V38 · HISTORICAL LEARNING ENGINE

BTC Prediction Lab

Train on past candles. Predict the next 15-minute direction. Lock each forecast. Score it later.

0No candle history found
0Samples are spaced 15 minutes apart to reduce label overlap
—No test run yet
—Must beat a simple baseline to claim predictive value
STEP 1 · DATA

Load historical candles

Shares the same browser storage as Candle History & Compare. Import OHLCV history there, then return here. You can also load a CSV directly.

Download all raw data (.CSV.GZ)

Supports plain .csv and compressed .csv.gz files. Large archives are streamed and the latest 250,000 valid candles are kept in memory to avoid freezing the browser. Recommended: thousands to hundreds of thousands of 1-minute candles covering multiple market regimes. The bundled scorecard and V28 files are prediction records, not OHLCV candles, so they cannot train a candle-feature model by themselves. Full archive source: Bitstamp BTC/USD, 6.85 million rows, Jan 2012–Jan 2025. The model retains at most the latest 250,000 candles in memory; download the raw archive link to keep all rows locally.

Waiting for candle history.
STEP 2 · TRAIN AND TEST

Historical predictive test

Chronological 70/30 split; features use only candles available at prediction time. Test labels are never used to fit the model.

No test computed yet.
Signal featureCorrelation with next 15m returnDirectionInterpretation
Run the test to calculate feature correlations from loaded candles.
STEP 3 · MAKE ONE FORECAST

Next 15-minute direction

Uses a logistic model trained on the loaded history. The forecast is timestamped and saved once; it is not continuously rewritten.

NOT PREDICTED

Load a valid candle history and run the historical test before generating a forecast.

Probability is a model estimate, not a calibrated real-world chance until calibration is verified. “No edge” is an acceptable model conclusion.

STEP 4 · IMMUTABLE HISTORY

Locked predictions & outcomes

Each locked forecast is append-only. Once the 15-minute horizon has elapsed, score against the candle close if matching candles are available.

Created UTCSpotForecastModel probability UPHorizon endActualResult
No locked predictions yet.

How this engine looks for correlations

Momentum

Returns over 1, 3, 5, 10, 15 and 30 minutes.

Volatility

Recent realized volatility and candle range relative to price.

Candle structure

Body direction and size relative to the high-low range.

Volume behavior

Recent volume versus its trailing average, when volume is available.

Forward target

Whether the close 15 minutes later is above or below the current close.

Validation

Chronological holdout, accuracy, Brier score, log loss, majority baseline and momentum baseline.

Correlation is association, not causation. The current bundled prediction records previously showed only weak relationship between the forecast and outcome, and the always-UP baseline did better in that sample. This new engine is designed to test actual candle-derived features separately rather than assume prior forecasts are informative.