David A. Louton

Diversification in Portfolios of Individual Stocks: 100 Stocks are Not Enough

We examine returns and ending wealth in portfolios selected from 1,000 large U.S. stocks over a 20-year holding period. Shortfall risk, the possibility of ending wealth being below a target, is a useful metric for long horizon investors and is consistent with the Safety First criterion. Density functions obtained from simulations illustrate that shortfall risk reduction continues as portfolio size is increased, even above 100 stocks. A slightly lower risk can be achieved in small portfolios by diversifying across industries, but a greater reduction is obtained by simply increasing the number of stocks.

A threshold autoregressive analysis of stock returns and real economic activity

Abstract We find evidence of a pronounced threshold-type asymmetry in the relation between stock returns and real economic activity. Negative stock returns are followed by sharp decreases in industrial production growth rates, while only slight increases in real activity follow positive stock returns. These findings are consistent with the recent empirical macroeconomics literature on business cycle asymmetry.

Business cycle asymmetry and the stock market

We present and estimate models of an asymmetric relationship between CRSP stock index returns and the U.S. unemployment rate. Based on the Akaike Information Criterion, conventional linear time series models are improved by allowing asymmetric responses. Our results show that negative stock returns are quickly followed by sharp increases in unemployment, while more gradual unemployment declines follow positive stock returns. According to our forecasting model, the unemployment rate rises by 1.12 percentage points during the 12 months after a 10 percent stock decline. Because macroeconomics forecasters have been unable to reliably predict downturns, these findings may provide a useful contribution.

Evidence of psychological barriers in the conditional moments of major world stock indices

Abstract This study investigates the existence of psychological barriers in the Dow Jones Industrial Average, the S&P 500, and six foreign stock indices. It is believed by many in the investment community that index levels that are multiples of 100 serve as barriers, and that markets may resist crossing these barriers. Although return dynamics in the neighborhood of barrier points are not identical for all series studied, we find aberrations in the conditional means and variances consistent with psychological barriers. In five of the eight indices studied, conditional mean returns are significantly higher after crossing a barrier as part of an upward move, while only two series exhibit significant mean effects after crossing a barrier as part of a downward move. In seven of the eight series studied, we find significant conditional variance effects coincident with a barrier crossing. In addition, most series exhibit evidence of autoregressive conditional heteroskedastic (ARCH), generalized ARCH (GARCH), and leverage effects.

The rise and fall of the "Dogs of the Dow"

Abstract The Dow Dividend Strategy recommends the highest-yielding stocks from the 30 Dow Industrials. These stocks have come to be known as the “Dogs of the Dow” since they often include some of the previous year’s worst performers. While the strategy’s successes—and more recently, its failures—have been well documented in the popular press, there have not been any convincing explanations of why the strategy worked. This paper demonstrates that the behavior of these stocks is consistent with the market overreaction hypothesis. In years before the stock market crash of 1987, the dogs were indeed “losers” which went on to become “winners.” But in the post-crash period, the high-yield stocks actually outperformed the market during the previous year. The Dow Dividend Strategy is no longer selecting the true dogs.

How Many Mutual Funds Are Needed to Form a Well- Diversified Asset Allocated Portfolio?

Funds of funds, which have become a popular investment vehicle in recent years, diversify across asset classes as well as managers with different styles and expertise. Lifecycle funds are a good example of funds of funds where investors can invest in a group of asset classes in different proportions depending on their investment horizon, risk tolerance, and objectives. Given that the number of mutual funds in the portfolios of lifecycle funds offered by different investment companies varies significantly even for those with similar targets, it is important to investigate the relationship between the number of mutual funds in an asset allocated portfolio and the resulting diversification benefits. As investors in lifecycle funds are concerned with the level of wealth they will have accumulated as of a target date, the variability of terminal wealth at the end of a given holding period is a relevant measure of risk for their portfolios. In this article the authors use a survivorship-bias-free sample to assess the impact of the number of mutual funds in an asset allocated portfolio on the variability and shortfall risk of its terminal wealth. Specifically, they run simulations to generate a large number of terminal wealth level outcomes for a portfolio with a given number of funds. Then, they obtain the frequency distribution of the terminal wealth outcomes, and use its dispersion as the risk measure in the analysis. The findings for three asset allocation scenarios, which are reported for 5-year and 10-year investment horizons, indicate that holding 10 to 12 funds in the portfolio instead of the minimum possible 2 funds as dictated by the asset allocation to equity and bonds reduces the standard deviation of terminal wealth by about 60%. This reduction can be obtained without sacrificing expected terminal wealth levels, and hence without a reduction in total returns. Similarly, the mean shortfall of terminal wealth and the semivariance of terminal wealth are reduced by 60% and 85%, respectively.

Performance Implications of Holding Multiple Mutual Funds with the Same Investment Objective

In this study we investigate the potential benefits of holding multiple mutual funds with the same fund objective. Given that a typical investors asset allocation may involve multiple asset classes, we report results for an array of mutual fund types including aggressive growth, international equity, high quality bond, balanced, and tax-free money market funds. We measure the impact of holding multiple funds with the same investment objective on the standard deviation, mean shortfall, and semivariance of terminal wealth. Our results, which are reported for 5-year, 7-year, and 10-year holding periods, indicate that, with the exception of money market funds, it takes 5 to 6 mutual funds to reduce the variability of terminal wealth significantly regardless of fund objective. The finding for aggressive growth mutual funds is robust to controls for style differences. In other words, it still takes 5 to 6 mutual funds to diversify manager risk when we classify aggressive growth funds into small, large, value, and growth style groups. We find that the standard deviation of terminal wealth and the shortfall risk of holding a tax-free money market fund are very small in relation to the expected terminal wealth level. Thus, diversification is not a particularly relevant concern for this asset class. We also investigate how the performance of a portfolio of multiple funds in a given asset class compares with that of the benchmark portfolio for the asset class. We show that during our sample period of 1993-2002 on average aggressive growth and high quality bond funds underperform their benchmark market indices, and that holding multiple mutual funds with the same objective does not mitigate this underperformance problem. An important contribution of our study is its use of a sample that is free of survivorship bias.

Competition and Innovation in Option-Market Models

The equity options market has shown rapid growth and the competition among different options exchanges and trading platforms has intensified in recent years. As growth and competition in the U.S. options market continues, it becomes increasingly important for market participants to evaluate market quality in different options trading venues. A sound comparison of market quality among the competing trading markets requires a clear understanding of their specific market structures, since each venue attempts to differentiate itself with a unique value proposition. This article provides a review of the market microstructures of the major options exchanges and trading platforms in the United States. Using a sample period around the entry of the NASDAQ Options Market and the BATS Options Exchange, it analyzes the competition for trading volume in the options industry, investigates the characteristics of trades and execution costs in the major options exchanges and trading platforms, and examines the determinants of execution location for trades. It shows that during the first three months of their operations, the NASDAQ Options Market and BATS Options Exchange do not make a big impact on the trading volumes of the other options exchanges. It also finds that the NASDAQ Options Market has the smallest quoted spread and effective spread values for equity options among the seven exchanges during the first three months of its market entry. The BATS Options Exchange shows lower average trade size and average dollar trade size, and does not demonstrate competitive execution quality indicators or competitive execution costs in the earlier months of its operation. A probit analysis confirms that in spite of the increasingly complex and nuanced nature of options exchange competition, the main factors determining execution location for new market entrants are: i) posting quotes at the NBBO; and ii) being alone at the NBBO.