removes the jump at harvest onset.\n",
    "    \"\"\"\n",
    "    d = np.arange(365)\n",
    "    prof = np.zeros(365)\n",
    "    for H, A, lam in harvests:\n",
    "        since = (d - H) % 365\n",
    "        prof -= A * np.exp(-since / lam)\n",
    "    k = np.arange(-60, 61)\n",
    "    w = np.exp(-0.5 * (k / smooth_days) ** 2)\n",
    "    w /= w.sum()\n",
    "    sm = np.array([np.sum(w * prof[(i + k) % 365]) for i in range(365)])\n",
    "    return sm - sm.mean()\n",
    "\n",
    "\n",
    "# Illustrative harvest calendars (peak-arrival day of year, amplitude in log points, decay in days)\n",
    "RICE_HARVESTS = [(324, 0.12, 120.0),   # wet-season harvest, peak arrivals ~20 November\n",
    "                 (171, 0.06, 90.0)]    # off-season (hot dry season) harvest, ~20 June\n",
    "ONION_HARVESTS = [(74, 0.55, 200.0)]   # cold dry-season harvest, peak arrivals ~15 March\n",
    "\n",
    "\n",
    "def _episode(idx: pd.DatetimeIndex, start: str, weeks: int, ramp: int = 3, persistent: bool = False) -> np.ndarray:\n",
    "    \"\"\"Shape of a shock: ramps up over `ramp` weeks, holds, ramps down (unless persistent).\"\"\"\n",
    "    t0 = idx.get_indexer([pd.Timestamp(start)])[0]\n",
    "    x = np.zeros(len(idx))\n",
    "    for i in range(len(idx)):\n",
    "        j = i - t0\n",
    "        if j < 0:\n",
    "            continue\n",
    "        if persistent:\n",
    "            x[i] = min(1.0, (j + 1) / weeks)\n",
    "        elif j < weeks:\n",
    "            up = min(1.0, (j + 1) / ramp)\n",
    "            down = min(1.0, (weeks - j) / ramp)\n",
    "            x[i] = min(up, down)\n",
    "    return x\n",
    "\n",
    "\n",
    "def _ar1(rng, n, rho, sd) -> np.ndarray:\n",
    "    e = rng.normal(0, sd, n)\n",
    "    x = np.zeros(n)\n",
    "    x[0] = e[0] / math.sqrt(1 - rho ** 2)\n",
    "    for i in range(1, n):\n",
    "        x[i] = rho * x[i - 1] + e[i]\n",
    "    return x\n",
    "\n",
    "\n",
    "def generate(g: GenParams = GenParams(), seed: int = SEED) -> pd.DataFrame:\n",
    "    \"\"\"Synthetic weekly prices, LCU/kg, rounded to 2 decimals (the canonical data).\"\"\"\n",
    "    rng = np.random.default_rng(seed)\n",
    "    idx = dates()\n",
    "    n = len(idx)\n",
    "    t = np.arange(n)\n",
    "    doy = ((idx + pd.Timedelta(days=3)).dayofyear.values - 1) % 365   # mid-week day of year\n",
    "    infl = np.exp(np.log(1 + g.inflation) * t / 52.0)\n",
    "    s_rice = _seasonal_profile(RICE_HARVESTS)[doy]\n",
    "    s_onion = _seasonal_profile(ONION_HARVESTS)[doy]\n",
    "    harvest_rice = np.clip(-s_rice / max(1e-9, -s_rice.min()), 0, 1)      # 0..1 harvest intensity\n",
    "    harvest_onion = np.clip(-s_onion / max(1e-9, -s_onion.min()), 0, 1)\n",
    "\n",
    "    sh = {s[\"id\"]: _episode(idx, s[\"start\"], s[\"weeks\"], persistent=(s[\"id\"] == \"S2\")) for s in SHOCKS}\n",
    "\n",
    "    # Exchange rate and world price\n",
    "    log_fx = np.log(g.fx0) + np.log(1 + g.fx_drift) * t / 52.0 + np.cumsum(rng.normal(0, 0.004, n))\n",
    "    log_fx += np.log(1 + 0.12) * sh[\"S2\"]\n",
    "    fx = np.exp(log_fx)\n",
    "    log_fob = np.log(g.fob0) + _ar1(rng, n, 0.97, 0.012) + np.log(1 + 0.30) * sh[\"S3\"]\n",
    "    fob = np.exp(log_fob)\n",
    "    parity = ((fob + g.freight) * fx / 1000.0 * (1 + g.duty) * (1 + g.importer_margin)\n",
    "              + (g.port_cost + g.haul_cost) * infl)\n",
    "\n",
    "    # Local milled rice, capital: partial pass-through of import parity, quality discount, seasonality\n",
    "    ipp_bar = parity[0] * infl\n",
    "    log_cap_r = (np.log(g.quality_discount) + g.ipp_passthrough * np.log(parity)\n",
    "                 + (1 - g.ipp_passthrough) * np.log(ipp_bar)\n",
    "                 + 0.6 * s_rice + _ar1(rng, n, 0.8, 0.010))\n",
    "    cap_r = np.exp(log_cap_r)\n",
    "\n",
    "    # Onion, capital: seasonal, persistent noise, supply shocks\n",
    "    log_cap_o = (np.log(g.onion_base) + np.log(infl) + 0.85 * s_onion + _ar1(rng, n, 0.85, 0.028)\n",
    "                 + np.log(1 + 0.35) * sh[\"S1\"] + np.log(1 - 0.25) * sh[\"S5\"] + np.log(1 + 0.30) * sh[\"S7\"])\n",
    "    cap_o = np.exp(log_cap_o)\n",
    "    cap_r = cap_r * (1 + 0.04 * sh[\"S4\"])          # road cut: capital a little dearer\n",
    "    cap_o = cap_o * (1 + 0.06 * sh[\"S4\"])\n",
    "\n",
    "    def valley(cap, transfer0, alpha, gamma, s_extra, harvest, road, noise_sd, local_shock):\n",
    "        tau = transfer0 * infl * (1 + 0.25 * harvest) + road\n",
    "        v = np.zeros(n)\n",
    "        target0 = cap[0] * np.exp(s_extra[0]) - tau[0]\n",
    "        v[0] = target0\n",
    "        eps = rng.normal(0, noise_sd, n)\n",
    "        for i in range(1, n):\n",
    "            target = cap[i - 1] * np.exp(s_extra[i]) * (1 + local_shock[i]) - tau[i]\n",
    "            v[i] = v[i - 1] + alpha * (target - v[i - 1]) + gamma * (cap[i] - cap[i - 1]) + eps[i] * infl[i]\n",
    "        return v\n",
    "\n",
    "    road = 8.0 * sh[\"S4\"] * infl\n",
    "    val_r = valley(cap_r, g.rice_transfer, g.rice_alpha, g.rice_gamma, 0.4 * s_rice, harvest_rice, road,\n",
    "                   0.45, -0.10 * sh[\"S6\"])\n",
    "    val_o = valley(cap_o, g.onion_transfer, g.onion_alpha, g.onion_gamma, 0.15 * s_onion, harvest_onion, road,\n",
    "                   0.45, np.zeros(n))\n",
    "\n",
    "    reg_r = 0.55 * cap_r + 0.45 * val_r + _ar1(rng, n, 0.5, 0.35) * infl\n",
    "    reg_o = 0.55 * cap_o + 0.45 * val_o + _ar1(rng, n, 0.5, 0.40) * infl\n",
    "\n",
    "    # Farm gate: paddy = milling ratio x valley milled price - milling cost, with a harvest discount\n",
    "    fg_r = (g.milling_ratio * val_r * (1 - 0.05 * harvest_rice) - g.milling_cost * infl\n",
    "            + _ar1(rng, n, 0.6, 0.25) * infl)\n",
    "    fg_o = (g.onion_farm_share * val_o * (1 - 0.08 * harvest_onion) - g.onion_farm_cost * infl\n",
    "            + _ar1(rng, n, 0.6, 0.30) * infl)\n",
    "\n",
    "    df = pd.DataFrame({\n",
    "        \"week\": t, \"date\": idx.strftime(\"%Y-%m-%d\"),\n",
    "        \"period\": np.where(t < N_REF, \"reference\", \"monitoring\"),\n",
    "        \"rice_farmgate\": fg_r, \"rice_valley\": val_r, \"rice_regional\": reg_r, \"rice_capital\": cap_r,\n",
    "        \"rice_parity\": parity,\n",
    "        \"onion_farmgate\": fg_o, \"onion_valley\": val_o, \"onion_regional\": reg_o, \"onion_capital\": cap_o,\n",
    "        \"fx_lcu_per_usd\": fx, \"world_fob_usd_t\": fob,\n",
    "    })\n",
    "    for k in KEYS:\n",
    "        df[k] = df[k].round(2)\n",
    "    df[\"fx_lcu_per_usd\"] = df[\"fx_lcu_per_usd\"].round(3)\n",
    "    df[\"world_fob_usd_t\"] = df[\"world_fob_usd_t\"].round(1)\n",
    "    return df\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- seasonal norms and alerts\n",
    "\n",
    "@dataclass(frozen=True)\n",
    "class AlertRule:\n",
    "    k: float = 2.0       # band half-width, in robust SDs of log(price / norm) over the reference period\n",
    "    n: int = 2           # consecutive weeks outside the band (same side) to raise a flag\n",
    "    window: int = 13     # weeks of deseasonalised prices in the level estimate\n",
    "    gap: int = 4         # weeks between the end of the level window and the current week\n",
    "\n",
    "\n",
    "def seasonal_index(df: pd.DataFrame) -> dict:\n",
    "    \"\"\"Robust STL (period 52, seasonal window 7) on log prices of the 5-year reference period.\n",
    "\n",
    "    Returns per series: the STL components, and a fixed 52-week seasonal index s_p\n",
    "    (p = week mod 52), the mean STL seasonal at each cycle position, centred on zero and\n",
    "    rounded to 5 decimals (the exported value used everywhere downstream).\n",
    "    \"\"\"\n",
    "    from statsmodels.tsa.seasonal import STL\n",
    "    out = {}\n",
    "    pos = np.arange(N_REF) % PERIOD\n",
    "    for k in KEYS:\n",
    "        y = np.log(df[k].values[:N_REF])\n",
    "        res = STL(y, period=PERIOD, seasonal=7, robust=True).fit()\n",
    "        s = np.array([res.seasonal[pos == p].mean() for p in range(PERIOD)])\n",
    "        s = np.round(s - s.mean(), 5)\n",
    "        out[k] = dict(index=s, trend=res.trend, seasonal=res.seasonal, remainder=res.resid,\n",
    "                      strength=float(max(0.0, 1 - np.var(res.resid) / np.var(res.resid + res.seasonal))))\n",
    "    return out\n",
    "\n",
    "\n",
    "def seasonal_norm(price: np.ndarray, s: np.ndarray, rule: AlertRule = AlertRule()) -> np.ndarray:\n",
    "    \"\"\"Causal seasonal norm: norm_t = exp(s_{t mod 52}) x L_t, where L_t is the median of the\n",
    "    deseasonalised price p_j / exp(s_{j mod 52}) over weeks t-gap-window+1 .. t-gap.\n",
    "    Undefined (NaN) for the first gap+window-1 weeks.\"\"\"\n",
    "    n = len(price)\n",
    "    sf = np.exp(s[np.arange(n) % PERIOD])\n",
    "    des = price / sf\n",
    "    norm = np.full(n, np.nan)\n",
    "    for t in range(rule.gap + rule.window - 1, n):\n",
    "        lo, hi = t - rule.gap - rule.window + 1, t - rule.gap + 1\n",
    "        norm[t] = sf[t] * np.median(des[lo:hi])\n",
    "    return norm\n",
    "\n",
    "\n",
    "def band_sigma(price: np.ndarray, norm: np.ndarray) -> float:\n",
    "    \"\"\"Robust SD (1.4826 x MAD) of log(price / norm) over the reference period.\"\"\"\n",
    "    r = np.log(price[:N_REF] / norm[:N_REF])\n",
    "    r = r[~np.isnan(r)]\n",
    "    return float(1.4826 * np.median(np.abs(r - np.median(r))))\n",
    "\n",
    "\n",
    "def band(norm: np.ndarray, sigma: float, k: float):\n",
    "    return norm * np.exp(-k * sigma), norm * np.exp(k * sigma)\n",
    "\n",
    "\n",
    "def alerts(price: np.ndarray, norm: np.ndarray, sigma: float, rule: AlertRule = AlertRule()) -> np.ndarray:\n",
    "    \"\"\"+1 high flag, -1 low flag, 0 none. A week is flagged when it and the previous n-1\n",
    "    weeks are all outside the band on the same side (causal: uses only weeks <= t).\"\"\"\n",
    "    lo, hi = band(norm, sigma, rule.k)\n",
    "    side = np.where(price > hi, 1, np.where(price < lo, -1, 0))   # NaN norm compares False -> 0\n",
    "    flag = np.zeros(len(price), dtype=int)\n",
    "    run, last = 0, 0\n",
    "    for i, s in enumerate(side):\n",
    "        run = run + 1 if (s != 0 and s == last) else (1 if s != 0 else 0)\n",
    "        last = s\n",
    "        if s != 0 and run >= rule.n:\n",
    "            flag[i] = s\n",
    "    return flag\n",
    "\n",
    "\n",
    "def monthly_norm(price: np.ndarray, s: np.ndarray):\n",
    "    \"\"\"Seasonal-norm price by calendar month at the current level, for the storage calculator.\n",
    "\n",
    "    level: mean log deseasonalised price over the last 52 weeks, moved forward 25.5 weeks to\n",
    "    the latest week with the drift d (average weekly change in the log deseasonalised level\n",
    "    between the first and the last 52 weeks). Month m uses the mean of s over cycle positions\n",
    "    whose mid-week date falls in month m (dates of the reference period).\"\"\"\n",
    "    n = len(price)\n",
    "    des = np.log(price) - s[np.arange(n) % PERIOD]\n",
    "    d = (des[-52:].mean() - des[:52].mean()) / (n - 52)\n",
    "    level = des[-52:].mean() + d * 25.5\n",
    "    months = (dates() + pd.Timedelta(days=3)).month.values[:N_REF]\n",
    "    pos = np.arange(N_REF) % PERIOD\n",
    "    sm_ = np.array([s[pos[months == m]].mean() for m in range(1, 13)])\n",
    "    return np.round(np.exp(level + sm_), 2), round(float(d), 6)\n",
    "\n",
    "\n",
    "def seasonal_norms(df: pd.DataFrame, rule: AlertRule = AlertRule()) -> dict:\n",
    "    si = seasonal_index(df)\n",
    "    out = {}\n",
    "    for k in KEYS:\n",
    "        p = df[k].values\n",
    "        norm = seasonal_norm(p, si[k][\"index\"], rule)\n",
    "        mn, d = monthly_norm(p, si[k][\"index\"])\n",
    "        out[k] = dict(si[k], norm=norm, sigma=round(band_sigma(p, norm), 4), monthly_norm=mn, drift_week=d)\n",
    "    return out\n",
    "\n",
    "\n",
    "# The series each injected shock hits first, and its direction (for the detection table)\n",
    "SHOCK_TARGETS = {\"S1\": [\"onion_capital\"], \"S2\": [\"rice_parity\"], \"S3\": [\"rice_parity\", \"rice_capital\"],\n",
    "                 \"S4\": [\"rice_valley\", \"onion_valley\"], \"S5\": [\"onion_capital\"], \"S6\": [\"rice_valley\"],\n",
    "                 \"S7\": [\"onion_capital\"]}\n",
    "\n",
    "\n",
    "def evaluate_alerts(df: pd.DataFrame, norms: dict, rule: AlertRule = AlertRule(), buffer: int = 8):\n",
    "    \"\"\"(1) Detection: for each shock and each series it hits first, the first week (counted from\n",
    "    the shock start) with a flag in the shock's direction, within the shock window plus buffer.\n",
    "    (2) Flags outside every shock window of that crop (plus buffer), by period.\"\"\"\n",
    "    idx = dates()\n",
    "    flags = {k: alerts(df[k].values, norms[k][\"norm\"], norms[k][\"sigma\"], rule) for k in KEYS}\n",
    "    det = []\n",
    "    for s in SHOCKS:\n",
    "        t0 = idx.get_indexer([pd.Timestamp(s[\"start\"])])[0]\n",
    "        t1 = min(N_WEEKS, t0 + s[\"weeks\"] + buffer)\n",
    "        sign = 1 if s[\"size\"] > 0 else -1\n",
    "        if s[\"id\"] == \"S4\":\n",
    "            sign = -1        # road cut lowers valley prices\n",
    "        for k in SHOCK_TARGETS[s[\"id\"]]:\n",
    "            hit = np.nonzero(flags[k][t0:t1] == sign)[0]\n",
    "            det.append(dict(shock=s[\"id\"], start=s[\"start\"], kind=s[\"kind\"], series=k,\n",
