Blog - Investing Notes

Market volatility tends to rise as returns fall. Does adding a proxy for U.S. equity market volatility to a diversified portfolio improve its performance? To check, we add iPath S&P 500 VIX Short Term Futures (VXX) to the following mix of asset class proxies (the same used in “Simple Asset Class ETF Momentum Strategy”):

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for VXX and the average pairwise correlation of VXX monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without VXX. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for VXX and the above nine asset class proxies from February 2009 (first return available for VXX) through January 2012 (only 36 monthly returns), we find that: More…

Each year, Forbes calculates the performance of columnist recommendations assuming: (1) equal initial investments in each stock pick when published; (2) 1% trading friction for each purchase; and, (3) matching benchmark investments in the S&P 500 Index for each pick with no trading friction. Because matching benchmark investments are spread across the year, the benchmark performance is not the same as the annual performance of the S&P 500 Index. In his column for the February 27, 2012 issue of Forbes, Ken Fisher reports the performance of the recommendations made in his column during 2011, as follows: “In 2011 my 63 investment recommendations lagged the S&P 500 for the fourth time in the 16 years FORBES has done a formal accounting of columnists’ picks.” More exactly, using the data in the 13 annual performance summary columns for 1998 through 2011 (columns for 1996 and 1997 are apparently unavailable online), we find that: More…

How do pension funds, arguably representative of sophisticated and conservative investors, use real estate as an alternative investment? In their January 2012 paper entitled “Value Added From Money Managers in Private Markets? An Examination of Pension Fund Investments in Real Estate”, Aleksandar Andonov, Piet Eichholtz and Nils Kok investigate the allocation, costs and performance of pension funds with respect to real estate investments. Using self-reported investment data for 884 U.S., Canadian, European and Australian/New Zealand pension funds during 1990 through 2009, they find that: More…

What factors make asset class diversification work? To investigate empirically, we consider the following mix of asset class proxies (the same used in “Simple Asset Class ETF Momentum Strategy”):

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

We calculate the cumulative trajectory for an equally weighted, monthly rebalanced portfolio of all nine asset class proxies. Then we recalculate the trajectory nine times, each time excluding one of them, and relate the resulting terminal values to three individual asset return characteristics: (1) average monthly return; (2) standard deviation of monthly returns; and, (3) average pairwise correlation of returns with the other eight assets. We ignore trading frictions associated with monthly rebalancing, which would be similar for all combinations. Using adjusted monthly returns for the above nine asset class proxies from September 2006 (allowing comparison with the momentum strategy output for the entire set of assets) through January 2012 (65 monthly returns), we find that: More…

The turn of the year (December-January) for the U.S. stock market reportedly includes the Santa Claus rally and the January effect. Some research indicates the latter is dead (and was driven essentially by small-capitalization stocks when alive). How does the stock market behave across the turn of the year for a recent sample? To check, we construct cumulative return profiles from 20 trading days before through 20 trading days after the end of the calendar year for the Russell 2000 Index, the S&P 500 Index and the Dow Jones Industrial Average (DJIA) since the inception of the Russell 2000 Index. Using daily and monthly levels of all three indexes from December 1987 through January 2012 (25 December and 25 January observations), we find that: More…

There is a new “Strategic Allocation” category in the list above that collects posts related to selection and weighting of asset classes for long-term diversification benefits.

Can investors usefully predict the short-term direction of the stock market by contrasting the outlooks implied by out-of-the-money (OTM) and at-the-money (ATM) market index options. In the October 2011 update of their paper entitled “Implied Volatility Spreads and Expected Market Returns”, Turan Bali, Ozgur Demirtas and Yigit Atilgan investigate the relationship between stock market index implied volatility spread (slope of the volatility smile) and future stock market return. They consider several measures of the implied volatility spread, such as the difference in implied volatilities between the S&P 500 Index OTM put option and the ATM call option that have the highest open interest or trading volume each day. They define moneyness as the ratio of strike price to stock price, with ATM (OTM) having moneyness between 0.95 and 1.05 (from 0.8 to 0.95). They exclude options with time to expiration less than 10 days or more than 60 days, options priced less than $0.125 and options with missing or anomalous data. Using daily closing prices for S&P 500 Index options and S&P 500 Index daily opening and closing levels from January 4, 1996 through September 10, 2008, along with contemporaneous firm and economic data used in robustness tests, they find that:
More…

Does the effectiveness of simple moving average (SMA) crossing signals vary with stock volatility? In the August 2011 update of their paper entitled “A New Anomaly: The Cross-Sectional Profitability of Technical Analysis”, Yufeng Han, Ke Yang and Guofu Zhou investigate the application of SMAs to portfolios of stocks sorted sorted based on realized volatility. Specifically, each year they sort stocks into deciles by volatility (standard deviation of daily returns over the past year). For each decile, they calculate a price index, an SMA for the index and daily returns based on initial equal weighting. When a decile portfolio is above (below) its SMA, they hold the portfolio (30-day Treasury bills), with a one-day delay for switches. They compare the returns for this timing strategy to buy-and-hold by decile. They focus on a 10-day SMA, but also test 20-day, 50-day, 100-day and 200-day SMAs. Using daily returns for a broad sample of U.S. stocks spanning 1963 through 2009, they find that: More…

Do aggregate corporate earnings predict bond market returns? In his January 2012 paper entitled “Aggregate Earnings and Corporate Bond Markets”, Xanthi Gkougkousi investigates the relationship between aggregate earnings and corporate bond market returns. Using quarterly aggregate earnings for a broad sample of U.S. stocks with fiscal years ending in March, June, September and December and total quarterly returns for ten U.S. corporate bond indexes during January 1973 through December 2010 (360,614 firm-quarter observations), he finds that: More…

Investor mood may affect financial markets. Sports may affect investor mood. The biggest mood-mover among sporting events in the U.S. is likely the National Football League’s Super Bowl. Is the week before the Super Bowl especially distracting and anxiety-producing? Is the week after the Super Bowl focusing and anxiety-relieving? Presumably, post-game elation and depression cancel between respective fan bases. Using past Super Bowl dates since inception and daily/weekly S&P 500 Index data for 1967-2011 (45 events), we find that: More…