Time Series Momentum
Time Series Momentum means the direction of a security or assets own price trend is a future predictor of its future trend. Times series momentum looks at a stock or markets own rate of change in its price trend. Applying time series momentum is a simple method of trend following.
Time Series Momentum demonstrates predictive ability. For example, the past 3 to 12-month price trend of a stock or market is a positive predictor of its future return. The positive trend momentum is expected to continue for some time.
An advantage of Time Series Momentum is that time series momentum returns demonstrate its edge when the stock market return is most extreme. We find empirical evidence for the existence of both market dislocation and momentum. So, time series momentum may be applied for position risk management or a hedge for bear markets and extreme events. However, time series momentum alone is not a complete risk management system.
Momentum is the effect, not the cause. What economic and behavioral finance theory causes Time Series Momentum?
Research studies find that the time series momentum effect is consistent with the behavioral theory that investors initially under-react to new information and also overreact to information dissemination. Information may be released at the same time and investors have access to it, but investors react to the information at different times. Some investors may delay their reaction, so they under-react to new information which causes the price to trend instead of an immediate adjustment to its future value. Investors may also over-react to information, causing prices to trend too far, too fast, which then leads to countertrends and mean reversion. There is a wide range of explanations from behavioral biases that may cause the momentum effect. Others believe an adaptive markets theory may explain momentum. In adaptive markets, momentum is simply caused by slow or prolonged periods of market divergence.
Cross-sectional momentum has been a well-documented anomaly for decades. Cross-sectional momentum applies a relative strength measure to a universe of stocks or markets (asset classes) to determine past winners and predicts those relative strength leaders will continue to outperform the laggards in the future. Cross-sectional momentum was originally simply called “momentum” and most investment managers simply called it “relative strength”. Momentum is the empirically observed tendency for rising prices to rise further. For example, a Jegadeesh and Titman (1993) study showed that stocks with strong performance over the past 3 to 12 months continue to outperform over the next 12 months. The high momentum stocks also outperform stocks with poor past performance in the next period.
Time series momentum is different than cross-sectional momentum.
Cross-sectional momentum is based on price trends between different markets or securities in the cross-section. What is the relative strength of a cross-section of markets? We rank them based on their relative momentum to determine which markets or stocks have gained more and which have gained less.
Time series momentum is momentum across time. Time series refers to a price trend, so time series momentum is the rate of change of a market or stocks on price trend.
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