    "                            direction=\"high\" if sign > 0 else \"low\",\n",
    "                            detected=bool(len(hit)), weeks_to_flag=(int(hit[0]) if len(hit) else None)))\n",
    "    rows = []\n",
    "    for k in KEYS:\n",
    "        crop = k.split(\"_\")[0]\n",
    "        in_window = np.zeros(N_WEEKS, dtype=bool)\n",
    "        for s in SHOCKS:\n",
    "            if s[\"crop\"] in (crop, \"both\"):\n",
    "                t0 = idx.get_indexer([pd.Timestamp(s[\"start\"])])[0]\n",
    "                in_window[t0:min(N_WEEKS, t0 + s[\"weeks\"] + buffer)] = True\n",
    "        valid = ~np.isnan(norms[k][\"norm\"])\n",
    "        for per, sl in ((\"reference\", slice(0, N_REF)), (\"monitoring\", slice(N_REF, N_WEEKS))):\n",
    "            f, w, v = flags[k][sl] != 0, in_window[sl], valid[sl]\n",
    "            rows.append(dict(series=k, period=per, weeks=int(v.sum()), flagged=int(f.sum()),\n",
    "                             flagged_outside_windows=int((f & ~w).sum()),\n",
    "                             weeks_outside_windows=int((~w & v).sum())))\n",
    "    tab = pd.DataFrame(rows)\n",
    "    tab[\"false_flag_rate\"] = (tab[\"flagged_outside_windows\"] / tab[\"weeks_outside_windows\"]).round(3)\n",
    "    return tab, pd.DataFrame(det)\n",
    "\n",
    "\n",
    "def rule_tradeoff(df, ks=(1.5, 2.0, 2.5), ns=(1, 2, 3)) -> pd.DataFrame:\n",
    "    \"\"\"Shocks detected (of 9 shock-series pairs) and false-flag rate outside shock windows, by k and n.\"\"\"\n",
    "    norms = seasonal_norms(df)\n",
    "    rows = []\n",
    "    for k in ks:\n",
    "        for n in ns:\n",
    "            r = AlertRule(k=k, n=n)\n",
    "            nr = {kk: dict(v, sigma=v[\"sigma\"]) for kk, v in norms.items()}\n",
    "            tab, det = evaluate_alerts(df, nr, r)\n",
    "            rows.append(dict(k=k, n=n, detected=int(det[\"detected\"].sum()), pairs=len(det),\n",
    "                             median_weeks_to_flag=float(det[\"weeks_to_flag\"].median()),\n",
    "                             false_flag_rate_reference=round(tab[tab.period == \"reference\"][\"flagged_outside_windows\"].sum()\n",
    "                                                             / tab[tab.period == \"reference\"][\"weeks_outside_windows\"].sum(), 3),\n",
    "                             false_flag_rate_monitoring=round(tab[tab.period == \"monitoring\"][\"flagged_outside_windows\"].sum()\n",
    "                                                              / tab[tab.period == \"monitoring\"][\"weeks_outside_windows\"].sum(), 3)))\n",
    "    return pd.DataFrame(rows)\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- spreads and margins\n",
    "\n",
    "MILLING_RATIO = GenParams().milling_ratio\n",
    "MILLING_COST_0 = GenParams().milling_cost\n",
    "\n",
    "\n",
    "def farmgate_equivalent(df: pd.DataFrame, crop: str) -> np.ndarray:\n",
    "    \"\"\"Farm-gate price in wholesale-product terms. Rice: (paddy + milling cost) / milling ratio,\n",
    "    milling cost indexed at 4% a year; onion: the farm-gate price itself.\"\"\"\n",
    "    if crop == \"onion\":\n",
    "        return df[\"onion_farmgate\"].values\n",
    "    infl = np.exp(np.log(1.04) * df[\"week\"].values / 52.0)\n",
    "    return (df[\"rice_farmgate\"].values + MILLING_COST_0 * infl) / MILLING_RATIO\n",
    "\n",
    "\n",
    "def spreads_margins(df: pd.DataFrame) -> pd.DataFrame:\n",
    "    out = pd.DataFrame({\"week\": df[\"week\"], \"date\": df[\"date\"]})\n",
    "    for crop in (\"rice\", \"onion\"):\n",
    "        cap = df[f\"{crop}_capital\"].values\n",
    "        out[f\"{crop}_spread\"] = (cap - df[f\"{crop}_valley\"].values).round(2)\n",
    "        out[f\"{crop}_margin_share\"] = ((cap - farmgate_equivalent(df, crop)) / cap).round(4)\n",
    "    out[\"rice_local_to_parity\"] = (df[\"rice_capital\"] / df[\"rice_parity\"]).round(4)\n",
    "    return out\n",
    "\n",
    "\n",
    "def same_week_reference_mean(x: np.ndarray, t: int) -> float:\n",
    "    \"\"\"Mean of x at t-52, t-104, ... restricted to the reference period (the 5-year norm).\"\"\"\n",
    "    vals = [x[j] for j in range(t - 52, -1, -52) if j < N_REF]\n",
    "    return float(np.mean(vals))\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- price transmission\n",
    "\n",
    "def transmission(df: pd.DataFrame, crop: str, seasonal: bool = False) -> dict:\n",
    "    \"\"\"Engle-Granger two-step on Valley market A (v) and Capital wholesale (c), levels, reference period.\n",
    "\n",
    "    Long run:  v_t = b0 + b1 c_t [+ two Fourier pairs of period 52 if seasonal] + e_t\n",
    "    ECM:       dv_t = a0 + alpha e_{t-1} + gamma dc_t + delta dv_{t-1} + u_t   (HAC standard errors, 4 lags)\n",
    "    Half-life of a deviation = ln(0.5) / ln(1 + alpha) weeks.\n",
    "    The Engle-Granger p-value (MacKinnon) is reported for the specification without Fourier terms.\n",
    "    \"\"\"\n",
    "    import statsmodels.api as sm\n",
    "    from statsmodels.tsa.stattools import adfuller, coint\n",
    "    v = df[f\"{crop}_valley\"].values[:N_REF]\n",
    "    c = df[f\"{crop}_capital\"].values[:N_REF]\n",
    "    t = np.arange(N_REF)\n",
    "    X = c[:, None]\n",
    "    if seasonal:\n",
    "        F = np.column_stack([f(2 * np.pi * j * t / PERIOD) for j in (1, 2) for f in (np.sin, np.cos)])\n",
    "        X = np.column_stack([c, F])\n",
    "    lr = sm.OLS(v, sm.add_constant(X)).fit()\n",
    "    e = lr.resid\n",
    "    t_stat, p_coint, _ = coint(v, c, trend=\"c\")\n",
    "    dv, dc = np.diff(v), np.diff(c)\n",
    "    Z = np.column_stack([e[1:-1], dc[1:], dv[:-1]])\n",
    "    ecm = sm.OLS(dv[1:], sm.add_constant(Z)).fit(cov_type=\"HAC\", cov_kwds={\"maxlags\": 4})\n",
    "    alpha = float(ecm.params[1])\n",
    "    g = GenParams()\n",
    "    return dict(\n",
    "        crop=crop, spec=\"with seasonal terms\" if seasonal else \"plain\",\n",
    "        adf_p_valley=float(adfuller(v, regression=\"ct\", autolag=\"AIC\")[1]),\n",
    "        adf_p_capital=float(adfuller(c, regression=\"ct\", autolag=\"AIC\")[1]),\n",
    "        b0=float(lr.params[0]), b1=float(lr.params[1]),\n",
    "        eg_t=float(t_stat), eg_p=float(p_coint),\n",
    "        alpha=alpha, alpha_se=float(ecm.bse[1]),\n",
    "        gamma=float(ecm.params[2]), gamma_se=float(ecm.bse[2]),\n",
    "        half_life_weeks=float(math.log(0.5) / math.log(1 + alpha)) if -1 < alpha < 0 else float(\"nan\"),\n",
    "        true_alpha=-(g.rice_alpha if crop == \"rice\" else g.onion_alpha),\n",
    "        true_gamma=g.rice_gamma if crop == \"rice\" else g.onion_gamma,\n",
    "    )\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- storage decision\n",
    "\n",
    "@dataclass(frozen=True)\n",
    "class Storage:\n",
    "    buy_month: int        # 1..12\n",
    "    sell_month: int       # 1..12, after buy_month (wraps into next year)\n",
    "    loss: float           # weight loss per month held (share)\n",
    "    finance: float        # financing cost per month, simple interest on purchase value\n",
    "    fee: float            # storage fee, LCU per tonne per month\n",
    "\n",
    "\n",
    "STORAGE_DEFAULTS = {\n",
    "    \"rice\": Storage(buy_month=12, sell_month=8, loss=0.005, finance=0.015, fee=250.0),    # paddy\n",
    "    \"onion\": Storage(buy_month=4, sell_month=9, loss=0.05, finance=0.015, fee=400.0),\n",
    "}\n",
    "\n",
    "\n",
    "def months_held(buy: int, sell: int) -> int:\n",
    "    m = (sell - buy) % 12\n",
    "    return 12 if m == 0 else m\n",
    "\n",
    "\n",
    "def storage_margin(monthly_norm, drift_week: float, s: Storage) -> dict:\n",
    "    \"\"\"Net margin per tonne stored (LCU/t), at seasonal-norm prices.\n",
    "\n",
    "    P_buy  = monthly_norm[buy];  P_sell = monthly_norm[sell] x exp(g m), g = drift_week x 52/12\n",
    "    sold   = (1 - loss)^m tonnes per tonne stored\n",
    "    net    = 1000 P_sell sold - 1000 P_buy (1 + finance m) - fee m\n",
    "    \"\"\"\n",
    "    m = months_held(s.buy_month, s.sell_month)\n",
    "    g = drift_week * 52.0 / 12.0\n",
    "    p_buy = float(monthly_norm[s.buy_month - 1])\n",
    "    p_sell = float(monthly_norm[s.sell_month - 1]) * math.exp(g * m)\n",
    "    sold = (1 - s.loss) ** m\n",
    "    revenue = 1000.0 * p_sell * sold\n",
    "    cost_goods = 1000.0 * p_buy\n",
    "    finance = cost_goods * s.finance * m\n",
    "    fees = s.fee * m\n",
    "    net = revenue - cost_goods - finance - fees\n",
    "    return dict(months=m, p_buy=p_buy, p_sell=p_sell, sold=sold, revenue=revenue, cost_goods=cost_goods,\n",
    "                finance=finance, fees=fees, lost_value=1000.0 * p_sell * (1 - sold), net=net,\n",
    "                return_on_stock=net / cost_goods)\n",
    "\n",
    "\n",
    "def storage_curve(monthly_norm, drift_week: float, s: Storage) -> pd.DataFrame:\n",
    "    \"\"\"Net margin for every possible sell month after the buy month (1..11 months held).\"\"\"\n",
    "    rows = []\n",
    "    for m in range(1, 12):\n",
    "        sell = (s.buy_month - 1 + m) % 12 + 1\n",
    "        r = storage_margin(monthly_norm, drift_week, Storage(s.buy_month, sell, s.loss, s.finance, s.fee))\n",
    "        rows.append(dict(sell_month=sell, **r))\n",
    "    cur = pd.DataFrame(rows)\n",
    "    return cur\n",
    "\n",
    "\n",
    "def break_even(cur: pd.DataFrame):\n",
    "    pos = cur[cur[\"net\"] >= 0]\n",
    "    return None if pos.empty else int(pos.iloc[0][\"sell_month\"])\n",
    "\n",
    "\n",
    "def break_even_finance(r: dict, s: Storage) -> float:\n",
    "    \"\"\"Monthly financing rate at which the plan breaks even: (revenue - goods - fees) / (goods x months).\"\"\"\n",
    "    return (r[\"revenue\"] - r[\"cost_goods\"] - r[\"fees\"]) / (r[\"cost_goods\"] * r[\"months\"])\n",
    "\n",
    "\n",
    "def break_even_loss(monthly_norm, drift_week: float, s: Storage) -> float:\n",
    "    \"\"\"Monthly loss rate at which the default buy/sell plan just breaks even (bisection).\"\"\"\n",
    "    lo, hi = 0.0, 0.5\n",
    "    f = lambda L: storage_margin(monthly_norm, drift_week, Storage(s.buy_month, s.sell_month, L, s.finance, s.fee))[\"net\"]\n",
    "    if f(lo) < 0:\n",
    "        return float(\"nan\")\n",
    "    for _ in range(100):\n",
    "        mid = 0.5 * (lo + hi)\n",
    "        if f(mid) >= 0:\n",
    "            lo = mid\n",
    "        else:\n",
    "            hi = mid\n",
    "    return lo\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- forecasting\n",
    "\n",
    "MODELS = (\"seasonal_naive\", \"sarima\", \"stl_ets\")\n",
    "HORIZON = 12\n",
    "Z80, Z95 = 1.2815515655446004, 1.959963984540054\n",
    "\n",
    "\n",
    "def _fc_seasonal_naive(y: np.ndarray, h: int):\n",
    "    \"\"\"log y_{T+j} = log y_{T+j-52}; interval from the SD of 52-week log differences.\"\"\"\n",
    "    d = y[52:] - y[:-52]\n",
    "    sd = d.std(ddof=1)\n",
    "    T = len(y)\n",
    "    mean = np.array([y[T - 52 + j] for j in range(h)])\n",
    "    sd_h = np.full(h, sd)\n",
    "    return mean, sd_h\n",
    "\n",
    "\n",
    "def _fc_sarima(y: np.ndarray, h: int):\n",
    "    \"\"\"SARIMA(1,0,0)(0,1,0)[52] with drift on log prices.\"\"\"\n",
    "    from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter(\"ignore\")\n",
    "        res = SARIMAX(y, order=(1, 0, 0), seasonal_order=(0, 1, 0, 52), trend=\"c\").fit(disp=False, maxiter=200)\n",
    "    f = res.get_forecast(h)\n",
    "    return np.asarray(f.predicted_mean), np.sqrt(np.asarray(f.var_pred_mean))\n",
    "\n",
    "\n",
    "def _fc_stl_ets(y: np.ndarray, h: int):\n",
    "    \"\"\"STL (robust, period 52) + ETS(A,Ad,N) on the seasonally adjusted log series.\"\"\"\n",
    "    from statsmodels.tsa.forecasting.stl import STLForecast\n",
    "    from statsmodels.tsa.exponential_smoothing.ets import ETSModel\n",
    "    y = pd.Series(y, index=pd.RangeIndex(len(y)))\n",
    "    mod = STLForecast(y, ETSModel, period=PERIOD, robust=True,\n",
    "                      model_kwargs=dict(error=\"add\", trend=\"add\", damped_trend=True))\n",
    "    res = mod.fit(fit_kwargs=dict(disp=False))\n",
    "    f = res.get_prediction(start=len(y), end=len(y) + h - 1)\n",
    "    sf = f.summary_frame(alpha=0.2)\n",
    "    mean = np.asarray(sf[\"mean\"])\n",
    "    sd = (np.asarray(sf[\"mean_ci_upper\"]) - mean) / Z80      # 80% prediction interval -> SD\n",
    "    return mean, sd\n",
    "\n",
    "\n",
    "FORECASTERS = {\"seasonal_naive\": _fc_seasonal_naive, \"sarima\": _fc_sarima, \"stl_ets\": _fc_stl_ets}\n",
    "\n",
    "\n",
    "def backtest(df: pd.DataFrame, origins=None, h: int = HORIZON) -> pd.DataFrame:\n",
    "    \"\"\"Rolling origin over the monitoring year: fit on weeks <= origin, forecast 1..h ahead.\n",
    "    Errors in price levels (median forecast exp(mean log)); 80% interval coverage.\"\"\"\n",
    "    if origins is None:\n",
    "        origins = list(range(N_REF - 1, N_WEEKS - h, 4))     # 259, 263, ..., 299\n",
    "    rows = []\n",
    "    for k in KEYS:\n",
    "        y = np.log(df[k].values)\n",
    "        for o in origins:\n",
    "            for m in MODELS:\n",
    "                mean, sd = FORECASTERS[m](y[: o + 1], h)\n",
    "                for j in range(h):\n",
    "                    actual = df[k].values[o + 1 + j]\n",
    "                    pred = math.exp(mean[j])\n",
    "                    lo, hi = math.exp(mean[j] - Z80 * sd[j]), math.exp(mean[j] + Z80 * sd[j])\n",
