MAE is the average absolute price error in rupees per quintal.

WAPE relates total absolute error to the total observed price scale.

Historical interval coverage describes past tests, not a promise for the next seven days.

Validated recent-level + lead-aware blendReliability context
₹522MAE
10.5%WAPE
2Levaluation examples
70.6%Expected range
80%Reliability context

MAE is the average absolute price error in rupees per quintal.

Forecast reliability is measured on later dates.

MethodMAEWAPEsMAPEn
Validated recent-level + lead-aware blendSelected₹4749.7%12.6%5,24,969
Five-report moving average₹48610%12.9%5,24,969
Last observation₹49610.2%13.1%5,24,969
Global histogram gradient boosting₹51210.5%13.1%5,24,969
Seven-day seasonal naive₹59012.1%15.6%5,24,969

Historical interval coverage describes past tests, not a promise for the next seven days. Information only — not trading or financial advice.

Technical report

Detailed notes, interpretation, and operational boundaries

This section documents what the published evidence means, how it was produced, and where the interface deliberately avoids making a stronger claim than the data supports.

01

How the production method is selected

Candidate methods are compared on chronological folds. A later time holdout is reported separately and is not an input to the automated selector.

  • Validated recent-level + lead-aware blend is the current production point method. The best lead-aware candidate improved pooled selection MAE by 2.6%; the gate requires 1%.
  • The candidate won 3 of 3 usable selection folds; the configured stability gate requires 66.6%.
  • Lag, rolling, calendar, market, crop, freshness, arrival-coverage, and volatility features are computed only from information available at each forecast origin.
02

How the seven-day point path is produced

The production blend keeps 70% of the stable five-report moving average, adds 30% of a lead-aware tree estimate, and applies a 7.5% damped recent-level adjustment per lead day.

  • The automated search selected the tree and level-drift weights from 90 parameter pairs using only chronological selection folds; holdout values are computed afterward.
  • Lead day, target weekday, target week, target month, recent momentum, volatility, arrivals, and market context can now change the central estimate from one target date to the next.
  • No cosmetic noise is added. A few genuinely stable series may still round to the same rupee on adjacent days, while their uncertainty ranges remain separately calibrated by horizon.
03

Locked holdout performance

The final holdout runs from 2026-05-29 to 2026-07-27 and contains 1,95,335 forecast examples.

  • Mean absolute error is ₹522 per quintal and WAPE is 10.5%.
  • Directional accuracy is 48.7%; this is contextual evidence, not a guarantee for a particular market or date.
  • Aggregate metrics can hide weak commodities or markets, so the published evaluation retains segmented horizon, commodity, state, market, and coverage results.
04

Uncertainty and safe interpretation

Intervals are asymmetric residual ranges calibrated on earlier out-of-time errors with hierarchical fallback when a narrow segment has too few examples.

  • The nominal interval target is 80%; empirical locked-holdout coverage is 70.6%.
  • Coverage below the nominal target is visible because hiding it would overstate reliability. Wider intervals should be read as less precision, not as a larger expected price move.
  • Forecasts are secondary to observed reports and are information only, not trading, procurement, or financial advice.