Momentum Investing

What Is Momentum Investing?

Momentum investing is a rules‑based strategy that seeks to profit from the persistence of existing price trends. The core idea: buy securities that have been rising and sell (or short) those that have been falling, remaining with the trend until there is a clear technical signal of reversal. Momentum can be applied to individual stocks, ETFs, futures, currencies and cross‑asset relationships.

Fast fact

– The most famous academic evidence for momentum is Jegadeesh and Titman (1993), who documented that buying recent winners and selling recent losers produced above‑market returns over 1965–1989 (short‑to‑intermediate horizons). (Jegadeesh & Titman, 1993)

Key ideas (overview)

– Momentum ≈ the tendency for a price trend to continue.
– Strategy types: trend‑following (moving averages), relative‑strength ranking (buy top decile, short bottom decile), sector rotation, long‑short pairings, or hybrid systems that mix momentum with fundamentals (e.g., CAN SLIM). (Investopedia)
– Momentum trading is typically technical‑indicator driven (RSI, MACD, ROC, stochastics, moving averages). (Investopedia)
– Critics point to market efficiency and the preference of many managers for fundamentals; proponents point to persistent academic and practical evidence that momentum works. (UCLA Anderson Review; Investopedia)

Important

– Liquidity, transaction costs, slippage and taxes matter for momentum because it often requires frequent trades and may tilt toward smaller-cap or less liquid names if not constrained. (Investopedia)
– Momentum can be applied across timeframes. Short‑term momentum (days–weeks) uses different signals than medium‑term (3–12 months) or long‑term (1+ year) strategies. (Investopedia)

The debate over momentum investing

– Support: academic papers and practitioner results show momentum outperformance over many periods and markets (e.g., Jegadeesh & Titman, 1993). Some practitioner systems (CAN SLIM) combine earnings momentum with price momentum and have shown strong historic results in backtests and some out‑of‑sample tests. (Jegadeesh & Titman, 1993; Lutey & Rayome, 2022; Investopedia)
– Criticism: momentum appears to conflict with the Efficient Market Hypothesis; it can crash during severe reversals and may underperform for long stretches, particularly when risk/valuation regimes change. Professional managers often prefer fundamental valuation and cash‑flow analysis for long‑term outperformance. (UCLA Anderson Review; Investopedia)

What technical indicators can momentum traders use?

Common momentum indicators and how traders use them:
– Moving average crossovers (e.g., 50‑day vs 200‑day): buy when shorter MA crosses above longer MA (golden cross); sell when it crosses below (death cross). Good for medium/long‑term trend signals. (Investopedia)
– Relative Strength Index (RSI): oscillates 0–100. Values above ~70 indicate overbought (possible pullback); below ~30 indicate oversold. Momentum traders sometimes use RSI divergences or RSI thresholds for entries/exits.
– Moving Average Convergence Divergence (MACD): difference between two EMAs and its signal line; crossovers and histogram direction help identify momentum strength and turning points.
– Rate of Change (ROC): percent change over X periods. Useful to rank securities by momentum.
– Stochastics: compares close to price range over a look‑back period; helps spot momentum loss or continuation.
– Cross‑asset signals: e.g., yield curve relationships (10‑yr vs 2‑yr) have been used as macro momentum indicators for equity positioning. (Investopedia)

What is the formula for market momentum?

A simple, commonly used (price‑difference) momentum measure:
M = V − Vx
– M = momentum
– V = the most recent price
– Vx = the closing price x days ago
Example: if current price V = $105 and V10 (10 days ago) = $100, then M = $5 (or +5%). Many traders convert that to a percent: (V − Vx)/Vx × 100%.

Practical steps to implement a momentum strategy

Below is a practical, step‑by‑step implementation checklist suitable for an individual investor or trader. Adjust parameters to your time horizon, capital and risk tolerance.

1) Define objective and time horizon

– Short‑term day/swing: indicators with short look‑backs (5–21 days).
– Medium‑term: 3–12 month momentum (popular in academic/quant work).
– Long‑term trend following: multi‑month to multi‑year moving averages.

2) Select the trading universe

– Highly liquid stocks, sector ETFs or broad ETFs to avoid slippage and high execution cost.
– Avoid penny stocks unless you explicitly account for higher costs and risks.

