Research

 

Published Papers

 

 

Working Papers

 

Abstract: We compare the performance of equal-, value-, and price-weighted portfolios of stocks in the major U.S. equity indices over the last four decades. We find that the equal-weighted portfolio with monthly rebalancing outperforms the value- and price-weighted portfolios in terms of total mean return, four factor alpha, Sharpe ratio, and certainty-equivalent return, even though the equal-weighted portfolio has greater portfolio risk. The total return of the equal-weighted portfolio exceeds that of the value- and price-weighted because the equal-weighted portfolio has both a higher return for bearing systematic risk and a higher alpha when using the four-factor model. The nonparametric test of Patton and Timmermann (2009) indicates that the differences in the total return of the equal-weighted portfolio and the value- and price-weighted portfolios is monotonically related to size, price, liquidity and idiosyncratic volatility; the relation with reversal is not monotonic, although the equal-weighted portfolio strongly outperforms the value- and price-weighted portfolios for the deciles with the lowest and the highest reversal characteristic. The higher systematic return of the equal-weighted portfolio arises from its higher exposure to the market, size, and value factors. The higher alpha of the equal-weighted portfolio arises from the monthly rebalancing required to maintain equal weights, which is implicitly a contrarian strategy that exploits reversal; thus, alpha depends only on the rebalancing frequency and not on the choice of initial weights.

Abstract: Our objective in this paper is to examine whether one can use option-implied information to improve the selection of portfolios with a large number of stocks, and to document which aspects of option-implied information are most useful for improving their out-of-sample performance. Portfolio performance is measured in terms of four metrics: volatility, Sharpe ratio, certainty-equivalent return, and turnover. Our empirical evidence shows that, while using option-implied volatility and correlation does not improve significantly the portfolio volatility, Sharpe ratio, and certainty-equivalent return, exploiting information contained in the volatility risk premium and option-implied skewness increases substantially both the Sharpe ratio and certainty-equivalent return, although this is accompanied by higher turnover. And, the volatility risk premium and option-implied skewness help improve not just the performance of mean-variance portfolios, but also the performance of parametric portfolios developed in Brandt, Santa-Clara and Valkanov (2009).

 Abstract: We propose a new method of using option-implied information to construct heterogeneous implied correlations (HETIC) for all stock pairs and stock-factor combinations. We use implied correlations in computing forward-looking betas for arbitrary factors, which is not possible with the other option-implied methods for finding betas. Computed under the risk-neutral measure, our market betas on average do not suffer from the bias induced by the volatility and correlation risk premiums. For the S&P500 stocks in 1996--2009, HETIC betas outperform other historical and option-implied methods in predicting the realized betas in terms of average and number of best MSE and R2. In market-neutral pairs trading and in portfolio exposure targeting applications, our betas outperform the others in terms of deviation from the target exposure. HETIC market betas clearly confirm the existence of a positive risk-return relation that incorrectly may be put in doubt if one uses daily betas.

 Abstract: Using data on all U.S. exchange-traded individual stock options, we show that the currently observed option-implied ex ante skewness is positively related to future stock returns. This contrasts with the existing evidence that uses historical stock or option data to estimate skewness and finds a negative skewness-return relation. We compute the ex ante skewness using the model-free implied skewness (MFIS) as in Bakshi, Kapadia, and Madan (2003) and show that high MFIS stocks outperform low MFIS stocks by 45 basis points per month after correcting for systematic exposure. We find that the positive MFIS-return relation stems from the ability of the current MFIS to identify the deviation of a firm’s value from its fundamental value, and the most overvalued stocks have the most negative ex ante skewness. We further find that the speed of the value correction process depends on the arbitrage risk faced by arbitrageurs trying to exploit the observed inefficiencies. Our results have implications for the segmentation of equity and options markets as well as for limits of arbitrage in equity markets.