Higher Sharpe Ratios Research Articles

Optimal Active Portfolio Management with Unconditional Mean-Variance Risk Preferences

We propose a comprehensive empirical strategy for optimizing the out-of-sample performance of sample mean-variance ecient portfolios. After constructing a sample objective function that accounts for the impact of estimation risk, specification errors, and transaction costs on portfolio performance, we maximize the function with respect to a set of tuning parameters to obtain plug-in estimates of the optimal portfolio weights. The methodology oers considerable flexibility in specifying objectives, constraints, and modeling techniques. Moreover, the resulting portfolios have well-behaved weights, reasonable turnover, and substantially higher Sharpe ratios and certainty-equivalent returns than benchmarks such as the 1/N portfolio and S&P 500 index.

Zero-R2 Hedge Funds and Market Neutrality

Factor models yield an R2 insignificantly different from zero for one-third of hedge funds in a broad sample. These funds illustrate the concept of market neutrality and feature lower volatilities, higher Sharpe ratios, and higher alphas than other funds, indicating they provide a successful alternative investment. However, large portfolios of zero-R2 funds contain fully half the volatility of portfolios of other funds, suggesting they feature substantial systematic risk. Furthermore, these funds display an increased probability of failure even after controlling for idiosyncratic volatility. These results indicate the presence of an omitted factor that exposes investors to significant downside risk.

Asset Prices and the Heterogeneous Impact of News

This paper analyzes a general equilibrium exchange economy with a continuum of agents who have catching up with the Joneses preferences and differ with respect to the curvature of their utility functions and - as a peculiarity - the impact of news about uncertainty. The dynamic redistribution of wealth among the agents generates endogenously the state-dependent preferences of the representative agent and the variation in the pricing kernel volatility, i.e. the price of risk. The model exhibits many of the empirically observed properties of the unconditional and conditional moments of stock returns. Indeed, the new source of heterogeneity has a strong impact on asset prices whereas heterogeneity in risk aversion has just a marginal effect once it is estimated from data. In particular the heterogeneous impact of news helps in explaining the equity premium and risk-free rate puzzles, the high and countercyclical Sharpe ratio, the long-horizon predictability of excess returns and the GARCH and leverage effects in return volatility.

Estimation Risk, Learning and the Equity Premium

We examine the effects of estimation risk and Bayesian learning on equilibrium asset prices when there is uncertainty about both the first and second moments of consumption and dividend growth rates. For the 1891-2007 period, our model generates a sizable average annual equity premium, relatively low average risk-free rate and a high mean Sharpe ratio that approximates the data average with (1) low risk aversion, (2) non-persistent (i.i.d.) growth rates, (3) power utility, (4) diffuse (or non-pessimistic) priors, and (5) finite posterior moments. Learning does not produce a monotonically declining equity premium and shocks to growth rates can induce sharp fluctuations in the market returns even after one hundred years of data. For reducing the discrepancy between the equilibrium outcomes and the data, variations in the prior estimation risk with respect to consumption --- but not dividend --- growth are at least as effective as variations in risk aversion, or in the inter-temporal elasticity of substitution, or in the persistence of growth rates.

Time-Change Risks and the Aggregate Stock Market Behavior

This paper investigates how the investors responses to the evolution of uncertainty affect equilibrium asset returns. I develop a discrete-time real endowment economy where the aggregate economic uncertainty, as detected by a time-change for the endowment process, alters the perceived utility from consumption and drives the state of the economy. The equilibrium pricing kernel reflects both the return on investments - a supply-side effect, as in the standard framework - and the agents' responses - a demand-side effect - which evolve with the arrival of news. Equilibria with both unpredictable and persistent impact of uncertainty are fully characterized: the pricing of supply-side and demand-side time-change risks is discussed. The model calibration shows that many features of financial returns are well described consistently with a low correlation of returns with consumption growth and a low and constant risk aversion. The model captures a high and countercyclical equity premium and Sharpe ratio, a high and clustered volatility, a rich time-variation of returns and a low and little volatile risk-free rate. I empirically verify the designed mechanism for intertemporal decisions by relating the model state-variable to the consumption-wealth ratio.