    "                    rows.append(dict(series=k, origin=o, model=m, h=j + 1, actual=actual, pred=pred,\n",
    "                                     ape=abs(pred - actual) / actual, covered80=int(lo <= actual <= hi)))\n",
    "    return pd.DataFrame(rows)\n",
    "\n",
    "\n",
    "def backtest_summary(bt: pd.DataFrame) -> pd.DataFrame:\n",
    "    bt = bt.copy()\n",
    "    bt[\"hgroup\"] = np.where(bt[\"h\"] <= 4, \"h1_4\", \"h5_12\")\n",
    "    a = bt.pivot_table(index=[\"series\", \"model\"], columns=\"hgroup\", values=\"ape\", aggfunc=\"mean\")\n",
    "    a[\"mape_all\"] = bt.groupby([\"series\", \"model\"])[\"ape\"].mean()\n",
    "    a[\"cover80\"] = bt.groupby([\"series\", \"model\"])[\"covered80\"].mean()\n",
    "    return (a * 100).round(1).reset_index()\n",
    "\n",
    "\n",
    "def best_models(bs: pd.DataFrame) -> dict:\n",
    "    \"\"\"Per crop, the model with the lowest backtest MAPE averaged over that crop's series (1-12 weeks).\"\"\"\n",
    "    bs = bs.assign(crop=bs[\"series\"].str.split(\"_\").str[0])\n",
    "    return {c: g.groupby(\"model\")[\"mape_all\"].mean().idxmin() for c, g in bs.groupby(\"crop\")}\n",
    "\n",
    "\n",
    "def forecast(df: pd.DataFrame, models: dict, h: int = HORIZON) -> dict:\n",
    "    \"\"\"12-week forecast bands for every series with its crop's model (dict crop -> model name).\"\"\"\n",
    "    out = {}\n",
    "    for k in KEYS:\n",
    "        y = np.log(df[k].values)\n",
    "        mean, sd = FORECASTERS[models[k.split(\"_\")[0]]](y, h)\n",
    "        out[k] = dict(\n",
    "            median=np.round(np.exp(mean), 2),\n",
    "            lo80=np.round(np.exp(mean - Z80 * sd), 2), hi80=np.round(np.exp(mean + Z80 * sd), 2),\n",
    "            lo95=np.round(np.exp(mean - Z95 * sd), 2), hi95=np.round(np.exp(mean + Z95 * sd), 2),\n",
    "        )\n",
    "    return out\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- headline numbers\n",
    "\n",
    "def headline(df, norms, rule: AlertRule = AlertRule(), fc=None) -> dict:\n",
    "    T = N_WEEKS - 1\n",
    "    sm_ = spreads_margins(df)\n",
    "    out = {\"last_date\": df[\"date\"].iloc[-1]}\n",
    "    for k in KEYS:\n",
    "        p = df[k].values\n",
    "        flag = alerts(p, norms[k][\"norm\"], norms[k][\"sigma\"], rule)\n",
    "        out[k] = dict(latest=float(p[T]), norm=float(norms[k][\"norm\"][T]),\n",
    "                      dev=float(p[T] / norms[k][\"norm\"][T] - 1),\n",
    "                      flagged_monitoring=int((flag[N_REF:] != 0).sum()),\n",
    "                      flag_now=int(flag[T]))\n",
    "        if fc is not None:\n",
    "            out[k][\"fc4\"] = (float(fc[k][\"median\"][3]), float(fc[k][\"lo80\"][3]), float(fc[k][\"hi80\"][3]))\n",
    "    for crop in (\"rice\", \"onion\"):\n",
    "        sp = sm_[f\"{crop}_spread\"].values\n",
    "        mg = sm_[f\"{crop}_margin_share\"].values\n",
    "        cap = df[f\"{crop}_capital\"].values\n",
    "        out[f\"{crop}_spread\"] = dict(latest=float(sp[T]), share=float(sp[T] / cap[T]),\n",
    "                                     norm=same_week_reference_mean(sp, T))\n",
    "        out[f\"{crop}_margin\"] = dict(latest=float(mg[T]), norm=same_week_reference_mean(mg, T))\n",
    "        s = STORAGE_DEFAULTS[crop]\n",
    "        k = f\"{crop}_farmgate\"\n",
    "        r = storage_margin(norms[k][\"monthly_norm\"], norms[k][\"drift_week\"], s)\n",
    "        cur = storage_curve(norms[k][\"monthly_norm\"], norms[k][\"drift_week\"], s)\n",
    "        best = cur.loc[cur[\"net\"].idxmax()]\n",
    "        out[f\"{crop}_storage\"] = dict(net=r[\"net\"], ret=r[\"return_on_stock\"], months=r[\"months\"],\n",
    "                                      p_buy=r[\"p_buy\"], p_sell=r[\"p_sell\"],\n",
    "                                      break_even_month=break_even(cur),\n",
    "                                      best_month=int(best[\"sell_month\"]), best_net=float(best[\"net\"]),\n",
    "                                      paying_months=[int(x) for x in cur[cur[\"net\"] >= 0][\"sell_month\"]],\n",
    "                                      break_even_finance=break_even_finance(r, s),\n",
    "                                      break_even_loss=break_even_loss(norms[k][\"monthly_norm\"], norms[k][\"drift_week\"], s))\n",
    "    return out\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- figures\n",
    "\n",
    "def _plt():\n",
    "    import matplotlib\n",
    "    matplotlib.use(\"Agg\")\n",
    "    import matplotlib.pyplot as plt\n",
    "    plt.rcParams.update({\"font.size\": 10, \"axes.spines.top\": False, \"axes.spines.right\": False})\n",
    "    return plt\n",
    "\n",
    "\n",
    "LABEL = {k: lab for k, _, _, lab in SERIES}\n",
    "\n",
    "\n",
    "def fig_bands(df, norms, out: Path, rule: AlertRule = AlertRule()):\n",
    "    \"\"\"Price, seasonal norm, band and flags for the two capital wholesale series and two farm-gate series.\"\"\"\n",
    "    plt = _plt()\n",
    "    x = pd.to_datetime(df[\"date\"])\n",
    "    keys = [\"rice_farmgate\", \"rice_capital\", \"onion_farmgate\", \"onion_capital\"]\n",
    "    fig, axs = plt.subplots(4, 1, figsize=(10, 11), sharex=True)\n",
    "    for ax, k in zip(axs, keys):\n",
    "        nm = norms[k]\n",
    "        lo, hi = band(nm[\"norm\"], nm[\"sigma\"], rule.k)\n",
    "        f = alerts(df[k].values, nm[\"norm\"], nm[\"sigma\"], rule)\n",
    "        ax.fill_between(x, lo, hi, color=\"#1f5f63\", alpha=0.15, lw=0, label=f\"band (norm x exp(+/-{rule.k:g} sigma))\")\n",
    "        ax.plot(x, nm[\"norm\"], color=\"#1f5f63\", lw=1, ls=\"--\", label=\"seasonal norm\")\n",
    "        ax.plot(x, df[k], color=\"#16181d\", lw=1.2, label=\"price\")\n",
    "        for sgn, col in ((1, \"#a3471c\"), (-1, \"#9a7420\")):\n",
    "            m = f == sgn\n",
    "            ax.scatter(x[m], df[k].values[m], s=10, color=col, zorder=3, label=\"flag: high\" if sgn > 0 else \"flag: low\")\n",
    "        ax.axvline(x.iloc[N_REF], color=\"#4f545e\", lw=0.8, ls=\":\")\n",
    "        ax.set_title(LABEL[k], loc=\"left\", fontsize=10)\n",
    "        ax.set_ylabel(\"LCU/kg\")\n",
    "    axs[0].legend(ncol=5, fontsize=8, loc=\"upper left\", frameon=False)\n",
    "    axs[-1].text(x.iloc[N_REF], axs[-1].get_ylim()[0], \"  monitoring year\", va=\"bottom\", fontsize=8, color=\"#4f545e\")\n",
    "    fig.tight_layout()\n",
    "    fig.savefig(out / \"price_bands.png\", dpi=130)\n",
    "    plt.close(fig)\n",
    "\n",
    "\n",
    "def fig_stl(df, norms, out: Path):\n",
    "    plt = _plt()\n",
    "    x = pd.to_datetime(df[\"date\"]).iloc[:N_REF]\n",
    "    fig, axs = plt.subplots(3, 2, figsize=(10, 6.5), sharex=True)\n",
    "    for j, k in enumerate([\"rice_farmgate\", \"onion_farmgate\"]):\n",
    "        nm = norms[k]\n",
    "        axs[0, j].plot(x, df[k].values[:N_REF], color=\"#16181d\", lw=1)\n",
    "        axs[0, j].plot(x, np.exp(nm[\"trend\"]), color=\"#1f5f63\", lw=1.5)\n",
    "        axs[0, j].set_title(LABEL[k] + \": price and STL trend\", loc=\"left\", fontsize=9)\n",
    "        axs[1, j].plot(x, 100 * nm[\"seasonal\"], color=\"#9a7420\", lw=1)\n",
    "        axs[1, j].set_title(\"seasonal component (% of trend, log points x 100)\", loc=\"left\", fontsize=9)\n",
    "        axs[2, j].plot(x, 100 * nm[\"remainder\"], color=\"#a3471c\", lw=0.8)\n",
    "        axs[2, j].set_title(\"remainder (log points x 100)\", loc=\"left\", fontsize=9)\n",
    "    fig.tight_layout()\n",
    "    fig.savefig(out / \"stl_decomposition.png\", dpi=130)\n",
    "    plt.close(fig)\n",
    "\n",
    "\n",
    "def fig_storage(norms, out: Path):\n",
    "    plt = _plt()\n",
    "    mon = [\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\", \"Aug\", \"Sep\", \"Oct\", \"Nov\", \"Dec\"]\n",
    "    fig, axs = plt.subplots(1, 2, figsize=(10, 3.8))\n",
    "    for ax, crop in zip(axs, (\"rice\", \"onion\")):\n",
    "        s = STORAGE_DEFAULTS[crop]\n",
    "        k = f\"{crop}_farmgate\"\n",
    "        cur = storage_curve(norms[k][\"monthly_norm\"], norms[k][\"drift_week\"], s)\n",
    "        cols = [\"#1f5f63\" if v >= 0 else \"#a3471c\" for v in cur[\"net\"]]\n",
    "        ax.bar([mon[m - 1] for m in cur[\"sell_month\"]], cur[\"net\"], color=cols)\n",
    "        ax.axhline(0, color=\"#4f545e\", lw=0.8)\n",
    "        ax.set_title(f\"{LABEL[k]}: bought in {mon[s.buy_month - 1]}, net margin by sell month (LCU/t)\",\n",
    "                     loc=\"left\", fontsize=9)\n",
    "        ax.tick_params(axis=\"x\", labelsize=8)\n",
    "    fig.tight_layout()\n",
    "    fig.savefig(out / \"storage_margin.png\", dpi=130)\n",
    "    plt.close(fig)\n",
    "\n",
    "\n",
    "def fig_forecast(df, fc, out: Path, keys=(\"rice_capital\", \"onion_capital\"), back: int = 52):\n",
    "    plt = _plt()\n",
    "    x = pd.to_datetime(df[\"date\"])\n",
    "    xf = pd.date_range(x.iloc[-1] + pd.Timedelta(days=7), periods=HORIZON, freq=\"7D\")\n",
    "    fig, axs = plt.subplots(1, len(keys), figsize=(10, 3.6))\n",
    "    for ax, k in zip(axs, keys):\n",
    "        ax.plot(x.iloc[-back:], df[k].values[-back:], color=\"#16181d\", lw=1.2)\n",
    "        ax.fill_between(xf, fc[k][\"lo95\"], fc[k][\"hi95\"], color=\"#9a7420\", alpha=0.15, lw=0, label=\"95%\")\n",
    "        ax.fill_between(xf, fc[k][\"lo80\"], fc[k][\"hi80\"], color=\"#9a7420\", alpha=0.35, lw=0, label=\"80%\")\n",
    "        ax.plot(xf, fc[k][\"median\"], color=\"#9a7420\", lw=1.2, ls=\"--\", label=\"median\")\n",
    "        ax.set_title(LABEL[k] + \": 12-week forecast band\", loc=\"left\", fontsize=9)\n",
    "        ax.tick_params(axis=\"x\", labelsize=8)\n",
    "    axs[0].legend(fontsize=8, frameon=False, loc=\"upper left\")\n",
    "    fig.tight_layout()\n",
    "    fig.savefig(out / \"forecast_bands.png\", dpi=130)\n",
    "    plt.close(fig)\n",
    "\n",
    "\n",
    "# ---------------------------------------------------------------- export for the website demo\n",
    "\n",
    "def export_ts(path: Path, df, norms, fc, model: dict, bt_sum: pd.DataFrame, rule: AlertRule = AlertRule()):\n",
    "    def arr(a):\n",
    "        return \"[\" + \",\".join(f\"{x:.2f}\".rstrip(\"0\").rstrip(\".\") for x in a) + \"]\"\n",
    "    lines = [\n",
    "        \"// Synthetic data for the MarketPriceMonitor demo. GENERATED by\",\n",
    "        \"// public/artifacts/agricultural-market-intelligence/market_intelligence.py --ts-out. Do not edit by hand.\",\n",
    "        \"// Prices in LCU/kg (generic local currency unit). Not the prices of any real market.\",\n",
    "        \"export type SeriesKey = \" + \" | \".join(f\"'{k}'\" for k in KEYS) + \";\",\n",
    "        \"export type SeriesData = { price: number[]; sIndex: number[]; sigma: number; driftWeek: number; monthlyNorm: number[];\",\n",
    "        \"  fc: { median: number[]; lo80: number[]; hi80: number[]; lo95: number[]; hi95: number[] };\",\n",
    "        \"  mape: { seasonal_naive: number; sarima: number; stl_ets: number } };\",\n",
    "        f\"export const START_DATE = '{START.strftime('%Y-%m-%d')}';\",\n",
    "        f\"export const N_WEEKS = {N_WEEKS};\",\n",
    "        f\"export const N_REF = {N_REF};\",\n",
    "        f\"export const FORECAST_MODEL: Record<'rice' | 'onion', 'seasonal_naive' | 'sarima' | 'stl_ets'> = {json.dumps(model)};\",\n",
    "        f\"export const ALERT_DEFAULTS = {{ k: {rule.k}, n: {rule.n}, window: {rule.window}, gap: {rule.gap} }};\",\n",
    "        \"export const DATA: Record<SeriesKey, SeriesData> = {\",\n",
    "    ]\n",
    "    for k in KEYS:\n",
    "        nm = norms[k]\n",
    "        f = fc[k]\n",
    "        mp = {m: float(bt_sum[(bt_sum.series == k) & (bt_sum.model == m)][\"mape_all\"].iloc[0]) for m in MODELS}\n",
    "        sidx = \"[\" + \",\".join(f\"{x:.5f}\".rstrip(\"0\").rstrip(\".\") for x in nm[\"index\"]) + \"]\"\n",
    "        lines.append(f\"  {k}: {{ price: {arr(df[k].values)}, sIndex: {sidx}, sigma: {nm['sigma']}, \"\n",
    "                     f\"driftWeek: {nm['drift_week']}, monthlyNorm: {arr(nm['monthly_norm'])},\")\n",
    "        lines.append(f\"    fc: {{ median: {arr(f['median'])}, lo80: {arr(f['lo80'])}, hi80: {arr(f['hi80'])}, \"\n",
    "                     f\"lo95: {arr(f['lo95'])}, hi95: {arr(f['hi95'])} }},\")\n",
    "        lines.append(f\"    mape: {json.dumps(mp)} }},\")\n",
    "    lines.append(\"};\")\n",
    "    path.write_text(\"\\n\".join(lines) + \"\\n\")\n",
    "\n",
    "\n",
    "def parameter_table() -> pd.DataFrame:\n",
    "    g = GenParams()\n",
    "    rows = [(k, v) for k, v in asdict(g).items()]\n",
    "    tab = pd.DataFrame(rows, columns=[\"parameter\", \"value\"])\n",
    "    tab[\"status\"] = \"illustrative\"\n",
    "    return tab\n",
    "\n",
    "\n",
    "def main(argv=None):\n",
    "    ap = argparse.ArgumentParser()\n",
    "    ap.add_argument(\"--out\", default=str(Path(__file__).resolve().parent))\n",
    "    ap.add_argument(\"--ts-out\", default=None)\n",
    "    a = ap.parse_args(argv)\n",
    "    out = Path(a.out)\n",
    "    df = generate()\n",
    "    df.to_csv(out / \"synthetic_prices_weekly.csv\", index=False)\n",
    "    norms = seasonal_norms(df)\n",
    "    tab, det = evaluate_alerts(df, norms)\n",
    "    tab.to_csv(out / \"alert_false_flags.csv\", index=False)\n",
    "    det.to_csv(out / \"alert_detection.csv\", index=False)\n",
    "    print(tab.groupby(\"period\")[[\"flagged\", \"flagged_outside_windows\", \"weeks_outside_windows\"]].sum())\n",
