Momentum Scanner

Trend is the overall direction of price over time. Momentum is the rate/speed of that movement. A stock can be in an uptrend but have slowing momentum (still going up but slower). Momentum often leads trend - weakening momentum can signal trend change ahead.

Not necessarily. Extremely high momentum may be overextended and due for pullback. Look for established momentum (positive ROC, RSI > 50) but not extreme (RSI > 80). Or wait for pullback in strong momentum stocks for better entry.

Signs of fading momentum: RSI divergence (price new high but RSI lower high), declining ROC, falling ADX, volume decreasing on up moves. No single signal is perfect - look for multiple signs. When momentum indicators turn, tighten stops.

Volume should confirm momentum: rising volume on up days (for bullish momentum), volume above 20-day average, OBV trending with price. Warning: low volume on new highs or diverging OBV suggests weak momentum.

Yes. For shorts: ROC negative and falling, RSI below 50, price below 50 MA, volume confirming selling. Short stocks with strong downward momentum. Same principles apply - trade with established momentum, not against it.

Create a composite score: normalize each indicator (0-100 scale), apply weights (e.g., ROC 40%, RSI 30%, RS 30%), sum for composite score. Or use confirmation approach - require multiple indicators to agree before trading.

Depends on trading style. Short-term trading: 5-10 day ROC. Swing trading: 14-20 day. Position trading: 50-100 day. Academic research shows 12-month momentum (with skip month) works well for longer-term strategies.

Calculate RS (stock return / benchmark return) over lookback period. Rank all stocks. Focus on top 20% (leaders). Rising RS line is bullish. New high in RS line = strong leadership. Avoid stocks with falling RS.

Exit options: 1) RSI crosses below 50 (bullish momentum lost), 2) ROC turns negative, 3) Price closes below key MA, 4) ADX turns down, 5) Trailing stop hit. Choose method based on your timeframe and risk tolerance.

Dual momentum combines absolute and relative momentum. Absolute: is the asset trending up (return > risk-free rate)? Relative: is it outperforming alternatives? Only buy if both are positive. This filter reduces drawdowns vs using just one type.

Steps: 1) Define universe and filters, 2) Calculate momentum metrics (ROC, RSI, ADX, RS), 3) Filter for minimum thresholds, 4) Calculate composite score, 5) Rank by score, 6) Output top N with details. Implement in Python with pandas.

Momentum crashes occur during sharp market reversals. Winners (long leg) fall hard; losers (short leg) rally hard. Historically happened in 1932, 2009. Causes: mean reversion after extended trends, liquidity crises, regime changes. Mitigation: use stops, reduce size during high spread periods.

Features: multi-period returns, technical indicators (RSI, MACD, ADX), volume metrics, relative strength. Target: forward return or momentum persistence. Models: Random Forest, XGBoost work well. Key: walk-forward validation to avoid overfitting.

Academic evidence: Jegadeesh-Titman (1993) showed 12-month momentum earns ~1% monthly excess return. Effect documented globally across asset classes. Behavioral explanations: underreaction to news, herding. Risk-based: compensation for crash risk.

Risk management: 1) Use stops religiously, 2) Monitor momentum spread (high spread = elevated risk), 3) Reduce leverage during volatile periods, 4) Consider momentum crash hedges, 5) Diversify across assets/strategies, 6) Accept drawdowns as cost of momentum returns.