Daily Academic Alpha: Which Trend if Your Friend?

/Daily Academic Alpha: Which Trend if Your Friend?

Daily Academic Alpha: Which Trend if Your Friend?

By | 2017-08-18T17:07:01+00:00 May 19th, 2015|Uncategorized|4 Comments

Which Trend Is Your Friend?

Managed-futures funds (sometimes called CTAs) trade predominantly on trends. There are several ways of identifying trends, either using heuristics or statistical measures often called “filters.” Two important statistical measures of price trends are time series momentum and moving average crossovers. We show both empirically and theoretically that these trend indicators are closely connected. In fact, they are equivalent representations in their most general forms, and they also capture many other types of filters such as the HP filter, the Kalman filter, and all other linear filters. Further, we show how trend filters can be equivalently represented as functions of past prices vs. past returns. Our results unify and broaden a range of trend-following strategies and we discuss the implications for investors.

Uncovering Trend Rules

Trend rules are widely used to infer whether financial markets show an upward or downward trend. By taking suitable long or short positions, one can profit from a continuation of these trends. Conventionally, trend rules are based on moving averages (MAs) of prices rather than returns, which obscures how much weight is assigned to different historical time periods. In this paper, we show how to uncover the underlying historical weighting schemes of price MAs and combinations of price MAs. This leads to surprising and useful insights about popular trend rules, for example that some trend rules have inverted information decay (i.e., distant returns have more weight than recent ones) or hidden mean-reversion patterns. This opens the possibility for improving the trend rule by analyzing the added value of the mean reversion part. We advocate designing trend rules in terms of returns instead of prices, as they offer more flexibility and allow for adjusting trend rules to autocorrelation patterns in returns.


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About the Author:

Wes Gray
After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes, ETF.com, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.

4 Comments

  1. dph May 19, 2015 at 6:47 pm

    I know guys who have gotten over 20% for decades (caveat: by their own admission) just by using moving averages alone. Amazing that these techniques have held up so well over decades. Most of them also using 15-25% stop loses, but no tighter, keeping them out of the rare maximum drawdown. Sometimes keeping it simple handily beats complex strategies.

    • Jack Vogel
      Jack Vogel, PhD May 20, 2015 at 11:27 am

      We agree — if possible, keep it simple!

  2. Govind May 20, 2015 at 9:44 am

    What paper are you referring to?

    • Jack Vogel
      Jack Vogel, PhD May 20, 2015 at 11:26 am

      The title of the papers above have a hyperlink to the papers on SSRN.

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