Limits to Arbitrage and Commodity Index Investment: Front-Running the Goldman Roll

This paper studies the unique rolling activity of commodity index in futures markets and shows that the resulting price impact is statistically and economically significant. Two trading strategies, devised to exploit this anomaly, yielded excess returns with positive skewness and Sharpe ratios as high as 4.39 from 2000 to March 2010. The profitability of the strategies is positively correlated with the net result of two opposite forces: the size of index investment and the amount of arbitrage capital employed. Due to the price impact, investors forwent 3.6\% annual return, 48\% higher Sharpe ratio, and billions of dollars over the period.

Do the Best Hedge Funds Hedge?

We provide a simple argument that suggests that better-informed hedge funds choose to have less exposure to factor risk. Consistent with this argument, we find that hedge funds that exhibit lower R-squareds with respect to systematic factors have higher Sharpe ratios, higher information ratios, and higher alphas. They also exhibit higher manipulation-proof performance measures and charge higher fees. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Portfolios Weighted by Repurchase and Total Payout

Portfolios weighted by fundamental measures of company size, such as assets, dividends, sales, earnings, and employees, have recently attracted a lot of attention. Pioneering research has showed that these fundamental value–weighted portfolios, especially dividend-weighted portfolios, can achieve better mean returns and better Sharpe ratios than could be attained with the traditional market value– weighted portfolio. In this article, the authors examine three portfolios weighted by the additional fundamental measures of firm size—share repurchases, total payout, and earnings retention—and find that the repurchase-weighted portfolios and total payout–weighted portfolios have higher excess returns and higher Sharpe ratios than the other fundamental value–weighted portfolios, including the dividend-weighted portfolio. The repurchase-weighted portfolio shows a positive and statistically significant alpha of 2.77% after controlling for the Fama–French factors (market, size, and book-to-market) and Carhart’s momentum variable. The total payout–weighted portfolio also has a positive and significant alpha, albeit smaller than that of the repurchase-weighted portfolio. <b>TOPICS:</b>Portfolio construction, security analysis and valuation

Illiquidity and Equilibrium Stock Returns

We consider an equilibrium in illiquid stock market in which liquidity suppliers trade with investors and face significant trading costs. A similar situation was observed during the recent financial crisis. We find that the expected risk premium on the stock and its Sharpe ratio are positive and very large, while the expected stock return volatility is a few times bigger than in the liquid market. Investors sell stock shares due to their excessive leverage, whereas market makers try to compensate their trading costs with the profits expected from buying the stock shares with very high Sharpe ratio. Moreover, the short-term stock returns exhibit either a strong overreaction or a momentum effect depending on the state of the economy.

Cross-Region, Cross-Sector Asset Allocation with Regimes

Cross-region and cross-sector asset allocation decisions are one of the most fundamental issues in international equity portfolio management. Equity returns exhibit higher volatilities and correlations, and lower expected returns, in bear markets compared to bull markets. However, static mean-variance analysis fails to capture this salient feature of equity returns. Using a regime switching model across both regions and sectors, the regime-dependent asset allocation substantially outperforms the static mean-variance allocation. This outperformance is robust to various asset allocation constraints. In addition, optimal allocation across sectors provide greater benefits compared to international diversification, which is characterized by higher returns, lower risks, lower correlations with the world market and a higher Sharpe ratio.

A Note on Sparse Minimum Variance Portfolios and Coordinate-Wise Descent Algorithms

A fast method based on coordinate-wise descent algorithms is developed to solve portfolio optimization problems in which asset weights are constrained by Lq norms for 1<=q<=2. The method is first applied to solve a minimum variance portfolio (mvp) optimization problem in which asset weights are constrained by a weighted L1 norm and a squared L2 norm. Performances of the weighted norm penalized mvp are examined with two benchmark data sets. When the sample size is not large in comparison with the number of assets, the weighted norm penalized mvp tends to have a lower out-of-sample portfolio variance, lower turnover rate, fewer numbers of active constituents and shortsale positions, but higher Sharpe ratio than the one without such penalty. Several extensions of the proposed method are illustrated; in particular, an efficient algorithm for solving a portfolio optimization problem in which assets are allowed to be chosen grouply is derived.

Alternative Objective Functions for Quasi-Shrinkage Portfolio Optimization

In this paper we propose a quasi-shrinkage approach for minimum-variance portfolios which does not use a quadratic loss function to derive the optimal shrinkage intensity. We develop two alternative objective functions for linear shrinkage. The first targets the reduction of portfolio variance. The second incorporates returns of assets to improve portfolio performance with respect to mean and variance. We compare the out-of-sample performance of our proposed portfolios to nine benchmark strategies across seven data sets. Our strategies often have lower portfolio variance and higher Sharpe ratios than the benchmark strategies. In particular, we beat the naive portfolio empirically on all seven and significantly on three data sets.

