Do Moving Averages Add Value in Factor Investing?

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Moving averages are a useful tool in investing. They smooth out price data over a specific period, providing a clearer trend perspective. The most common types are the simple moving average (SMA) and the exponential moving average (EMA). Investors often use moving averages to identify trends and filter out short-term price fluctuations.

Factor investing is a strategy in which investors focus on specific characteristics or factors that historically contributed to the outperformance of certain stocks. Factor investing emphasizes factors such as value, size, momentum, quality, and low volatility. Factor investing relies on empirical research and data analysis to identify these factors and incorporate them into a systematic investment approach.

Reference [1] investigates the added value of moving averages in factor investing in the Chinese stock market. The approach involves enhancing a four-factor model by incorporating two moving averages, resulting in a six-factor model. The authors pointed out,

  • First, the investment term structures in the Chinese market are diversified. Investors’ behavioral decisions with different investment term structures can obtain excess returns, but short-term investment returns are significantly higher, indicating that investors with heterogeneous beliefs in the Chinese market prefer short-term positive market news rather than long-term value investment.
  • Second, moving averages with different term structures are factored into the pricing model to capture the trading information of heterogeneous investors. By studying the excess returns of different moving average strategies, we introduce moving average factors with different term structures. To avoid factor redundancy, we introduce two moving average factors derived from double moving trading strategies based on short-term moving average of 1-month and long-term moving averages of 3-, 12-month. These two moving average factors significantly improving the pricing power of the Chinese market anomalies.

In brief, incorporating moving averages enhances the factor model’s performance. However, it’s important to note that this result is specific to the Chinese stock market, where retail investors dominate and the trading behavior of noise traders significantly influences the market.

Let us know what you think in the comments below or in the discussion forum.

References

[1] YuZhi Chen, Yi Fang, XinYue Li & Jian Wei, A factor pricing model based on double moving average strategy, Humanit Soc Sci Commun 10, 830 (2023).

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