    "    print(det.to_string(index=False))\n",
    "    tr = pd.DataFrame([transmission(df, c, sz) for c in (\"rice\", \"onion\") for sz in (False, True)])\n",
    "    tr.round(4).to_csv(out / \"price_transmission.csv\", index=False)\n",
    "    print(tr.round(3).to_string())\n",
    "    bt = backtest(df)\n",
    "    bs = backtest_summary(bt)\n",
    "    bs.to_csv(out / \"forecast_backtest.csv\", index=False)\n",
    "    print(bs.groupby(\"model\")[[\"h1_4\", \"h5_12\", \"mape_all\", \"cover80\"]].mean().round(1))\n",
    "    model = best_models(bs)\n",
    "    fc = forecast(df, model)\n",
    "    hl = headline(df, norms, fc=fc)\n",
    "    hl[\"forecast_model\"] = model\n",
    "    (out / \"headline_numbers.json\").write_text(json.dumps(hl, indent=1, default=float))\n",
    "    print(json.dumps(hl, indent=1, default=float))\n",
    "    fig_bands(df, norms, out)\n",
    "    fig_stl(df, norms, out)\n",
    "    fig_storage(norms, out)\n",
    "    fig_forecast(df, fc, out)\n",
    "    if a.ts_out:\n",
    "        export_ts(Path(a.ts_out), df, norms, fc, model, bs)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4c27544",
   "metadata": {},
   "source": [
    "## 1. The synthetic data\n",
    "\n",
    "Six years of weekly prices, 16 November 2020 to 2 November 2026 (312 weeks). Weeks 0–259 form the **five-year reference period** used to estimate seasonality and calibrate the band. Weeks 260–311 are the **monitoring year**, handled as a live bulletin would handle them: with seasonal factors frozen at the end of the reference period.\n",
    "\n",
    "How the generator builds the prices (all parameters illustrative):\n",
    "\n",
    "- **Import parity, rice (capital):** $IPP_t = \\frac{(FOB_t + F)\\,e_t}{1000}(1+\\tau)(1+m) + c^{port}_t + c^{haul}_t$, with world FOB price $FOB_t$ (US\\$/t, persistent random process), freight $F$ = US\\$55/t, exchange rate $e_t$ (LCU per US\\$, random walk with 3% yearly depreciation), duty and taxes $\\tau$ = 10%, importer margin $m$ = 6%, port and haulage costs indexed to 4% yearly inflation.\n",
    "- **Local milled rice, capital:** a quality discount (0.85) on import parity, 60% pass-through of import-parity movements in logs, plus a harvest-calendar seasonal profile.\n",
    "- **Onion, capital:** a strong single-harvest seasonal profile plus persistent noise.\n",
    "- **Valley market A:** an error-correction process towards the capital price minus a transfer cost that rises at harvest, with adjustment speed $\\alpha$ = 0.25 (rice) and 0.35 (onion).\n",
    "- **Regional market:** a weighted average of capital and valley plus noise. **Farm gate:** paddy = 0.65 × valley milled price − milling cost, with a harvest discount; onion = 0.8 × valley price − field-to-market cost.\n",
    "- **Seven shocks** are injected (table below) so that the alert rule can be tested against known events."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f7e14a16",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:26.964398Z",
     "iopub.status.busy": "2026-11-07T02:11:26.964126Z",
     "iopub.status.idle": "2026-11-07T02:11:27.008772Z",
     "shell.execute_reply": "2026-11-07T02:11:27.007890Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(312, 14)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>rice_farmgate</th>\n",
       "      <td>312.0</td>\n",
       "      <td>29.43</td>\n",
       "      <td>3.39</td>\n",
       "      <td>21.91</td>\n",
       "      <td>27.47</td>\n",
       "      <td>28.95</td>\n",
       "      <td>31.61</td>\n",
       "      <td>37.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_valley</th>\n",
       "      <td>312.0</td>\n",
       "      <td>50.97</td>\n",
       "      <td>5.11</td>\n",
       "      <td>39.77</td>\n",
       "      <td>47.95</td>\n",
       "      <td>50.46</td>\n",
       "      <td>54.15</td>\n",
       "      <td>63.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_regional</th>\n",
       "      <td>312.0</td>\n",
       "      <td>55.73</td>\n",
       "      <td>5.28</td>\n",
       "      <td>44.21</td>\n",
       "      <td>52.08</td>\n",
       "      <td>55.68</td>\n",
       "      <td>59.18</td>\n",
       "      <td>68.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_capital</th>\n",
       "      <td>312.0</td>\n",
       "      <td>59.68</td>\n",
       "      <td>5.52</td>\n",
       "      <td>48.36</td>\n",
       "      <td>55.28</td>\n",
       "      <td>59.97</td>\n",
       "      <td>63.66</td>\n",
       "      <td>71.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_parity</th>\n",
       "      <td>312.0</td>\n",
       "      <td>73.75</td>\n",
       "      <td>8.25</td>\n",
       "      <td>57.77</td>\n",
       "      <td>66.28</td>\n",
       "      <td>74.26</td>\n",
       "      <td>78.92</td>\n",
       "      <td>92.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_farmgate</th>\n",
       "      <td>312.0</td>\n",
       "      <td>17.97</td>\n",
       "      <td>4.37</td>\n",
       "      <td>8.57</td>\n",
       "      <td>14.36</td>\n",
       "      <td>18.26</td>\n",
       "      <td>20.62</td>\n",
       "      <td>29.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_valley</th>\n",
       "      <td>312.0</td>\n",
       "      <td>24.18</td>\n",
       "      <td>5.21</td>\n",
       "      <td>12.46</td>\n",
       "      <td>20.22</td>\n",
       "      <td>24.40</td>\n",
       "      <td>27.30</td>\n",
       "      <td>39.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_regional</th>\n",
       "      <td>312.0</td>\n",
       "      <td>27.45</td>\n",
       "      <td>5.15</td>\n",
       "      <td>15.29</td>\n",
       "      <td>23.80</td>\n",
       "      <td>27.51</td>\n",
       "      <td>30.11</td>\n",
       "      <td>44.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_capital</th>\n",
       "      <td>312.0</td>\n",
       "      <td>30.23</td>\n",
       "      <td>5.06</td>\n",
       "      <td>17.52</td>\n",
       "      <td>26.60</td>\n",
       "      <td>30.20</td>\n",
       "      <td>32.92</td>\n",
       "      <td>47.26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count   mean   std    min    25%    50%    75%    max\n",
       "rice_farmgate   312.0  29.43  3.39  21.91  27.47  28.95  31.61  37.89\n",
       "rice_valley     312.0  50.97  5.11  39.77  47.95  50.46  54.15  63.20\n",
       "rice_regional   312.0  55.73  5.28  44.21  52.08  55.68  59.18  68.06\n",
       "rice_capital    312.0  59.68  5.52  48.36  55.28  59.97  63.66  71.53\n",
       "rice_parity     312.0  73.75  8.25  57.77  66.28  74.26  78.92  92.98\n",
       "onion_farmgate  312.0  17.97  4.37   8.57  14.36  18.26  20.62  29.92\n",
       "onion_valley    312.0  24.18  5.21  12.46  20.22  24.40  27.30  39.31\n",
       "onion_regional  312.0  27.45  5.15  15.29  23.80  27.51  30.11  44.50\n",
       "onion_capital   312.0  30.23  5.06  17.52  26.60  30.20  32.92  47.26"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = generate()\n",
    "df.to_csv('synthetic_prices_weekly.csv', index=False)\n",
    "print(df.shape)\n",
    "df[KEYS].describe().round(2).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c77a036e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:27.010570Z",
     "iopub.status.busy": "2026-11-07T02:11:27.010374Z",
     "iopub.status.idle": "2026-11-07T02:11:27.019405Z",
     "shell.execute_reply": "2026-11-07T02:11:27.018470Z"
    }
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>start</th>\n",
       "      <th>weeks</th>\n",
       "      <th>crop</th>\n",
       "      <th>where</th>\n",
       "      <th>kind</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>2022-08-29</td>\n",
       "      <td>10</td>\n",
       "      <td>onion</td>\n",
       "      <td>capital</td>\n",
       "      <td>supply shortfall</td>\n",
       "      <td>0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>2023-02-06</td>\n",
       "      <td>6</td>\n",
       "      <td>rice</td>\n",
       "      <td>parity</td>\n",
       "      <td>exchange-rate depreciation (persistent)</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>2023-08-07</td>\n",
       "      <td>14</td>\n",
       "      <td>rice</td>\n",
       "      <td>parity</td>\n",
       "      <td>world price spike</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>2024-08-12</td>\n",
       "      <td>8</td>\n",
       "      <td>both</td>\n",
       "      <td>valley</td>\n",
       "      <td>road cut: transfer cost up</td>\n",
       "      <td>8.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5</td>\n",
       "      <td>2025-03-10</td>\n",
       "      <td>8</td>\n",
       "      <td>onion</td>\n",
       "      <td>capital</td>\n",
       "      <td>bumper harvest glut</td>\n",
       "      <td>-0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S6</td>\n",
       "      <td>2025-12-08</td>\n",
       "      <td>6</td>\n",
       "      <td>rice</td>\n",
       "      <td>valley</td>\n",
       "      <td>harvest glut, late paddy payments</td>\n",
       "      <td>-0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>S7</td>\n",
       "      <td>2026-09-14</td>\n",
       "      <td>8</td>\n",
       "      <td>onion</td>\n",
       "      <td>capital</td>\n",
       "      <td>storage losses, early stock-out</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id       start  weeks   crop    where  \\\n",
       "0  S1  2022-08-29     10  onion  capital   \n",
       "1  S2  2023-02-06      6   rice   parity   \n",
       "2  S3  2023-08-07     14   rice   parity   \n",
       "3  S4  2024-08-12      8   both   valley   \n",
       "4  S5  2025-03-10      8  onion  capital   \n",
       "5  S6  2025-12-08      6   rice   valley   \n",
       "6  S7  2026-09-14      8  onion  capital   \n",
       "\n",
       "                                      kind  size  \n",
       "0                         supply shortfall  0.35  \n",
       "1  exchange-rate depreciation (persistent)  0.12  \n",
       "2                        world price spike  0.30  \n",
       "3               road cut: transfer cost up  8.00  \n",
       "4                      bumper harvest glut -0.25  \n",
       "5        harvest glut, late paddy payments -0.10  \n",
       "6          storage losses, early stock-out  0.30  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(SHOCKS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "24c6c1fc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:27.020865Z",
     "iopub.status.busy": "2026-11-07T02:11:27.020687Z",
     "iopub.status.idle": "2026-11-07T02:11:27.030350Z",
     "shell.execute_reply": "2026-11-07T02:11:27.029069Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>parameter</th>\n",
       "      <th>value</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>inflation</td>\n",
       "      <td>0.04</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fob0</td>\n",
       "      <td>480.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>freight</td>\n",
       "      <td>55.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>fx0</td>\n",
       "      <td>100.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>fx_drift</td>\n",
       "      <td>0.03</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>duty</td>\n",
       "      <td>0.10</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>importer_margin</td>\n",
       "      <td>0.06</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>port_cost</td>\n",
       "      <td>2.50</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>haul_cost</td>\n",
       "      <td>1.50</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>quality_discount</td>\n",
       "      <td>0.85</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ipp_passthrough</td>\n",
       "      <td>0.60</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>milling_ratio</td>\n",
       "      <td>0.65</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>milling_cost</td>\n",
       "      <td>3.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>rice_transfer</td>\n",
       "      <td>7.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>onion_transfer</td>\n",
       "      <td>5.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>rice_alpha</td>\n",
       "      <td>0.25</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>onion_alpha</td>\n",
       "      <td>0.35</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>rice_gamma</td>\n",
       "      <td>0.30</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>onion_gamma</td>\n",
       "      <td>0.40</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>onion_base</td>\n",
       "      <td>26.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>onion_farm_share</td>\n",
       "      <td>0.80</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>onion_farm_cost</td>\n",
       "      <td>1.00</td>\n",
       "      <td>illustrative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           parameter   value        status\n",
       "0          inflation    0.04  illustrative\n",
       "1               fob0  480.00  illustrative\n",
       "2            freight   55.00  illustrative\n",
       "3                fx0  100.00  illustrative\n",
       "4           fx_drift    0.03  illustrative\n",
       "5               duty    0.10  illustrative\n",
       "6    importer_margin    0.06  illustrative\n",
       "7          port_cost    2.50  illustrative\n",
       "8          haul_cost    1.50  illustrative\n",
       "9   quality_discount    0.85  illustrative\n",
