feat(data): add data models for ticker and trading features

paperone/data.py

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+from dataclasses import dataclass
+from datetime import datetime
+from typing import List
+
+
+@dataclass
+class TickerData:
+    date: datetime
+    open: float
+    close: float
+    low: float
+    high: float
+    avg: float
+    volume: float
+
+
+@dataclass
+class TimeSeriesFeatures:
+    ticker: str
+    target_date: datetime
+    current_day_data: TickerData
+    past_30d_data: List[TickerData]
+
+
+@dataclass
+class TradingFeatures:
+    ticker: str
+    target_date: datetime
+
+    # Current day features
+    current_open: float
+    current_high: float
+    current_low: float
+    current_close: float
+    current_volume: float
+
+    # Lagged price features (last 5 days)
+    close_lag_1: float
+    close_lag_2: float
+    close_lag_3: float
+    close_lag_4: float
+    close_lag_5: float
+
+    # Lagged volume features
+    volume_lag_1: float
+    volume_lag_2: float
+    volume_lag_3: float
+    volume_lag_4: float
+    volume_lag_5: float
+
+    # 5-day rolling window features
+    rolling_5d_mean: float
+    rolling_5d_std: float
+    rolling_5d_min: float
+    rolling_5d_max: float
+    rolling_5d_range: float
+    rolling_5d_volume_mean: float
+    rolling_5d_returns: float
+
+    # 10-day rolling window features
+    rolling_10d_mean: float
+    rolling_10d_std: float
+    rolling_10d_min: float
+    rolling_10d_max: float
+    rolling_10d_range: float
+    rolling_10d_volume_mean: float
+    rolling_10d_returns: float
+
+    # 30-day rolling window features
+    rolling_30d_mean: float
+    rolling_30d_std: float
+    rolling_30d_min: float
+    rolling_30d_max: float
+    rolling_30d_range: float
+    rolling_30d_volume_mean: float
+    rolling_30d_returns: float
+
+    # VIX features (from separate VIX time series)
+    vix_current: float
+    vix_lag_1: float
+    vix_lag_5: float
+    vix_rolling_5d_mean: float
+    vix_rolling_10d_mean: float
+    vix_rolling_30d_mean: float
+    vix_rolling_30d_std: float