Do technical trend trading/intrinsic momentum strategies work for widely used equity factors such as size (small minus big market capitalizations), value (high minus low book-to-market ratios), profitability (robust minus weak), investment (conservative minus aggressive) and momentum (winners minus losers)? In their January 2018 paper entitled “What Goes up Must Not Come Down – Time Series Momentum in Factor Risk Premiums”, Maximilian Renz investigates time variation and trend-based predictability of these five factors and the market factor. He first constructs price series for the six long-short factor portfolios. He then considers seven rules based on a short simple moving average (SMA) crossing above (bullish) or below (bearish) a long SMA measured in trading days: SMA(1, 20), SMA(1, 40), SMA(1, 120), SMA(1, 180), SMA(1, 240), SMA(20, 180) and SMA(20, 240). He also considers two intrinsic (absolute or time series) momentum rules based on change in price over the past 180 or 240 trading days (positive bullish and negative bearish). Motivated by prior research by others, he focuses on SMA(1, 180), daily price crossing its 180-day SMA. He measures trend-based statistical predictability of factor premiums and investigates economic value via a strategy that levers factor exposures between 0 and 1.5 using trend-based signals. Finally, he examines whether incorporating trend information improves accuracies of 1-factor (market), 3-factor (adding size and value) and 5-factor (further adding profitability and investment) models of stock returns. Using daily returns for the six selected U.S. stock market equity factors and for 30 industries during July 1963 through December 2015, he finds that:
- Equity factor portfolios trend. Specifically:
- Premiums are significantly higher (lower) after recent factor uptrends (downtrends), most strongly for value and least strongly for the market.
- Predictability is stronger during factor downtrends/crashes than during uptrends.
- Results are robust across technical indicators and over time, and they apply to both long and short sides of factors portfolios.
- Relative to untimed factor portfolios, a strategy that applies trend-based signals to lever factor exposures up or down based to maximize expected Sharpe ratio produces:
- Gross annualized utility gains ranging from 1.8% to 4.4% across factors.
- Gross annualized Sharpe ratio increases ranging from 0.16 to 0.43.
- Substantially shallower gross maximum drawdowns for four of six factors.
- Annual factor exposure turnovers ranging from 370% to 640%.
- Trend-based timing improvements derive substantially from protection against factor portfolio crashes. For example, between October 2008 and October 2009, trend-based timing suppresses value portfolio drawdown from -52% to -16%.
- Using trend-based technical indicators improves abilities of factor models to explain stock returns, improving 1-factor model explanatory power from 23% to 60%, 3-factor model explanatory power from 61% to 84% and 5-factor model explanatory power from 66% to 83%. Improvements in explanatory power for 30 industries are even larger.
In summary, evidence indicates that premiums for widely used equity factors trend exploitably over the intermediate term.
Cautions regarding findings include:
- Return calculations are gross, not net. Accounting for frictions may eliminate some or all performance improvements reported above. More specifically:
- The assets considered are essentially indexes based on long-short hedge portfolios. They do not account for costs of transforming indexes to liquid funds, including shorting costs (and inability to short some stocks due to lack of shares to borrow).
- Levering factor exposures up and down as specified introduces large turnovers of the factor portfolio holdings that may be costly to execute.
- There may be inherited data snooping bias in focusing on the SMA(1, 180) rule. Also, in general, testing multiple strategy variations on multiple factor premiums introduces snooping bias, such that the best historical backtests overstate expectations.