       "10   ipp_passthrough    0.60  illustrative\n",
       "11     milling_ratio    0.65  illustrative\n",
       "12      milling_cost    3.00  illustrative\n",
       "13     rice_transfer    7.00  illustrative\n",
       "14    onion_transfer    5.00  illustrative\n",
       "15        rice_alpha    0.25  illustrative\n",
       "16       onion_alpha    0.35  illustrative\n",
       "17        rice_gamma    0.30  illustrative\n",
       "18       onion_gamma    0.40  illustrative\n",
       "19        onion_base   26.00  illustrative\n",
       "20  onion_farm_share    0.80  illustrative\n",
       "21   onion_farm_cost    1.00  illustrative"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parameter_table()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6877e615",
   "metadata": {},
   "source": [
    "## 2. Seasonal decomposition (STL)\n",
    "\n",
    "Robust STL (Cleveland et al., 1990, as implemented in statsmodels), period 52 weeks, seasonal window 7, on log prices of the reference period. The seasonal component is averaged at each of the 52 positions of the cycle to give a fixed **seasonal index** $s_p$ (centred on zero). Seasonal strength is $\\max(0, 1 - \\mathrm{Var}(R)/\\mathrm{Var}(S+R))$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7b2bc78d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:27.032247Z",
     "iopub.status.busy": "2026-11-07T02:11:27.032026Z",
     "iopub.status.idle": "2026-11-07T02:11:28.305135Z",
     "shell.execute_reply": "2026-11-07T02:11:28.303930Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seasonal_strength</th>\n",
       "      <th>index_min_pct</th>\n",
       "      <th>index_max_pct</th>\n",
       "      <th>band_sigma</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>rice_farmgate</th>\n",
       "      <td>0.76</td>\n",
       "      <td>-13.9</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.0433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_valley</th>\n",
       "      <td>0.68</td>\n",
       "      <td>-8.7</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_regional</th>\n",
       "      <td>0.64</td>\n",
       "      <td>-7.2</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0.0281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_capital</th>\n",
       "      <td>0.56</td>\n",
       "      <td>-5.3</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.0245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_parity</th>\n",
       "      <td>0.34</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.0376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_farmgate</th>\n",
       "      <td>0.84</td>\n",
       "      <td>-50.2</td>\n",
       "      <td>24.8</td>\n",
       "      <td>0.0900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_valley</th>\n",
       "      <td>0.81</td>\n",
       "      <td>-34.9</td>\n",
       "      <td>20.5</td>\n",
       "      <td>0.0806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_regional</th>\n",
       "      <td>0.81</td>\n",
       "      <td>-31.5</td>\n",
       "      <td>16.6</td>\n",
       "      <td>0.0641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_capital</th>\n",
       "      <td>0.73</td>\n",
       "      <td>-25.2</td>\n",
       "      <td>12.6</td>\n",
       "      <td>0.0595</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                seasonal_strength  index_min_pct  index_max_pct  band_sigma\n",
       "rice_farmgate                0.76          -13.9            9.8      0.0433\n",
       "rice_valley                  0.68           -8.7            7.0      0.0387\n",
       "rice_regional                0.64           -7.2            6.8      0.0281\n",
       "rice_capital                 0.56           -5.3            4.6      0.0245\n",
       "rice_parity                  0.34           -4.0            4.6      0.0376\n",
       "onion_farmgate               0.84          -50.2           24.8      0.0900\n",
       "onion_valley                 0.81          -34.9           20.5      0.0806\n",
       "onion_regional               0.81          -31.5           16.6      0.0641\n",
       "onion_capital                0.73          -25.2           12.6      0.0595"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norms = seasonal_norms(df)\n",
    "pd.DataFrame({k: dict(seasonal_strength=round(norms[k]['strength'], 2),\n",
    "                      index_min_pct=round(100 * norms[k]['index'].min(), 1),\n",
    "                      index_max_pct=round(100 * norms[k]['index'].max(), 1),\n",
    "                      band_sigma=norms[k]['sigma']) for k in KEYS}).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f0f34344",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:28.307375Z",
     "iopub.status.busy": "2026-11-07T02:11:28.307127Z",
     "iopub.status.idle": "2026-11-07T02:11:29.078438Z",
     "shell.execute_reply": "2026-11-07T02:11:29.077559Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "fig_stl(df, norms, Path('.'))\n",
    "Image('stl_decomposition.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf58a979",
   "metadata": {},
   "source": [
    "## 3. Seasonal norm, band and alert rule\n",
    "\n",
    "**Norm (causal).** $norm_t = e^{s_{t \\bmod 52}} \\times L_t$, where $L_t$ is the median of the deseasonalised price $p_j / e^{s_{j \\bmod 52}}$ over weeks $t-16$ to $t-4$ (a 13-week window that ends four weeks before the current week). The gap keeps a new shock out of its own baseline for a month.\n",
    "\n",
    "**Band.** $norm_t \\times e^{\\pm k\\sigma}$, with $\\sigma$ the robust standard deviation (1.4826 × median absolute deviation) of $\\log(p_t / norm_t)$ over the reference period.\n",
    "\n",
    "**Rule.** A week is **flagged** when the price has been outside the band, on the same side, for $n$ consecutive weeks including this one. Defaults: $k = 2$, $n = 2$. This is in the spirit of WFP's ALPS indicator (price gap from an estimated seasonal trend, standardised by the residual standard deviation), adapted to weekly data and to a two-sided rule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7a010240",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:29.080228Z",
     "iopub.status.busy": "2026-11-07T02:11:29.079909Z",
     "iopub.status.idle": "2026-11-07T02:11:29.103899Z",
     "shell.execute_reply": "2026-11-07T02:11:29.102931Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shock</th>\n",
       "      <th>start</th>\n",
       "      <th>kind</th>\n",
       "      <th>series</th>\n",
       "      <th>direction</th>\n",
       "      <th>detected</th>\n",
       "      <th>weeks_to_flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>2022-08-29</td>\n",
       "      <td>supply shortfall</td>\n",
       "      <td>onion_capital</td>\n",
       "      <td>high</td>\n",
       "      <td>True</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>2023-02-06</td>\n",
       "      <td>exchange-rate depreciation (persistent)</td>\n",
       "      <td>rice_parity</td>\n",
       "      <td>high</td>\n",
       "      <td>True</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>2023-08-07</td>\n",
       "      <td>world price spike</td>\n",
       "      <td>rice_parity</td>\n",
       "      <td>high</td>\n",
       "      <td>True</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S3</td>\n",
       "      <td>2023-08-07</td>\n",
       "      <td>world price spike</td>\n",
       "      <td>rice_capital</td>\n",
       "      <td>high</td>\n",
       "      <td>True</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S4</td>\n",
       "      <td>2024-08-12</td>\n",
       "      <td>road cut: transfer cost up</td>\n",
       "      <td>rice_valley</td>\n",
       "      <td>low</td>\n",
       "      <td>True</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S4</td>\n",
       "      <td>2024-08-12</td>\n",
       "      <td>road cut: transfer cost up</td>\n",
       "      <td>onion_valley</td>\n",
       "      <td>low</td>\n",
       "      <td>True</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>S5</td>\n",
       "      <td>2025-03-10</td>\n",
       "      <td>bumper harvest glut</td>\n",
       "      <td>onion_capital</td>\n",
       "      <td>low</td>\n",
       "      <td>True</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S6</td>\n",
       "      <td>2025-12-08</td>\n",
       "      <td>harvest glut, late paddy payments</td>\n",
       "      <td>rice_valley</td>\n",
       "      <td>low</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>S7</td>\n",
       "      <td>2026-09-14</td>\n",
       "      <td>storage losses, early stock-out</td>\n",
       "      <td>onion_capital</td>\n",
       "      <td>high</td>\n",
       "      <td>True</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  shock       start                                     kind         series  \\\n",
       "0    S1  2022-08-29                         supply shortfall  onion_capital   \n",
       "1    S2  2023-02-06  exchange-rate depreciation (persistent)    rice_parity   \n",
       "2    S3  2023-08-07                        world price spike    rice_parity   \n",
       "3    S3  2023-08-07                        world price spike   rice_capital   \n",
       "4    S4  2024-08-12               road cut: transfer cost up    rice_valley   \n",
       "5    S4  2024-08-12               road cut: transfer cost up   onion_valley   \n",
       "6    S5  2025-03-10                      bumper harvest glut  onion_capital   \n",
       "7    S6  2025-12-08        harvest glut, late paddy payments    rice_valley   \n",
       "8    S7  2026-09-14          storage losses, early stock-out  onion_capital   \n",
       "\n",
       "  direction  detected  weeks_to_flag  \n",
       "0      high      True            2.0  \n",
       "1      high      True            3.0  \n",
       "2      high      True            2.0  \n",
       "3      high      True            2.0  \n",
       "4       low      True            3.0  \n",
       "5       low      True            5.0  \n",
       "6       low      True            2.0  \n",
       "7       low     False            NaN  \n",
       "8      high      True            3.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab, det = evaluate_alerts(df, norms)\n",
    "tab.to_csv('alert_false_flags.csv', index=False); det.to_csv('alert_detection.csv', index=False)\n",
    "det"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bffa7886",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:29.106590Z",
     "iopub.status.busy": "2026-11-07T02:11:29.106395Z",
     "iopub.status.idle": "2026-11-07T02:11:29.117215Z",
     "shell.execute_reply": "2026-11-07T02:11:29.115733Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>flagged</th>\n",
       "      <th>flagged_outside_windows</th>\n",
       "      <th>weeks_outside_windows</th>\n",
       "      <th>false_flag_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>period</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>monitoring</th>\n",
       "      <td>42</td>\n",
       "      <td>18</td>\n",
       "      <td>366</td>\n",
       "      <td>0.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reference</th>\n",
       "      <td>185</td>\n",
       "      <td>29</td>\n",
       "      <td>1736</td>\n",
       "      <td>0.017</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            flagged  flagged_outside_windows  weeks_outside_windows  \\\n",
       "period                                                                \n",
       "monitoring       42                       18                    366   \n",
       "reference       185                       29                   1736   \n",
       "\n",
       "            false_flag_rate  \n",
       "period                       \n",
       "monitoring            0.049  \n",
       "reference             0.017  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab.groupby('period')[['flagged', 'flagged_outside_windows', 'weeks_outside_windows']].sum().assign(\n",
    "    false_flag_rate=lambda x: (x.flagged_outside_windows / x.weeks_outside_windows).round(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28b10b90",
   "metadata": {},
   "source": [
    "Trade-off between band width $k$ and persistence $n$: shocks detected (of nine shock–series pairs), median delay, and the share of weeks outside shock windows that are flagged."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8a17efa8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:29.119484Z",
     "iopub.status.busy": "2026-11-07T02:11:29.119228Z",
     "iopub.status.idle": "2026-11-07T02:11:29.900600Z",
     "shell.execute_reply": "2026-11-07T02:11:29.899614Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>k</th>\n",
       "      <th>n</th>\n",
       "      <th>detected</th>\n",
       "      <th>pairs</th>\n",
       "      <th>median_weeks_to_flag</th>\n",
       "      <th>false_flag_rate_reference</th>\n",
       "      <th>false_flag_rate_monitoring</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.107</td>\n",
       "      <td>0.270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.5</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.062</td>\n",
       "      <td>0.180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.5</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2.5</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2.5</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2.5</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     k  n  detected  pairs  median_weeks_to_flag  false_flag_rate_reference  \\\n",