3) Choose momentum metrics and parameters

– Example medium‑term system: rank universe by 6‑month total return, buy top decile and short bottom decile, rebalance monthly.
– Example trend‑following system: 50/200‑day MA crossover for entries/exits.
– Combined systems: require both price momentum (price above X‑day MA) and fundamental momentum (improving EPS). (CAN SLIM hybrid approach)

4) Define clear entry rules

– E.g., buy when 50‑day MA crosses above 200‑day and price is in top 20% by 6‑month return. Or buy when RSI > 50 and ROC positive. Keep rules deterministic.

5) Define exit and risk management rules

– Stop losses: fixed percent (e.g., 8–12%), ATR‑based trailing stops, or MA crossover exit.
– Profit targets are optional; many momentum systems use trailing stops so winners can run.
– Position sizing: risk per trade (e.g., 1–2% of portfolio) and maximum exposure per sector.

6) Rebalancing frequency

– Define rebalancing cadence: daily (for active traders), weekly, or monthly (common for cross‑section momentum). More frequent rebalancing increases costs.

7) Account for transaction costs and taxes

– Backtest with realistic commissions, bid/ask spreads and shorting costs. For taxable accounts, frequent trading can create short‑term gains taxed at higher rates.

8) Backtest and paper trade

– Use historical data and realistic assumptions. Look for robustness to parameter variation and include transaction costs/slippage. Paper trade to validate live execution and psychology.

9) Monitor, review and iterate

– Keep track of drawdowns, win/loss ratios, and tail risk. Be disciplined about following rules—momentum works best with consistent execution.

10) Consider blending with fundamentals

– To reduce some crash risk, combine momentum with valuation or quality filters (e.g., minimum market cap, profitability screens, or earnings momentum like CAN SLIM). (Investopedia; Lutey & Rayome, 2022)

Example simple retail momentum rule (medium‑term)

– Universe: S&P 500 stocks with average daily volume > $1M.
– Rank by 6‑month total return.
– Entry: top 10% (or top 5 stocks) — buy on monthly rebalance.
– Exit: drop out of top 20% or price falls below 50‑day MA; use 8% trailing stop.
– Position sizing: equal weight, limit position size to 5% of portfolio.
– Rebalance monthly.

Risk considerations and common pitfalls

– Momentum crashes: momentum strategies can suffer abrupt, correlated reversals. Tail risk is real—define drawdown limits and stop rules.
– Transaction costs and market impact: frequent rotation can erode returns, particularly in small caps. Always test with realistic costs. (Investopedia)
– Overfitting: tune parameters conservatively and test out‑of‑sample.
– Data‑snooping: many momentum wins in backtests disappear when realistic constraints are applied. (UCLA Anderson Review discussion)

Market psychology behind momentum trading

– Herd behavior, fear of missing out (FOMO) and information cascades cause trends to persist beyond immediate fundamentals. Investors piling into winners can create self‑reinforcing price moves; conversely, fear and panic can amplify declines. Momentum traders attempt to exploit these behavioral dynamics, staying with the herd while it runs and exiting when momentum indicators suggest the herd is reversing. (Investopedia; Tanous, 1999)

Advanced variants and professional approaches

– Long‑short quant momentum: rank a large universe, go long top decile and short bottom decile to reduce market beta.
– Sector rotation: long strongest momentum sectors, short weakest sectors; rotate periodically. (Investopedia)
– Cross‑asset momentum: rotate between asset classes (equities, bonds, commodities) by momentum score.
– Hybrid systems: combine momentum with value/quality to capture multiple factor premia and potentially reduce crashes.

Empirical evidence and research

– Jegadeesh & Titman (1993) demonstrated momentum profits in U.S. equities over short–intermediate horizons.
– CAN SLIM‑style systems (mix of earnings momentum and price momentum) have shown positive results in some studies and practitioner reports; careful live testing is needed. (Lutey & Rayome, 2022; Investor’s Business Daily profile)
– The academic and practitioner debate continues on why momentum works (behavioral vs risk explanations) and on robustness across periods and markets. (UCLA Anderson Review)

Practical checklist before you trade

– Have explicit entry and exit rules.
– Backtest with realistic trading frictions.
– Limit exposure per trade and manage position sizing.
– Use liquid instruments (ETFs/stocks) for ease of execution.
– Monitor maximum drawdown and have a plan for regime changes.
– Consider tax and margin implications (especially for shorting).
– Start small and paper trade if new to momentum.

If you’d like, I can:

– Convert one of the example rule sets into a backtestable specification (parameter list) you can paste into a backtesting platform.
– Build a concrete monthly rebalance watchlist (long & short candidates) for a given universe and date using look‑back returns and liquidity filters.