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Weekly Summary of Research Findings: 3/11/19 – 3/15/19

Below is a weekly summary of our research findings for 3/11/19 through 3/15/19. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs.

Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list. Keep Reading

Optimal Monthly Cycle for SACEMS?

Is there a best time of the month for measuring momentum within the Simple Asset Class ETF Momentum Strategy (SACEMS)? This strategy each month picks winners from the following set of exchange-traded funds (ETF) based on total returns over a specified lookback interval:

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)

To investigate, we compare 21 variations of the strategy based on shifting the monthly return calculation cycle relative to trading days from the end of the month (EOM). For example, an EOM+5 cycle ranks assets based on closing prices five trading days after EOM each month. We focus on gross compound annual growth rate (CAGR) and gross maximum drawdown (MaxDD) as key performance statistics for the Top 1, equally weighted (EW) Top 2 and EW Top 3 portfolios of monthly winners. Using monthly total (dividend-adjusted) returns for the specified assets during mid-February 2006 (limited by DBC) through mid-February 2019, we find that: Keep Reading

Relative Wealth Effects on Investors

How does investor competitiveness (a goal of relative rather than absolute wealth) affect optimal allocations? In their February 2019 paper entitled “The Growth of Relative Wealth and the Kelly Criterion”, Andrew Lo, Allen Orr and Ruixun Zhang compare optimal portfolios for maximizing relative wealth versus absolute wealth at both short and long investment horizons. They define an individual’s relative wealth as fraction held of total wealth of all investors. Their model assumes that investors allocate to two assets, one risky and one riskless. They identify when an investor should allocate according to the Kelly criterion (series of allocations that maximize terminal wealth over the long run) and when the investor should deviate from it. Based on derivations and modeling, they conclude that:

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SACEMS Top 1 Mean Reversion?

Subscribers asked whether the monthly winner (Top 1) of the Simple Asset Class ETF Momentum Strategy (SACEMS) is more prone to mean reversion than momentum, thereby justifying its exclusion from or lower weight within SACEMS portfolios. SACEMS each month picks winners from the following universe of 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)

To investigate, we review relevant past research and conduct in-depth robustness tests of SACEMS monthly returns and volatilities across all ranks 1 through 9 and ranking (lookback) intervals one to 12 months. Limited by availability of DBC (inception February 2006) and a 12-month lookback interval, we start the comparison with March 2007. Using monthly dividend adjusted closing prices for the asset class proxies and the yield for Cash during February 2006 through February 2019, we find that: Keep Reading

Any Seasonality for Gold or Gold Miners?

Do gold and gold mining stocks exhibit exploitable seasonality? Using monthly closes for spot gold and the S&P 500 Index since December 1974, PHLX Gold/Silver Sector (XAU) since December 1983, AMEX Gold Bugs Index (HUI) since June 1996 and SPDR Gold Shares (GLD) since November 2004, all through January 2019, we find that: Keep Reading

Inflated Expectations of Factor Investing

How should investors feel about factor/multi-factor investing? In their February 2019 paper entitled “Alice’s Adventures in Factorland: Three Blunders That Plague Factor Investing”, Robert Arnott, Campbell Harvey, Vitali Kalesnik and Juhani Linnainmaa explore three critical failures of U.S. equity factor investing:

  1. Returns are far short of expectations due to overfitting and/or trade crowding.
  2. Drawdowns far exceed expectations.
  3. Diversification of factors occasionally disappears when correlations soar.

They focus on 15 factors most closely followed by investors: the market factor; a set of six factors from widely used academic multi-factor models (size, value, operating profitability, investment, momentum and low beta); and, a set of eight other popular factors (idiosyncratic volatility, short-term reversal, illiquidity, accruals, cash flow-to-price, earnings-to-price, long-term reversal and net share issuance). For some analyses they employ a broader set of 46 factors. They consider both long-term (July 1963-June 2018) and short-term (July 2003-June 2018) factor performances. Using returns for the specified factors during July 1963 through June 2018, they conclude that:

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Weekly Summary of Research Findings: 3/4/19 – 3/8/19

Below is a weekly summary of our research findings for 3/4/19 through 3/8/19. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs.

Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list. Keep Reading

Effects of Execution Delay on SACEMS

“Optimal Monthly Cycle for SACEMS?” investigates whether using a monthly cycle other than end-of-month (EOM) to pick winning assets improves performance of the Simple Asset Class ETF Momentum Strategy (SACEMS). This strategy each month picks winners from the following set of exchange-traded funds (ETF) based on total returns over a specified lookback interval:

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)

In response, a subscriber asked whether sticking with an EOM cycle for determining the winner, but delaying signal execution, affects strategy performance. To investigate, we compare 23 variations of SACEMS portfolios that all use EOM to pick winners but shift execution from the contemporaneous EOM to the next open or to closes over the next 21 trading days (about one month). For example, EOM+5 uses an EOM cycle to determine winners but delays execution until the close five trading days after EOM. We focus on gross compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as key performance statistics for the Top 1, equally weighted (EW) Top 2 and EW Top 3 portfolios of monthly winners. Using daily dividend-adjusted opens and closes for the asset class proxies and the yield for Cash during February 2006 (limited by DBC) through January 2019, we find that: Keep Reading

Country Stock Market Anomaly Momentum

Do country stock market anomalies have trends? In his March 2018 paper entitled “The Momentum Effect in Country-Level Stock Market Anomalies”, Adam Zaremba investigates whether country-level stock market return anomalies exhibit trends (momentum) based on their past returns. Specifically, he:

  • Screens potential anomalies via monthly reformed hedge portfolios that long (short) the equal-weighted or capitalization-weighted fifth of country stock market indexes with the highest (lowest) expected gross returns based on one of 40 market-level characteristics/combinations of characteristics. Characteristics span aggregate market value, momentum, reversal, skewness, quality, volatility, liquidity, net stock issuance and seasonality metrics.
  • Tests whether the most reliable anomalies exhibit trends (momentum) based on their respective returns over the past 3, 6, 9 or 12 months.
  • Compares performance of a portfolio that is long the third of reliable anomalies with the highest past returns to that of a portfolio that is long the equal-weighted combination of all reliable anomalies.

He performs all calculations twice, accounting in a second iteration for effects of taxes on dividends across countries. Using returns for capitalization-weighted country stock market indexes and data required for the 40 anomaly hedge portfolios as available across 78 country markets during January 1995 through May 2015, he finds that: Keep Reading

Testing the All Weather Portfolio

A subscriber requested a test of Ray Dalio‘s All Weather (AW) portfolio with different rebalancing frequencies, allocated to exchange-traded funds (ETF) as asset class proxies as follows:

30% – Vanguard Total Stock Market (VTI)
40% – iShares 20+ Year Treasury (TLT)
15% – iShares 7-10 Year Treasury (IEF)
7.5% – SPDR Gold Shares (GLD)
7.5% – Invesco DB Commodity Tracking (DBC)

To investigate, we test:

We consider the following gross performance metrics, all based on monthly measurements: average monthly return, standard deviation of monthly returns, compound annual growth rate (CAGR), maximum drawdown (MaxDD) and Sharpe ratio (with the 3-month Treasury bill yield as the risk-free rate). We also compare number of rebalance actions for each portfolio. Using monthly dividend-adjusted returns for the specified assets during February 2006 (limited by DBC) through January 2019), we find that: Keep Reading

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