       "0  1.5  1         8      9                   1.0                      0.107   \n",
       "1  1.5  2         8      9                   2.0                      0.062   \n",
       "2  1.5  3         7      9                   3.0                      0.040   \n",
       "3  2.0  1         8      9                   1.5                      0.040   \n",
       "4  2.0  2         8      9                   2.5                      0.017   \n",
       "5  2.0  3         7      9                   3.0                      0.012   \n",
       "6  2.5  1         8      9                   2.0                      0.009   \n",
       "7  2.5  2         8      9                   3.0                      0.003   \n",
       "8  2.5  3         7      9                   4.0                      0.002   \n",
       "\n",
       "   false_flag_rate_monitoring  \n",
       "0                       0.270  \n",
       "1                       0.180  \n",
       "2                       0.128  \n",
       "3                       0.107  \n",
       "4                       0.049  \n",
       "5                       0.025  \n",
       "6                       0.016  \n",
       "7                       0.005  \n",
       "8                       0.003  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rule_tradeoff(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c3adffb2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:29.902519Z",
     "iopub.status.busy": "2026-11-07T02:11:29.902265Z",
     "iopub.status.idle": "2026-11-07T02:11:30.336146Z",
     "shell.execute_reply": "2026-11-07T02:11:30.335558Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig_bands(df, norms, Path('.'))\n",
    "Image('price_bands.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0580f83",
   "metadata": {},
   "source": [
    "Reading the result. The rule flags eight of the nine shock–series pairs within two to five weeks. It misses the 10% fall in Valley market A rice in December 2025 at every setting tested, because that fall coincides with the wet-season harvest dip and is smaller than two robust standard deviations of a rice price that already swings with the season. After a long shock the moving baseline has partly absorbed the shock, so the return to normal can itself be flagged on the other side (rice import parity in late 2023). A bulletin should read flags together with the price path, not as isolated signals."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b91489bc",
   "metadata": {},
   "source": [
    "## 4. Spreads and marketing margins\n",
    "\n",
    "- **Spatial spread:** capital wholesale minus Valley market A (LCU/kg).\n",
    "- **Marketing margin:** $(P^{capital} - P^{farm,eq}) / P^{capital}$. For rice the farm-gate price is converted to milled-rice terms: $P^{farm,eq} = (P^{paddy} + c^{mill}) / 0.65$. For onion, $P^{farm,eq}$ is the farm-gate price.\n",
    "- **Local rice to import parity:** how far local milled rice at the capital sits below imported rice."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "081801c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:30.338672Z",
     "iopub.status.busy": "2026-11-07T02:11:30.338475Z",
     "iopub.status.idle": "2026-11-07T02:11:30.352645Z",
     "shell.execute_reply": "2026-11-07T02:11:30.351748Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rice_spread</th>\n",
       "      <th>onion_spread</th>\n",
       "      <th>rice_margin_share</th>\n",
       "      <th>onion_margin_share</th>\n",
       "      <th>rice_local_to_parity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>8.577</td>\n",
       "      <td>4.029</td>\n",
       "      <td>0.198</td>\n",
       "      <td>0.361</td>\n",
       "      <td>0.836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>7.802</td>\n",
       "      <td>5.282</td>\n",
       "      <td>0.151</td>\n",
       "      <td>0.399</td>\n",
       "      <td>0.824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>7.554</td>\n",
       "      <td>5.525</td>\n",
       "      <td>0.148</td>\n",
       "      <td>0.408</td>\n",
       "      <td>0.837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>8.421</td>\n",
       "      <td>6.016</td>\n",
       "      <td>0.149</td>\n",
       "      <td>0.422</td>\n",
       "      <td>0.791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>9.648</td>\n",
       "      <td>6.771</td>\n",
       "      <td>0.166</td>\n",
       "      <td>0.424</td>\n",
       "      <td>0.805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025</th>\n",
       "      <td>9.113</td>\n",
       "      <td>6.519</td>\n",
       "      <td>0.158</td>\n",
       "      <td>0.418</td>\n",
       "      <td>0.813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2026</th>\n",
       "      <td>9.947</td>\n",
       "      <td>6.509</td>\n",
       "      <td>0.149</td>\n",
       "      <td>0.399</td>\n",
       "      <td>0.791</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      rice_spread  onion_spread  rice_margin_share  onion_margin_share  \\\n",
       "year                                                                     \n",
       "2020        8.577         4.029              0.198               0.361   \n",
       "2021        7.802         5.282              0.151               0.399   \n",
       "2022        7.554         5.525              0.148               0.408   \n",
       "2023        8.421         6.016              0.149               0.422   \n",
       "2024        9.648         6.771              0.166               0.424   \n",
       "2025        9.113         6.519              0.158               0.418   \n",
       "2026        9.947         6.509              0.149               0.399   \n",
       "\n",
       "      rice_local_to_parity  \n",
       "year                        \n",
       "2020                 0.836  \n",
       "2021                 0.824  \n",
       "2022                 0.837  \n",
       "2023                 0.791  \n",
       "2024                 0.805  \n",
       "2025                 0.813  \n",
       "2026                 0.791  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm_ = spreads_margins(df)\n",
    "sm_['year'] = pd.to_datetime(sm_['date']).dt.year\n",
    "sm_.groupby('year')[['rice_spread', 'onion_spread', 'rice_margin_share', 'onion_margin_share', 'rice_local_to_parity']].mean().round(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac00a367",
   "metadata": {},
   "source": [
    "## 5. Price transmission: Valley market A and the capital\n",
    "\n",
    "Engle–Granger two-step estimation on the reference period, in levels, as in the FAO review by Rapsomanikis, Hallam and Conforti (2003): a long-run regression $v_t = b_0 + b_1 c_t + e_t$, then an error-correction model $\\Delta v_t = a_0 + \\alpha e_{t-1} + \\gamma \\Delta c_t + \\delta \\Delta v_{t-1} + u_t$ with HAC standard errors. A second specification adds two Fourier pairs (period 52) to the long-run regression. The generator's true values are shown for comparison."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f18c56c9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:30.354467Z",
     "iopub.status.busy": "2026-11-07T02:11:30.354298Z",
     "iopub.status.idle": "2026-11-07T02:11:30.725013Z",
     "shell.execute_reply": "2026-11-07T02:11:30.723703Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crop</th>\n",
       "      <th>spec</th>\n",
       "      <th>adf_p_valley</th>\n",
       "      <th>adf_p_capital</th>\n",
       "      <th>eg_t</th>\n",
       "      <th>eg_p</th>\n",
       "      <th>b1</th>\n",
       "      <th>alpha</th>\n",
       "      <th>alpha_se</th>\n",
       "      <th>true_alpha</th>\n",
       "      <th>half_life_weeks</th>\n",
       "      <th>gamma</th>\n",
       "      <th>true_gamma</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>rice</td>\n",
       "      <td>plain</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.270</td>\n",
       "      <td>-5.098</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.857</td>\n",
       "      <td>-0.155</td>\n",
       "      <td>0.035</td>\n",
       "      <td>-0.25</td>\n",
       "      <td>4.102</td>\n",
       "      <td>0.309</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>rice</td>\n",
       "      <td>with seasonal terms</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.270</td>\n",
       "      <td>-5.098</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.807</td>\n",
       "      <td>-0.178</td>\n",
       "      <td>0.043</td>\n",
       "      <td>-0.25</td>\n",
       "      <td>3.547</td>\n",
       "      <td>0.326</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>onion</td>\n",
       "      <td>plain</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-4.917</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.954</td>\n",
       "      <td>-0.152</td>\n",
       "      <td>0.037</td>\n",
       "      <td>-0.35</td>\n",
       "      <td>4.191</td>\n",
       "      <td>0.436</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>onion</td>\n",
       "      <td>with seasonal terms</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-4.917</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.724</td>\n",
       "      <td>-0.206</td>\n",
       "      <td>0.047</td>\n",
       "      <td>-0.35</td>\n",
       "      <td>2.999</td>\n",
       "      <td>0.435</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    crop                 spec  adf_p_valley  adf_p_capital   eg_t  eg_p  \\\n",
       "0   rice                plain         0.008          0.270 -5.098   0.0   \n",
       "1   rice  with seasonal terms         0.008          0.270 -5.098   0.0   \n",
       "2  onion                plain         0.000          0.004 -4.917   0.0   \n",
       "3  onion  with seasonal terms         0.000          0.004 -4.917   0.0   \n",
       "\n",
       "      b1  alpha  alpha_se  true_alpha  half_life_weeks  gamma  true_gamma  \n",
       "0  0.857 -0.155     0.035       -0.25            4.102  0.309         0.3  \n",
       "1  0.807 -0.178     0.043       -0.25            3.547  0.326         0.3  \n",
       "2  0.954 -0.152     0.037       -0.35            4.191  0.436         0.4  \n",
       "3  0.724 -0.206     0.047       -0.35            2.999  0.435         0.4  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr = pd.DataFrame([transmission(df, c, s) for c in ('rice', 'onion') for s in (False, True)])\n",
    "tr.round(4).to_csv('price_transmission.csv', index=False)\n",
    "tr[['crop', 'spec', 'adf_p_valley', 'adf_p_capital', 'eg_t', 'eg_p', 'b1', 'alpha', 'alpha_se', 'true_alpha', 'half_life_weeks', 'gamma', 'true_gamma']].round(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0a13352",
   "metadata": {},
   "source": [
    "Reading the result. The test points the right way: valley and capital prices are cointegrated, valley prices close part of any gap every week, and about a third (rice) or 40% (onion) of a capital price change reaches the valley in the same week. But the linear model **underestimates the speed of adjustment** even on data generated by an error-correction process (−0.16 against −0.25 for rice, −0.15 against −0.35 for onion). The reason is that transfer costs rise at harvest, and a road cut raised them for eight weeks. Those movements stay in the error term. Adding seasonal terms helps a little. The unit-root tests also disagree (several series look trend-stationary over five years of weekly data). On real data these issues are usually worse, and the estimate should be read as an order of magnitude, with threshold models as the next step when transfer costs are large."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "198089da",
   "metadata": {},
   "source": [
    "## 6. Storage decision: does holding stock pay?\n",
    "\n",
    "For one tonne bought (or kept back) in month $b$ and sold in month $s$, $m$ months later, at seasonal-norm prices:\n",
    "\n",
    "$$\n",
    "\\text{net} = 1000\\,P_s e^{g m} (1-\\ell)^m - 1000\\,P_b (1 + r\\,m) - f\\,m\n",
    "$$\n",
    "\n",
    "with $P$ the monthly seasonal norm at the current price level (LCU/kg), $g$ the monthly drift of the deseasonalised level, $\\ell$ the weight loss per month, $r$ the monthly financing cost (simple interest on the purchase value) and $f$ the storage fee per tonne per month. Defaults (illustrative): paddy $\\ell$ = 0.5%, onion $\\ell$ = 5% (traditional store); $r$ = 1.5% a month for both; fees 250 and 400 LCU/t/month."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "accddf99",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:30.727613Z",
     "iopub.status.busy": "2026-11-07T02:11:30.727334Z",
     "iopub.status.idle": "2026-11-07T02:11:30.754426Z",
     "shell.execute_reply": "2026-11-07T02:11:30.753005Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rice_farmgate monthly norm (Jan..Dec): [30.27 31.67 33.3  34.56 35.11 34.94 34.35 35.44 35.39 36.11 34.19 29.81] drift/week: 0.000853\n",
      "Storage(buy_month=12, sell_month=8, loss=0.005, finance=0.015, fee=250.0)\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sell_month</th>\n",
       "      <th>months</th>\n",
       "      <th>p_buy</th>\n",
       "      <th>p_sell</th>\n",
       "      <th>sold</th>\n",
       "      <th>finance</th>\n",
       "      <th>fees</th>\n",
       "      <th>net</th>\n",
       "      <th>return_on_stock</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>29.81</td>\n",
