Glen A. Larsen

Empirical Insights on Indexing

Winston-Salem (NC 27109). assive index funds that buy and hold the stocks in high-capitalization major market indexes like the Standard & Poor’s 500 stock index P have beaten the vast majority of actively run stock funds over the past few years. A glaring exception has been low-capitalization stock index funds. Passive index funds whose purpose is to match the performance of a small-stock benchmark, like the Russell 2000 index, have seen results that lag their actively managed small-stock fund peers. While Damato [1997] states that “overall, indexing has been a great mutual-fund investment strategy,” she quotes Vanguard Group president John J. Brennan as saying that Vanguard’s

The Optimal Construction of Internationally Diversified Equity Portfolios Hedged Against Exchange Rate Uncertainty

1.6 billion passive small-stock fund is “the one anomaly among Vanguard’s numerous index funds, where the performance hasn’t been nearly as good against the actively managed small-stock fund.” A cost-efficient approach to indexing involves purchasing a selected sample of securities in an index. Rudd [1980] describes an optimization technique for forming passive indexed portfolios using a sample of stocks. The aim of the technique is to minimize the residual risk of the indexed portfolio compared to the index that it is designed to match. Using the S&P 500 as the index, Rudd compares the tracking results of the optimization approach to a less sophisticated stratification or cell approach in forming an indexed portfolio. His results show a 50% improvement in trachng error risk of the optimized indexed portfolio over the stratified indexed portfolio.

Parameter Estimation Techniques, Optimization Frequency, and Portfolio Return Enhancement

Much of the empirical work on hedging exchange rate exposure in portfolios of financial assets has used a unitary hedge ratio, or a currency overlay. Alternatively, the currencies themselves can be treated as assets and the position in them optimized. This study empirically tests whether the ex post results of recent studies, which conclude that currencies should themselves be optimized, stand up under parameter uncertainty. It may very well be that ex ante, when parameter inputs must be estimated from historical data, the attempt to determine the optimal currency weights results in inferior performance in comparison to using a simple unitary hedging strategy, or even unhedged international investment. The results suggest that a local currency return unitary hedging strategy works best in the presence of parameter uncertainty.

Refining the bootstrap method of stochastic dominance analysis: The case of the January effect

Modern portfolio theory dictates that the lower the pairwise correlation between securities, the greater the potential for efficiency enhancement from ex ante optimization. When securities exhibit a high degree of pairwise correlation, ex ante optimization should provide less potential for efficiency enhancement. It is an empirical issue as to whether ex ante return estimation and optimization techniques can provide strict return enhancement in risk–return space. Strict return enhancement, without the use of leverage, may be possible if ex ante portfolio parameter estimation techniques allow securities with higher realized returns to carry greater weights in the ex ante optimal portfolio than in the benchmark portfolio. The authors of this article examine how various ex ante portfolio parameter estimation techniques and optimization/holding–period frequency intervals can enhance managed portfolio returns. Overall, the results suggest that it is possible to consistently achieve enhanced returns at much the same level of return per unit of risk as the benchmark portfolio.

An Optimization Strategy for Enhancing thePerformance of Fund-of-Funds Portfolios

This study investigates the effect of sample size and population distribution on the bootstrap estimated sampling distributions for stochastic dominance (SD) test statistics. Bootstrap critical values for Whitmores (1978) second- and third-degree stochastic dominance test statistics are found to vary with both data sample size and variance of the population distribution. The results indicate the parametric nature of the statistics and suggest that the bootstrap method should be used to estimate a sampling distribution each time a new data sample is drawn. As an application of the bootstrap method, the January small firm effect is examined. The results conflict with the SD results of others, and indicate that not all investors would prefer to hold just a portfolio of small capitalization firms in January.

Seasonality in firm-size portfolio returns: A nonparametric analysis

Previous research provides evidence that much of the crosssectional variation in equity returns can be explained by firm characteristics or sectors. One popular money management technique is to construct a portfolio (fund) using other managed portfolios (funds). The resulting overall portfolio is generally referred to as a fund-of-funds portfolio. This study by Larsen and Resnick demonstrates the potential for performance enhancement in a fund of funds when portfolio optimization techniques are employed on sector funds in order to construct the overall fund. Notably, ex ante optimization over sector funds that are constructed on the basis of market capitalization, price-to-earnings ratios, change in operating earnings, and book-to-market ratios demonstrates the potential for enhancing an overall equity fund performance relative to value-weighted and equal-weighted benchmark portfolios that are constructed from the population of stocks from which the sector portfolios are formed.

Enhancing the Returns of SRI Portfolios Using a Minimum Variance Small-Basket Strategy

In this study the author uses stochastic dominance, a nonparametric method of portfolio performance analysis, to test for seasonality in firm-size portfolio return behavior. Stochastic dominance confirms the January effect, found in previous parametric studies, only for the smallest firm-size portfolio. It statistically eliminates the size effect for the larger firm-size portfolios in January and for all firm-size portfolios in the other months of the year. It is demonstrated that a market proxy problem and normality assumption violation may bias the parametric results. Nonparametric analysis, therefore, suggests that markets may be more efficient than parametric methods imply when model violations exist.

Implications for Enhanced Portfolio Performance Based on the Information Content of Short Interest

The focus of this research is on enhancing the returns of socially responsible investment (SRI) portfolios by constructing minimum variance small-basket portfolios. The results suggest that individual investors and professional financial planners on behalf of their clients can realize enhanced performance relative to SRI funds that contain a large number of stocks by constructing minimum variance portfolios that generally contain fewer than 10 stocks. Over the 10-year period from 2002 through 2011, which is a function of the availability of SRI fund return data, the average annual excess returns for the minimum variance small-basket portfolios range from 2.59% to 6.99% relative to the larger SRI funds from which the small-basket funds are constructed. Measures of total risk and downside risk further support the enhanced performance of the minimum variance small-basket portfolio strategy. Perhaps most importantly, the minimum variance small-basket strategy that we describe can be easily implemented by individual investors or by professional financial planners on behalf of their clients.

Duration of share repurchase programs and firm performance

In this paper, we review the mean-variance portfolio theory literature that supports short selling as an active portfolio management tool and the empirical literature that provides evidence of active short sellers having superior information about overpriced securities. What may not be clear is exactly how that information can be detected and analyzed. We, therefore, review the theoretical and empirical literature that investigates the information content of short interest. Finally, we document several methods used by portfolio managers to target short sale candidates.

Market Timing Can Work in the Real World

It is widely known that under asymmetric information, share repurchasss can be used by firms to signal firm quality. In this paper, it is shown that the duration of share repurchase programs can signal the degree of firm quality. The model predicts that the highest quality firms repurchase a fraction of their shares outstanding over a short duration, medium quality firms repurchase the same fraction over a longer duration, and low quality firms do not repurchase shares at all. An empirical investigation of firms that engage in repurchase activity supports the model.