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Features

DeepAlpha's free version computes 15 technical features from raw OHLCV candle data. All features are normalized so the model can generalize across coins with different price scales.


Feature List

Basic Price Features

# Feature Description
1 rsi_14 Relative Strength Index over 14 periods. Measures whether an asset is overbought (>70) or oversold (<30). Bounded between 0 and 100.
2 atr_14 Average True Range over 14 periods, normalized by close price. Measures current volatility as a fraction of price. Higher values indicate more volatile conditions.
3 ema_12_26_diff Difference between the 12-period and 26-period exponential moving averages, normalized by close price. Positive values indicate bullish momentum (fast EMA above slow EMA), negative values indicate bearish momentum. This is essentially a normalized MACD line.

Momentum Features

# Feature Description
4 price_momentum_3 Percentage price change over the last 3 candles. Captures short-term directional momentum.
5 price_momentum_7 Percentage price change over the last 7 candles. Captures medium-term directional momentum. Comparing 3-period and 7-period momentum reveals whether a move is accelerating or decelerating.

Volume Features

# Feature Description
6 volume_ma_ratio Current volume divided by the 20-period simple moving average of volume. Values above 1.0 indicate above-average volume (potential breakout or capitulation). Values below 1.0 indicate quiet markets.
7 volume_change_pct Percentage change in volume from the prior candle. Sudden volume spikes often precede large price moves.

Volatility Features

# Feature Description
8 high_low_range (High - Low) / Close for each candle. Measures intra-candle volatility. Wide ranges suggest high volatility or potential reversal.
9 candle_body_ratio |Close - Open| / (High - Low). Ratio of the candle body to the total range (body + wicks). Values near 1.0 indicate strong directional moves. Values near 0.0 indicate indecision (long wicks, small body -- doji patterns).

Price Structure Features

# Feature Description
10 close_vs_open (Close - Open) / Open. The directional movement of the candle as a percentage. Positive = green candle, negative = red candle.
11 price_vs_vwap Price relative to the session VWAP (Volume Weighted Average Price). (Close - VWAP) / VWAP. Positive values mean price is above average transaction price (bullish), negative means below (bearish). VWAP is approximated using a cumulative calculation.
12 dist_from_24h_high (Close - 24h_Rolling_High) / 24h_Rolling_High. How far the current price is from the rolling 24-hour high. Always negative or zero. Values near zero indicate price is at recent highs.
13 dist_from_24h_low (Close - 24h_Rolling_Low) / 24h_Rolling_Low. How far the current price is above the rolling 24-hour low. Always positive or zero. Values near zero indicate price is at recent lows.

Advanced Features

# Feature Description
14 btc_correlation_20 20-period rolling Pearson correlation between the coin's close price and BTC's close price. Values near 1.0 mean the coin moves in lockstep with BTC. Values near 0.0 indicate independent movement. Low correlation coins offer diversification when BTC dominates the market.
15 funding_rate The current Hyperliquid funding rate for the asset. Positive funding means longs pay shorts (market is bullish/overleveraged long). Negative funding means shorts pay longs. Extreme funding rates often precede reversals.

Why These Features?

The feature set was chosen based on several principles:

  1. Normalization -- Every feature is expressed as a ratio or percentage, not an absolute value. This allows the model to learn patterns that generalize across BTC ($60,000) and PEPE ($0.00001) without scale bias.

  2. Complementary signals -- The features cover different aspects of market microstructure: trend (EMA, momentum), mean reversion (RSI), volatility (ATR, range), volume activity, price structure (VWAP, 24h range), and cross-asset correlation.

  3. No lookahead bias -- Every feature is computed using only past data available at prediction time. The training pipeline enforces chronological splitting to prevent data leakage.

  4. Computational efficiency -- All features are computed using pure NumPy without external TA libraries. This keeps the dependency footprint minimal and allows fast computation during live trading.


Pro Version Features

The Pro version expands the feature set to 40+, adding:

Category Features
Funding dynamics funding_rate_delta_1h, funding_rate_delta_4h, funding_rate_delta_8h, funding_oi_weighted
Open Interest oi_change_pct, oi_value
Order flow order_flow_ratio, obi_proxy, obi_momentum
Cumulative Volume Delta cvd_5, cvd_20
Multi-timeframe rsi_4h
Sentiment fear_greed_index
Liquidation liquidation_pressure
Statistical price_skewness_24, price_kurtosis_24, linear_trend_slope_24
Time hour_of_day, day_of_week
Streak consecutive_green, consecutive_red
Divergence rsi_divergence
Volume momentum volume_momentum_3

These additional features capture order flow dynamics, market sentiment, and cross-timeframe signals that the free version does not include.