       "      <td>30.382</td>\n",
       "      <td>0.995</td>\n",
       "      <td>447.15</td>\n",
       "      <td>250.0</td>\n",
       "      <td>-276.965</td>\n",
       "      <td>-0.009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>29.81</td>\n",
       "      <td>31.905</td>\n",
       "      <td>0.990</td>\n",
       "      <td>894.30</td>\n",
       "      <td>500.0</td>\n",
       "      <td>382.441</td>\n",
       "      <td>0.013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>29.81</td>\n",
       "      <td>33.671</td>\n",
       "      <td>0.985</td>\n",
       "      <td>1341.45</td>\n",
       "      <td>750.0</td>\n",
       "      <td>1267.320</td>\n",
       "      <td>0.043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>29.81</td>\n",
       "      <td>35.075</td>\n",
       "      <td>0.980</td>\n",
       "      <td>1788.60</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1779.925</td>\n",
       "      <td>0.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>29.81</td>\n",
       "      <td>35.765</td>\n",
       "      <td>0.975</td>\n",
       "      <td>2235.75</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>1583.948</td>\n",
       "      <td>0.053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>29.81</td>\n",
       "      <td>35.724</td>\n",
       "      <td>0.970</td>\n",
       "      <td>2682.90</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>672.257</td>\n",
       "      <td>0.023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>29.81</td>\n",
       "      <td>35.250</td>\n",
       "      <td>0.966</td>\n",
       "      <td>3130.05</td>\n",
       "      <td>1750.0</td>\n",
       "      <td>-655.079</td>\n",
       "      <td>-0.022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>29.81</td>\n",
       "      <td>36.504</td>\n",
       "      <td>0.961</td>\n",
       "      <td>3577.20</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>-318.414</td>\n",
       "      <td>-0.011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>29.81</td>\n",
       "      <td>36.587</td>\n",
       "      <td>0.956</td>\n",
       "      <td>4024.35</td>\n",
       "      <td>2250.0</td>\n",
       "      <td>-1111.102</td>\n",
       "      <td>-0.037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>29.81</td>\n",
       "      <td>37.470</td>\n",
       "      <td>0.951</td>\n",
       "      <td>4471.50</td>\n",
       "      <td>2500.0</td>\n",
       "      <td>-1143.669</td>\n",
       "      <td>-0.038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>29.81</td>\n",
       "      <td>35.609</td>\n",
       "      <td>0.946</td>\n",
       "      <td>4918.65</td>\n",
       "      <td>2750.0</td>\n",
       "      <td>-3780.097</td>\n",
       "      <td>-0.127</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sell_month  months  p_buy  p_sell   sold  finance    fees       net  \\\n",
       "0            1       1  29.81  30.382  0.995   447.15   250.0  -276.965   \n",
       "1            2       2  29.81  31.905  0.990   894.30   500.0   382.441   \n",
       "2            3       3  29.81  33.671  0.985  1341.45   750.0  1267.320   \n",
       "3            4       4  29.81  35.075  0.980  1788.60  1000.0  1779.925   \n",
       "4            5       5  29.81  35.765  0.975  2235.75  1250.0  1583.948   \n",
       "5            6       6  29.81  35.724  0.970  2682.90  1500.0   672.257   \n",
       "6            7       7  29.81  35.250  0.966  3130.05  1750.0  -655.079   \n",
       "7            8       8  29.81  36.504  0.961  3577.20  2000.0  -318.414   \n",
       "8            9       9  29.81  36.587  0.956  4024.35  2250.0 -1111.102   \n",
       "9           10      10  29.81  37.470  0.951  4471.50  2500.0 -1143.669   \n",
       "10          11      11  29.81  35.609  0.946  4918.65  2750.0 -3780.097   \n",
       "\n",
       "    return_on_stock  \n",
       "0            -0.009  \n",
       "1             0.013  \n",
       "2             0.043  \n",
       "3             0.060  \n",
       "4             0.053  \n",
       "5             0.023  \n",
       "6            -0.022  \n",
       "7            -0.011  \n",
       "8            -0.037  \n",
       "9            -0.038  \n",
       "10           -0.127  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "onion_farmgate monthly norm (Jan..Dec): [27.45 27.41 20.96 15.08 15.93 17.47 20.   22.39 24.53 24.82 27.02 26.88] drift/week: 0.001131\n",
      "Storage(buy_month=4, sell_month=9, loss=0.05, finance=0.015, fee=400.0)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sell_month</th>\n",
       "      <th>months</th>\n",
       "      <th>p_buy</th>\n",
       "      <th>p_sell</th>\n",
       "      <th>sold</th>\n",
       "      <th>finance</th>\n",
       "      <th>fees</th>\n",
       "      <th>net</th>\n",
       "      <th>return_on_stock</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>15.08</td>\n",
       "      <td>16.008</td>\n",
       "      <td>0.950</td>\n",
       "      <td>226.2</td>\n",
       "      <td>400.0</td>\n",
       "      <td>-498.349</td>\n",
       "      <td>-0.033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>15.08</td>\n",
       "      <td>17.642</td>\n",
       "      <td>0.902</td>\n",
       "      <td>452.4</td>\n",
       "      <td>800.0</td>\n",
       "      <td>-410.420</td>\n",
       "      <td>-0.027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>15.08</td>\n",
       "      <td>20.296</td>\n",
       "      <td>0.857</td>\n",
       "      <td>678.6</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>442.882</td>\n",
       "      <td>0.029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>15.08</td>\n",
       "      <td>22.833</td>\n",
       "      <td>0.815</td>\n",
       "      <td>904.8</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>1013.036</td>\n",
       "      <td>0.067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>15.08</td>\n",
       "      <td>25.139</td>\n",
       "      <td>0.774</td>\n",
       "      <td>1131.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1240.718</td>\n",
       "      <td>0.082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>15.08</td>\n",
       "      <td>25.561</td>\n",
       "      <td>0.735</td>\n",
       "      <td>1357.2</td>\n",
       "      <td>2400.0</td>\n",
       "      <td>-47.741</td>\n",
       "      <td>-0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>15.08</td>\n",
       "      <td>27.963</td>\n",
       "      <td>0.698</td>\n",
       "      <td>1583.4</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>64.247</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>15.08</td>\n",
       "      <td>27.955</td>\n",
       "      <td>0.663</td>\n",
       "      <td>1809.6</td>\n",
       "      <td>3200.0</td>\n",
       "      <td>-1543.785</td>\n",
       "      <td>-0.102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>15.08</td>\n",
       "      <td>28.688</td>\n",
       "      <td>0.630</td>\n",
       "      <td>2035.8</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>-2635.273</td>\n",
       "      <td>-0.175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>15.08</td>\n",
       "      <td>28.787</td>\n",
       "      <td>0.599</td>\n",
       "      <td>2262.0</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>-4106.263</td>\n",
       "      <td>-0.272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "      <td>15.08</td>\n",
       "      <td>22.121</td>\n",
       "      <td>0.569</td>\n",
       "      <td>2488.2</td>\n",
       "      <td>4400.0</td>\n",
       "      <td>-9385.780</td>\n",
       "      <td>-0.622</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sell_month  months  p_buy  p_sell   sold  finance    fees       net  \\\n",
       "0            5       1  15.08  16.008  0.950    226.2   400.0  -498.349   \n",
       "1            6       2  15.08  17.642  0.902    452.4   800.0  -410.420   \n",
       "2            7       3  15.08  20.296  0.857    678.6  1200.0   442.882   \n",
       "3            8       4  15.08  22.833  0.815    904.8  1600.0  1013.036   \n",
       "4            9       5  15.08  25.139  0.774   1131.0  2000.0  1240.718   \n",
       "5           10       6  15.08  25.561  0.735   1357.2  2400.0   -47.741   \n",
       "6           11       7  15.08  27.963  0.698   1583.4  2800.0    64.247   \n",
       "7           12       8  15.08  27.955  0.663   1809.6  3200.0 -1543.785   \n",
       "8            1       9  15.08  28.688  0.630   2035.8  3600.0 -2635.273   \n",
       "9            2      10  15.08  28.787  0.599   2262.0  4000.0 -4106.263   \n",
       "10           3      11  15.08  22.121  0.569   2488.2  4400.0 -9385.780   \n",
       "\n",
       "    return_on_stock  \n",
       "0            -0.033  \n",
       "1            -0.027  \n",
       "2             0.029  \n",
       "3             0.067  \n",
       "4             0.082  \n",
       "5            -0.003  \n",
       "6             0.004  \n",
       "7            -0.102  \n",
       "8            -0.175  \n",
       "9            -0.272  \n",
       "10           -0.622  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for crop in ('rice', 'onion'):\n",
    "    k = f'{crop}_farmgate'\n",
    "    print(k, 'monthly norm (Jan..Dec):', norms[k]['monthly_norm'], 'drift/week:', norms[k]['drift_week'])\n",
    "    s = STORAGE_DEFAULTS[crop]\n",
    "    print(s)\n",
    "    display(storage_curve(norms[k]['monthly_norm'], norms[k]['drift_week'], s)[['sell_month', 'months', 'p_buy', 'p_sell', 'sold', 'finance', 'fees', 'net', 'return_on_stock']].round(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6b99c47",
   "metadata": {},
   "source": [
    "Sensitivity of the default onion plan (April to September) to the storage loss rate, and of the default paddy plan (December to August) to the financing cost."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "104587b0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:30.756397Z",
     "iopub.status.busy": "2026-11-07T02:11:30.756191Z",
     "iopub.status.idle": "2026-11-07T02:11:30.766389Z",
     "shell.execute_reply": "2026-11-07T02:11:30.765153Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   loss     net\n",
      "0  0.00  6928.0\n",
      "1  0.02  4512.0\n",
      "2  0.03  3376.0\n",
      "3  0.05  1241.0\n",
      "4  0.08 -1643.0\n",
      "   finance     net\n",
      "0    0.000  3259.0\n",
      "1    0.005  2066.0\n",
      "2    0.010   874.0\n",
      "3    0.015  -318.0\n",
      "4    0.020 -1511.0\n"
     ]
    }
   ],
   "source": [
    "k = 'onion_farmgate'; s = STORAGE_DEFAULTS['onion']\n",
    "print(pd.DataFrame([dict(loss=L, net=storage_margin(norms[k]['monthly_norm'], norms[k]['drift_week'], Storage(s.buy_month, s.sell_month, L, s.finance, s.fee))['net']) for L in (0.0, 0.02, 0.03, 0.05, 0.08)]).round({'net': 0}))\n",
    "k = 'rice_farmgate'; s = STORAGE_DEFAULTS['rice']\n",
    "print(pd.DataFrame([dict(finance=r, net=storage_margin(norms[k]['monthly_norm'], norms[k]['drift_week'], Storage(s.buy_month, s.sell_month, s.loss, r, s.fee))['net']) for r in (0.0, 0.005, 0.01, 0.015, 0.02)]).round({'net': 0}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5e23c532",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:30.768545Z",
     "iopub.status.busy": "2026-11-07T02:11:30.768365Z",
     "iopub.status.idle": "2026-11-07T02:11:30.958228Z",
     "shell.execute_reply": "2026-11-07T02:11:30.957190Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig_storage(norms, Path('.'))\n",
    "Image('storage_margin.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4c1b289",
   "metadata": {},
   "source": [
    "## 7. Short-horizon forecasts, backtested\n",
    "\n",
    "Three models on log prices: **seasonal naive** (same week last year), **SARIMA(1,0,0)(0,1,0)[52] with drift**, and **STL + ETS** (robust STL, then an additive damped-trend exponential-smoothing model on the seasonally adjusted series), following Hyndman and Athanasopoulos, *Forecasting: Principles and Practice*. Rolling-origin backtest over the monitoring year: 11 origins (weeks 259, 263, …, 299), horizons 1–12 weeks, errors on the price level, and the share of outcomes that fall inside the 80% prediction interval. This cell takes about a minute and a half."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "da029b71",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:11:30.960681Z",
     "iopub.status.busy": "2026-11-07T02:11:30.960458Z",
     "iopub.status.idle": "2026-11-07T02:12:48.926518Z",
     "shell.execute_reply": "2026-11-07T02:12:48.925405Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>hgroup</th>\n",
       "      <th>h1_4</th>\n",
       "      <th>h5_12</th>\n",
       "      <th>mape_all</th>\n",
       "      <th>cover80</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sarima</th>\n",
       "      <td>4.4</td>\n",
       "      <td>8.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>76.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seasonal_naive</th>\n",
       "      <td>11.8</td>\n",
       "      <td>12.7</td>\n",
       "      <td>12.5</td>\n",
       "      <td>45.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stl_ets</th>\n",
       "      <td>6.1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>55.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "hgroup          h1_4  h5_12  mape_all  cover80\n",
       "model                                         \n",
       "sarima           4.4    8.5       7.1     76.8\n",
