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SACEMS at Weekly and Biweekly Frequencies

Posted in Momentum Investing, Strategic Allocation

Subscribers asked whether weekly or biweekly (every two weeks) measurement of asset class momentum works better than monthly measurement as used in “Simple Asset Class ETF Momentum Strategy” (SACEMS), hypothesizing that the faster frequencies would respond more quickly to market turns. To investigate, we compare simple weekly, biweekly and monthly strategies as applied to the following eight asset class exchange-traded funds (ETF), plus cash:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 2000 Index (IWM)
SPDR S&P 500 (SPY)
iShares Barclays 20+ Year Treasury Bond (TLT)
Vanguard REIT ETF (VNQ)
3-month Treasury bills (Cash)

We use comparable lookback intervals, though they differ slightly due to mismatches between ends of weeks and ends of months. We consider portfolios of past ETF winners based on Top 1 and on equally weighted (EW) Top 2 and Top 3. We consider as benchmarks an equally weighted portfolio of all ETFs, rebalanced at the measurement frequency (EW All) and basic SACEMS at a monthly frequency. We focus on gross compound annual growth rates (CAGR), annual returns and maximum drawdowns (MaxDD) as performance metrics. Using weekly dividend-adjusted closing prices for the asset class proxies and the yield for Cash during February 2006 (when all ETFs are first available) through May 2017 (136 months), we find that:

We first look at weekly measurement frequency, with 20-week lookback interval as most comparable to the baseline 5-month lookback interval tracked in monthly SACEMS. The following chart compares gross cumulative performances of Top 1, EW Top 2 and EW Top 3 portfolios for weekly SACEMS over the available sample period. Notable points are:

  • All momentum portfolios outperform naive, equally weighted diversification across all assets.
  • The Top 1 portfolio is very volatile.
  • The momentum portfolios have not recently performed well.

What about the biweekly frequency?

The next chart compares gross cumulative performances of Top 1, EW Top 2 and EW Top 3 portfolios for biweekly SACEMS (lookback interval 10 biweeks) over the available sample period. Notable points are:

  • Again, all momentum portfolios outperform naive, equally weighted diversification across all assets.
  • The Top 1 portfolio is again very volatile, but performs better than for weekly SACEMS.
  • Again, the momentum portfolios have not recently performed well.

How do the above performances compare to that of basic monthly SACEMS?

The following table compares (mostly) annual performance statistics for weekly, biweekly and monthly SACEMS Top 1 portfolios with comparable lookback intervals over the available sample period. Rough Sharpe ratio ignores the risk-free rate, which is near zero for most of the sample period. Notable points are:

  • Based on returns, the biweekly measurement frequency is mostly the best, followed closely by the monthly measurement frequency. The biweekly frequency has somewhat deeper MaxDD (but MaxDDs measured at different frequencies are not perfectly comparable).
  • Higher measurement frequencies means more ETF switches and therefore higher trading frictions, such that net results may differ from gross results.
  • Differences in performance across measurement frequencies indicate that the momentum model is subject to considerable noise.

What about the EW Top 2 portfolios?

The next table compares (mostly) annual performance statistics for weekly, biweekly and monthly SACEMS EW Top 2 portfolios with the specified comparable lookback intervals over the available sample period. Notable points are:

  • Based on returns, weekly and biweekly measurement frequencies are best, with similar MaxDDs for all three portfolios.
  • Again, higher measurement frequencies means more ETF switches and therefore higher trading frictions, such that net results may differ from gross results.
  • Again, differences in performance indicate considerable noise effects on the momentum model.

What about the EW Top 3 portfolios?

The final table compares (mostly) annual performance statistics for weekly, biweekly and monthly SACEMS EW Top 3 portfolios with the specified comparable lookback intervals over the available sample period. Notable points are:

  • Based on returns, the monthly measurement frequency is best, with similar MaxDDs for all three portfolios.
  • Again, higher measurement frequencies means more ETF switches and therefore higher trading frictions, such that net results may differ from gross results.
  • Again, differences in performance indicate considerable noise effects on the momentum model.

In summary, evidence from a limited sample period suggests that SACEMS at weekly and biweekly measurement frequencies are no better than the basic monthly SACEMS for a diversified momentum portfolio, especially after accounting for higher switching frictions.

Cautions regarding findings include:

  • As noted, sample size is modest (about 27 independent lookback intervals).
  • As noted, annual measurements are slightly misaligned for end-of-week versus end-of-month data. Measurement frequency also affects MaxDD measurements.
  • As noted, analyses are gross. Accounting for costs of regular portfolio reformation would reduce returns, and performance reduction deepens as portfolio reformation frequency increases.
  • Weekly and biweekly measurement frequencies require more effort than monthly measurements.
  • Other weekly and biweekly lookback intervals may work better, but experimentation would elevate data snooping bias, which is especially pernicious for small samples.
  • Other cautions noted in “Simple Asset Class ETF Momentum Strategy” apply.
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