Are Carry Trade Risks Systematic Risks Now? An Analysis of the Dynamics of Carry Trade Risks

In this paper, I study individual currency pairs and examine the behavior of the cross section of their carry returns with the USD. Developed and emerging market carry trades yield high Sharpe ratios even after adjusting for transaction costs. I show that carry trade risks carry trade risks are dynamic and have become more systematic in recent years. From 1999 onwards, the high carry return currencies have significant coefficients in a time series regression of returns on the US stock market returns, implied volatility innovations of the US stock market options (VIX), TED spreads. In addition to the time series factor loadings, I find that the cross section of carry trade returns can be sorted by betas on the any of these variables - US stock market, VIX innovations and TED spreads. I also document the increasing role of inflation growth in the cross section of currency returns and the increase in carry returns due to the presence of differentially inflation targeting central banks. I find that in both periods, the more negatively a central banks Taylor rule beta with respect to the US central bank is, the higher the return that currency pair achieves. I analyze how this observation may help make hedge funds and investors investing in other countries endogenous in theoretical models.

Systematic Funds Outperform Discretionary Funds

This article compares the performance of systematic and discretionary hedge funds. In systematic funds, most trades are originated and executed by computer programs written for that purpose. In discretionary funds, human traders make decisions when to buy and sell which financial securities. The analysis herein shows that systematic funds consistently outperform discretionary funds when performance is measured by Jensen’s Alpha. Systematic funds also exhibit lower correlation with the S&P 500 index and produce higher cumulative returns since inception, although with higher volatility.On the basis of absolute monthly returns, systematic hedge funds outperform discretionary hedge funds whenever markets are falling. When markets are rising, however, discretionary funds tend to deliver higher absolute returns than do systematic funds. On the absolute return basis, the difference between systematic and nonsystematic funds cannot be explained by liquidity considerations: both systematic and discretionary funds deliver comparable returns in both liquid and illiquid markets.Across a variety of other metrics, however, systematic funds perform much better than discretionary funds in limited liquidity across a variety of metrics: systematic funds produce less extreme drawdowns, higher Sharpe ratios, higher Jensen’s alpha, and attract higher Assets Under Management (AUM).Finally, systematic funds exhibit lower skewness and kurtosis than do discretionary funds. When adjusted for skewness and kurtosis, systematic returns are statistically indistinguishable from discretionary returns, suggesting that much of systematic funds’ outperformance comes from better ability to manage extreme events, performing better than discretionary funds in crisis conditions.

An examination of HMM-based investment strategies for asset allocation

We develop and analyse investment strategies relying on hidden Markov model approaches. In particular, we use filtering techniques to aid an investor in his decision to allocate all of his investment fund to either growth or value stocks at a given time. As this allows the investor to switch between growth and value stocks, we call this first strategy a switching investment strategy. This switching strategy is compared with the strategies of purely investing in growth or value stocks by tracking the quarterly terminal wealth of a hypothetical portfolio for each strategy. Using the data sets on Russell 3000 growth index and Russell 3000 value index compiled by Russell Investment Services for the period 1995–2008, we find that the overall risk-adjusted performance of the switching strategy is better than that of solely investing in either one of the indices. We also consider a second strategy referred to as a mixed investment strategy which enables the investor to allocate an optimal proportion of his investment between growth and value stocks given a level of risk aversion. Numerical demonstrations are provided using the same data sets on Russell 3000 growth and value indices. The switching investment strategy yields the best or second best Sharpe ratio as compared with those obtained from the pure index strategies and mixed strategy in 14 intervals. The performance of the mixed investment strategy under the HMM setting is also compared with that of the classical mean–variance approach. To make the comparison valid, we choose the same level of risk aversion for each set-up. Our findings show that the mixed investment strategy within the HMM framework gives higher Sharpe ratios in 5 intervals of the time series than that given by the standard mean–variance approach. The calculated weights through time from the strategy incorporating the HMM set-up are more stable. A simulation analysis further shows a higher performance stability of the HMM strategies compared with the pure strategies and the mean–variance strategy. Copyright © 2009 John Wiley & Sons, Ltd.