       "seasonal_naive  11.8   12.7      12.5     45.8\n",
       "stl_ets          6.1    8.0       7.4     55.1"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt = backtest(df)\n",
    "bs = backtest_summary(bt)\n",
    "bs.to_csv('forecast_backtest.csv', index=False)\n",
    "bs.groupby('model')[['h1_4', 'h5_12', 'mape_all', 'cover80']].mean().round(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "28f02c5f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:12:48.928374Z",
     "iopub.status.busy": "2026-11-07T02:12:48.928189Z",
     "iopub.status.idle": "2026-11-07T02:12:48.938022Z",
     "shell.execute_reply": "2026-11-07T02:12:48.937048Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>model</th>\n",
       "      <th>sarima</th>\n",
       "      <th>seasonal_naive</th>\n",
       "      <th>stl_ets</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>onion_capital</th>\n",
       "      <td>10.8</td>\n",
       "      <td>14.9</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_farmgate</th>\n",
       "      <td>13.7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_regional</th>\n",
       "      <td>11.8</td>\n",
       "      <td>16.5</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onion_valley</th>\n",
       "      <td>13.2</td>\n",
       "      <td>17.9</td>\n",
       "      <td>10.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_capital</th>\n",
       "      <td>2.4</td>\n",
       "      <td>8.3</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_farmgate</th>\n",
       "      <td>4.1</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_parity</th>\n",
       "      <td>2.7</td>\n",
       "      <td>11.1</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_regional</th>\n",
       "      <td>2.5</td>\n",
       "      <td>7.9</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rice_valley</th>\n",
       "      <td>2.9</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "model           sarima  seasonal_naive  stl_ets\n",
       "series                                         \n",
       "onion_capital     10.8            14.9      8.2\n",
       "onion_farmgate    13.7            18.2     11.8\n",
       "onion_regional    11.8            16.5     10.0\n",
       "onion_valley      13.2            17.9     10.2\n",
       "rice_capital       2.4             8.3      4.4\n",
       "rice_farmgate      4.1             9.4      5.8\n",
       "rice_parity        2.7            11.1      6.7\n",
       "rice_regional      2.5             7.9      4.7\n",
       "rice_valley        2.9             8.0      4.5"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bs.pivot(index='series', columns='model', values='mape_all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "85fd7750",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:12:48.939591Z",
     "iopub.status.busy": "2026-11-07T02:12:48.939410Z",
     "iopub.status.idle": "2026-11-07T02:12:48.951539Z",
     "shell.execute_reply": "2026-11-07T02:12:48.950361Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hgroup</th>\n",
       "      <th>h1_4</th>\n",
       "      <th>h5_12</th>\n",
       "      <th>mape_all</th>\n",
       "      <th>cover80</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>crop</th>\n",
       "      <th>model</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">onion</th>\n",
       "      <th>sarima</th>\n",
       "      <td>7.4</td>\n",
       "      <td>14.9</td>\n",
       "      <td>12.4</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seasonal_naive</th>\n",
       "      <td>16.2</td>\n",
       "      <td>17.2</td>\n",
       "      <td>16.9</td>\n",
       "      <td>44.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stl_ets</th>\n",
       "      <td>8.3</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>68.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">rice</th>\n",
       "      <th>sarima</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>90.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seasonal_naive</th>\n",
       "      <td>8.4</td>\n",
       "      <td>9.2</td>\n",
       "      <td>8.9</td>\n",
       "      <td>46.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stl_ets</th>\n",
       "      <td>4.4</td>\n",
       "      <td>5.6</td>\n",
       "      <td>5.2</td>\n",
       "      <td>44.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "hgroup                h1_4  h5_12  mape_all  cover80\n",
       "crop  model                                         \n",
       "onion sarima           7.4   14.9      12.4     60.0\n",
       "      seasonal_naive  16.2   17.2      16.9     44.5\n",
       "      stl_ets          8.3   11.0      10.0     68.2\n",
       "rice  sarima           2.0    3.4       2.9     90.1\n",
       "      seasonal_naive   8.4    9.2       8.9     46.8\n",
       "      stl_ets          4.4    5.6       5.2     44.7"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bs.assign(crop=bs['series'].str.split('_').str[0]).groupby(['crop', 'model'])[['h1_4', 'h5_12', 'mape_all', 'cover80']].mean().round(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b20879bb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:12:48.953711Z",
     "iopub.status.busy": "2026-11-07T02:12:48.953474Z",
     "iopub.status.idle": "2026-11-07T02:12:52.233270Z",
     "shell.execute_reply": "2026-11-07T02:12:52.232142Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model with the lowest backtest MAPE, by crop: {'onion': 'stl_ets', 'rice': 'sarima'}\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = best_models(bs)\n",
    "print('model with the lowest backtest MAPE, by crop:', model)\n",
    "fc = forecast(df, model)\n",
    "fig_forecast(df, fc, Path('.'))\n",
    "Image('forecast_bands.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f63dc8e",
   "metadata": {},
   "source": [
    "Reading the result. No single model wins. For rice, SARIMA is clearly best (mean absolute percentage error of 2.0% at 1–4 weeks and 3.4% at 5–12 weeks), and its 80% intervals are too wide rather than too narrow (90% coverage): the seasonal difference carries last year's week-to-week noise into this year's forecast. For onion, SARIMA is slightly better at 1–4 weeks (7.4% against 8.3%), but STL + ETS is better at 5–12 weeks (11.0% against 14.9%) and overall, and its intervals are closer to nominal, though still too narrow (68% coverage), partly because the September 2026 shock has no precedent in the history. Seasonal naive is the benchmark to beat and is beaten everywhere. The system therefore uses SARIMA for rice and STL + ETS for onion, and the bulletin shows bands, not points: for onion, even the 80% band misses about one week in three."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e94ce4e3",
   "metadata": {},
   "source": [
    "## 8. Headline numbers (the same numbers the website demo shows with default settings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7d6d7fd8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-07T02:12:52.235413Z",
     "iopub.status.busy": "2026-11-07T02:12:52.235230Z",
     "iopub.status.idle": "2026-11-07T02:12:52.247077Z",
     "shell.execute_reply": "2026-11-07T02:12:52.245775Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      " \"last_date\": \"2026-11-02\",\n",
      " \"rice_farmgate\": {\n",
      "  \"latest\": 37.01,\n",
      "  \"norm\": 37.69830771788511,\n",
      "  \"dev\": -0.018258318729743817,\n",
      "  \"flagged_monitoring\": 3,\n",
      "  \"flag_now\": 0,\n",
      "  \"fc4\": [\n",
      "   32.18,\n",
      "   30.25,\n",
      "   34.23\n",
      "  ]\n",
      " },\n",
      " \"rice_valley\": {\n",
      "  \"latest\": 62.83,\n",
      "  \"norm\": 62.232898672039404,\n",
      "  \"dev\": 0.009594625040804328,\n",
      "  \"flagged_monitoring\": 1,\n",
      "  \"flag_now\": 0,\n",
      "  \"fc4\": [\n",
      "   57.72,\n",
      "   55.11,\n",
      "   60.45\n",
      "  ]\n",
      " },\n",
      " \"rice_regional\": {\n",
      "  \"latest\": 66.65,\n",
      "  \"norm\": 67.03423238051784,\n",
      "  \"dev\": -0.005731883052478959,\n",
      "  \"flagged_monitoring\": 0,\n",
      "  \"flag_now\": 0,\n",
      "  \"fc4\": [\n",
      "   61.88,\n",
      "   58.83,\n",
      "   65.09\n",
      "  ]\n",
      " },\n",
      " \"rice_capital\": {\n",
      "  \"latest\": 70.22,\n",
      "  \"norm\": 69.79404774747583,\n",
      "  \"dev\": 0.006102988238557483,\n",
      "  \"flagged_monitoring\": 5,\n",
      "  \"flag_now\": 0,\n",
      "  \"fc4\": [\n",
      "   66.41,\n",
      "   63.24,\n",
      "   69.75\n",
      "  ]\n",
      " },\n",
      " \"rice_parity\": {\n",
      "  \"latest\": 85.97,\n",
      "  \"norm\": 87.38250914258255,\n",
      "  \"dev\": -0.0161646667787686,\n",
      "  \"flagged_monitoring\": 2,\n",
      "  \"flag_now\": 0,\n",
      "  \"fc4\": [\n",
      "   83.68,\n",
      "   78.93,\n",
      "   88.71\n",
      "  ]\n",
      " },\n",
      " \"onion_farmgate\": {\n",
      "  \"latest\": 28.58,\n",
      "  \"norm\": 22.932338350606837,\n",
      "  \"dev\": 0.2462750009635939,\n",
      "  \"flagged_monitoring\": 7,\n",
      "  \"flag_now\": 1,\n",
      "  \"fc4\": [\n",
      "   31.22,\n",
      "   27.95,\n",
      "   34.87\n",
      "  ]\n",
      " },\n",
      " \"onion_valley\": {\n",
      "  \"latest\": 36.59,\n",
      "  \"norm\": 30.134665260871564,\n",
      "  \"dev\": 0.2142162417682596,\n",
      "  \"flagged_monitoring\": 7,\n",
      "  \"flag_now\": 1,\n",
      "  \"fc4\": [\n",
      "   35.57,\n",
      "   32.33,\n",
      "   39.12\n",
      "  ]\n",
      " },\n",
      " \"onion_regional\": {\n",
      "  \"latest\": 38.95,\n",
      "  \"norm\": 33.43947927724984,\n",
      "  \"dev\": 0.16479086522436326,\n",
      "  \"flagged_monitoring\": 11,\n",
      "  \"flag_now\": 1,\n",
      "  \"fc4\": [\n",
      "   39.43,\n",
      "   36.13,\n",
      "   43.02\n",
      "  ]\n",
      " },\n",
      " \"onion_capital\": {\n",
      "  \"latest\": 39.7,\n",
      "  \"norm\": 35.94298454427447,\n",
      "  \"dev\": 0.10452708653333032,\n",
      "  \"flagged_monitoring\": 6,\n",
      "  \"flag_now\": 0,\n",
      "  \"fc4\": [\n",
      "   40.91,\n",
      "   37.48,\n",
      "   44.65\n",
      "  ]\n",
      " },\n",
      " \"rice_spread\": {\n",
      "  \"latest\": 7.39,\n",
      "  \"share\": 0.10524067217317003,\n",
      "  \"norm\": 7.138000000000001\n",
      " },\n",
      " \"rice_margin\": {\n",
      "  \"latest\": 0.106,\n",
      "  \"norm\": 0.11932000000000001\n",
      " },\n",
      " \"rice_storage\": {\n",
      "  \"net\": -318.4136232352421,\n",
      "  \"ret\": -0.010681436539256696,\n",
      "  \"months\": 8,\n",
      "  \"p_buy\": 29.81,\n",
      "  \"p_sell\": 36.503633092052304,\n",
      "  \"break_even_month\": 2,\n",
      "  \"best_month\": 4,\n",
      "  \"best_net\": 1779.9254741196041,\n",
      "  \"paying_months\": [\n",
      "   2,\n",
      "   3,\n",
      "   4,\n",
      "   5,\n",
      "   6\n",
      "  ],\n",
      "  \"break_even_finance\": 0.013664820432592912,\n",
      "  \"break_even_loss\": 0.0038751745033322456\n",
      " },\n",
      " \"onion_spread\": {\n",
      "  \"latest\": 3.11,\n",
      "  \"share\": 0.07833753148614608,\n",
      "  \"norm\": 5.274\n",
      " },\n",
      " \"onion_margin\": {\n",
      "  \"latest\": 0.2801,\n",
      "  \"norm\": 0.3613799999999999\n",
      " },\n",
      " \"onion_storage\": {\n",
      "  \"net\": 1240.717827271219,\n",
      "  \"ret\": 0.08227571798880763,\n",
      "  \"months\": 5,\n",
      "  \"p_buy\": 15.08,\n",
      "  \"p_sell\": 25.138533252211612,\n",
      "  \"break_even_month\": 7,\n",
      "  \"best_month\": 9,\n",
      "  \"best_net\": 1240.717827271219,\n",
      "  \"paying_months\": [\n",
      "   7,\n",
      "   8,\n",
      "   9,\n",
      "   11\n",
      "  ],\n",
      "  \"break_even_finance\": 0.031455143597761526,\n",
      "  \"break_even_loss\": 0.06244064414649458\n",
      " },\n",
      " \"forecast_model\": {\n",
      "  \"onion\": \"stl_ets\",\n",
      "  \"rice\": \"sarima\"\n",
      " }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "hl = headline(df, norms, fc=fc); hl['forecast_model'] = model\n",
    "import json\n",
    "Path('headline_numbers.json').write_text(json.dumps(hl, indent=1, default=float))\n",
    "print(json.dumps(hl, indent=1, default=float))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ff903fb",
   "metadata": {},
   "source": [
    "## Limits\n",
    "\n",
    "- Synthetic data generated by a model that this notebook then analyses. Recovering the generator's structure tests the code and the method, not any real market.\n",
    "- The seasonal index is fixed over five years; real harvest calendars move with rainfall, river flood and irrigation schedules.\n",
    "- The band calibrates on its own reference period; with real data it should be recalibrated every year and checked against field reports.\n",
    "- The transmission model is linear and symmetric. Real valley–capital links often have thresholds (no trade when the gap is below transfer costs) and asymmetric responses.\n",
    "- The storage calculator uses seasonal-norm prices, not a forecast of this year's prices, and assumes the buyer can sell the whole stock in the chosen month.\n",
    "- Nothing here uses or reproduces FAO GIEWS FPMA or WFP data; those sources are named on the website page as inputs for a real system."
   ]
  }
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