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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

DJIA-Gold Ratio as a Stock Market Indicator

A reader requested a test of the following hypothesis from the article “Gold’s Bluff – Is a 30 Percent Drop Next?” [no longer available]: “Ironically, gold is more than just a hedge against market turmoil. Gold is actually one of the most accurate indicators of the stock market’s long-term direction. The Dow Jones measured in gold is a forward looking indicator.” To test this assertion, we examine relationships between the spot price of gold and the level of the Dow Jones Industrial Average (DJIA). Using monthly data for the spot price of gold in dollars per ounce and DJIA over the period January 1971 through January 2019 (577 months), we find that: Keep Reading

Tug-of-war Risk and Future Stock Returns

Does persistence in the difference in direction between overnight stock trading and intraday stock trading behaviors (tug of war) predict future returns? In their January 2019 paper entitled “Overnight Returns, Daytime Reversals, and Future Stock Returns: The Risk of Investing in a Tug of War with Noise Traders”, Ferhat Akbas, Ekkehart Boehmer, Chao Jiang and Paul Koch investigate relationships between intensity of the daily tug-of-war between between overnight (noise) and intraday (other) stock traders and future stock returns. They specify tug-of-war intensity as percentage of trading days during a month for which a stock exhibits negative (or positive) daytime reversals divided by average monthly percentage of negative (or positive) reversals over the last 12 months. They then examine whether either negative or positive tug-of-war intensity predicts future stock returns. Using overnight/intraday stock returns for a broad sample of U.S. common stocks, along with monthly returns for widely accepted factors, during May 1993 through December 2017, they find that:

Keep Reading

Weekly Summary of Research Findings: 2/25/19 – 3/1/19

Below is a weekly summary of our research findings for 2/25/19 through 3/1/19. 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

Commercial and Industrial Credit as a Stock Market Driver

Does commercial and industrial (C&I) credit fuel business growth and thereby drive the stock market? To investigate, we relate changes in credit standards from the Federal Reserve Board’s quarterly Senior Loan Officer Opinion Survey on Bank Lending Practices to future U.S. stock market returns. Presumably, loosening (tightening) of credit standards is good (bad) for stocks. The Federal Reserve publishes survey results about the end of the first month of each quarter (January, April, July and October). Using the “Net Percentage of Domestic Respondents Tightening Standards for C&I Loans” for large and medium businesses from the Senior Loan Officer Opinion Survey on Bank Lending Practices Chart Data for the second quarter of 1990 through the first quarter of 2019 (117 surveys), and contemporaneous S&P 500 Index quarterly returns (aligned to survey months), we find that: Keep Reading

Add Position Stop-gain to SACEMS?

Does adding a position take-profit (stop-gain) rule improve the performance of the “Simple Asset Class ETF Momentum Strategy” (SACEMS) by harvesting some upside volatility? SACEMS 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 the value of stop-gains, we augment SACEMS with a simple rule that: (1) exits to Cash from any current winner ETF when its intra-month return rises above a specified threshold; and, (2) re-sets positions per winners at the end of the 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 and intra-month maximum returns for the specified assets during February 2006 (limited by DBC) through January 2019, we find that: Keep Reading

Add Position Stop-loss to SACEMS?

Does adding a position stop-loss rule improve the performance of the “Simple Asset Class ETF Momentum Strategy” (SACEMS) by avoiding some downside volatility? SACEMS 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 the value of stop-losses, we augment SACEMS with a simple rule that: (1) exits to Cash from any current winner ETF when its intra-month return falls below a specified threshold; and, (2) re-sets positions per winners at the end of the 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 and intra-month drawdowns for the specified assets during February 2006 (limited by DBC) through January 2019, we find that: Keep Reading

Simple Term Structure ETF/Mutual Fund Momentum Strategy

Does a simple relative momentum strategy applied to tradable U.S. Treasury term structure proxies produce attractive results by picking the best duration for exploiting current interest rate trend? To investigate, we run short-term and long-term tests. The short-term test employs four exchange-traded funds (ETF) to represent the term structure:

SPDR Barclays 1-3 Month T-Bill (BIL)
iShares 1-3 Year Treasury Bond (SHY)
iShares Barclays 7-10 Year Treasury Bond (IEF)
iShares Barclays 20+ Year Treasury Bond (TLT)

The second test employs three Vanguard mutual funds to represent the term structure:

Vanguard Short-Term Treasury Fund (VFISX)
Vanguard Intermediate-Term Treasury Fund (VFITX)
Vanguard Long-Term Treasury Fund (VUSTX)

For each test, we allocate all funds at the end of each month to the fund with the highest total return over a specified ranking (lookback) interval, ranging from one month to 12 months. To accommodate the longest lookback interval, portfolio formation commences 12 months after the start of the sample. We focus on compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as key performance metrics. Using monthly dividend-adjusted closing prices for BIL since May 2007, for SHY, IEF and TLT since July 2002 and for VFISX, VFITX and VUSTX since October 1991, all through January 2019, we find that: Keep Reading

Warren Buffett on Investing

Does Warren Buffett consistently keep Berkshire Hathaway in market-beating form? If so, how does he do it? In his annual letters to stockholders, he includes company performance and benchmark data and describes in general terms how he goes about investing. He sometimes shares his thoughts on the current state of and prospects for the U.S. equity market. Using annual performance data from his 2018 letter for 1965 through 2018 (54 years) and the investing approach/outlooks described in his letters of 1977 through 2018, we find that: Keep Reading

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