A stochastic dominance analysis of yen carry trades

Yen carry trades have made headline news for over a decade. We examine the profitability of such trades for the period 2001–2009. Yen carry trades generated high mean returns and Sharpe ratios prior to the recent financial crisis. They continued to outperform major stock markets for the full sample period. Given the non-normality of carry trade returns, we apply non-parametric tests based on stochastic dominance (SD) to evaluate whether the high returns of yen carry trades are compatible with risk as reflected in returns on US and global stock market indices. We apply a general test for SD developed recently by Linton, Maasoumi and Whang (2005) to six currencies as well as portfolios of these currencies. For a large class of risk-averse investors, profits from yen carry trades cannot be attributed to risks.

Range-Based Covariance Estimation Using High-Frequency Data: The Realized Co-Range

textabstractWe introduce the realized co-range, utilizing intraday high-low price ranges to estimate asset return covariances. Using simulations we find that for plausible levels of bid-ask bounce and infrequent and non-synchronous trading the realized co-range improves upon the realized covariance, which uses cross-products of intraday returns. One advantage of the co-range is that in an ideal world it is five times more efficient than the realized covariance when sampling at the same frequency. The second advantage is that the upward bias due to bid-ask bounce and the downward bias due to infrequent and non-synchronous trading partially offset each other. In a volatility timing strategy for S\\&P500, bond and gold futures we find that the co-range estimates are less noisy as exemplified by lower transaction costs and also higher Sharpe ratios when using more weight on recent data for predicting covariances.

Understanding Index Option Returns

This paper studies the returns from investing in index options. Previous research documents significant average option returns, large CAPM alphas, and high Sharpe ratios, and concludes that put options are mispriced. We propose an alternative approach to evaluate the significance of option returns and obtain different conclusions. Instead of using these statistical metrics, we compare historical option returns to those generated by commonly used option pricing models. We find that the most puzzling finding in the existing literature, the large returns to writing out-of-themoney puts, is not even inconsistent with the Black-Scholes model. Moreover, simple stochastic volatility models with no risk premia generate put returns across all strikes that are not inconsistent with the observed data. At-the-money straddle returns are more challenging to understand, and we find that these returns are not inconsistent with explanations such as jump risk premia, Peso problems, and estimation risk.

A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms

We provide a general framework for finding portfolios that perform well out-of-sample in the presence of estimation error. This framework relies on solving the traditional minimum-variance problem but subject to the additional constraint that the norm of the portfolio-weight vector be smaller than a given threshold. We show that our framework nests as special cases the shrinkage approaches of Jagannathan and Ma (Jagannathan, R., T. Ma. 2003. Risk reduction in large portfolios: Why imposing the wrong constraints helps. J. Finance 58 1651–1684) and Ledoit and Wolf (Ledoit, O., M. Wolf. 2003. Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. J. Empirical Finance 10 603–621, and Ledoit, O., M. Wolf. 2004. A well-conditioned estimator for large-dimensional covariance matrices. J. Multivariate Anal. 88 365–411) and the 1/N portfolio studied in DeMiguel et al. (DeMiguel, V., L. Garlappi, R. Uppal. 2009. Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy? Rev. Financial Stud. 22 1915–1953). We also use our framework to propose several new portfolio strategies. For the proposed portfolios, we provide a moment-shrinkage interpretation and a Bayesian interpretation where the investor has a prior belief on portfolio weights rather than on moments of asset returns. Finally, we compare empirically the out-of-sample performance of the new portfolios we propose to 10 strategies in the literature across five data sets. We find that the norm-constrained portfolios often have a higher Sharpe ratio than the portfolio strategies in Jagannathan and Ma (2003), Ledoit and Wolf (2003, 2004), the 1/N portfolio, and other strategies in the literature, such as factor portfolios.

Portfolios Weighted by Repurchase and Total Payout

This paper examines three portfolios weighted by fundamental measures of firm size: share repurchases, total payout, and earnings retention. We find that the repurchase weighted and the total payout weighted portfolios have higher excess returns and higher Sharpe ratios than the most common fundamental weighted portfolio (namely, the dividend weighted portfolio). The repurchase weighted portfolio shows a positive and statistically significant alpha of 2.77% after controlling for the Fama-French factors (of market, size, book-to-market), and Carhart's momentum variable. The total payout weighted portfolio also has a positive and significant alpha, albeit smaller than that of the repurchase weighted portfolio.