Training data generation.

docs/README.md

@@ -12,6 +12,8 @@ Responsible for acquiring and storing market, asset, and any future feature data
 
 The first planned tool is an IBKR daily candle fetcher. It should fetch open, high, low, close, and volume data for a ticker and date range, then eventually persist that data to a ticker-named Parquet file. See [data-fetcher.md](data-fetcher.md).
 
+The initial supervised training dataset is documented in [training-dataset.md](training-dataset.md). It derives market-regime features from `SPY`, `VIX`, `TLT`, and `USO`, then labels whether `SPY` closes higher five trading days later.
+
 Parquet files are partitioned by ticker, not by date.
 
 Open decisions:
@@ -30,7 +32,6 @@ Responsible for building datasets, training models, evaluating candidates, and w
 Open decisions:
 
 - prediction target;
-- feature set;
 - model family;
 - validation strategy;
 - evaluation metrics;