Fund managers highly prioritize selecting portfolios with a high Sharpe ratio. Traditionally, this task can be achieved by revising the objective function of the Markowitz mean-variance portfolio model and then resolving quadratic programming problems to obtain the maximum Sharpe ratio portfolio. This study presents a closed-form solution for the optimal Sharpe ratio portfolio by applying Cauch...

While many trading strategies are based on price prediction, traders in financial markets are typically interested in optimizing risk-adjusted performance such as the Sharpe Ratio, rather than the price predictions themselves. This paper introduces an approach which generates a nonlinear strategy that explicitly maximizes the Sharpe Ratio. It is expressed as a neural network model whose output ...

Performance measures such as the Sharpe ratio and the information ratio are estimation subject to estimation error. Lo (2002) derives the explicit expressions for the statistical distribution of the Sharpe ratio. Bertrand and Protopopescu (2007) have extended his work to the bivariate case which corresponds to the Information ratio. In the present paper, we analyze the effects of skewness and k...

We analyze the risk characteristics and the valuation of assets in an economy in which the investment opportunity set is described by the real interest rate and the maximum Sharpe ratio. It is shown that, holding constant the beta of the underlying cash flow, the beta of a security is a function of the maturity of the cash flow. For parameter values estimated from U.S. data, the security beta i...

We analyze the risk characteristics and the valuation of assets in an economy in which the investment opportunity set is described by the real interest rate and the maximum Sharpe ratio. It is shown that, holding constant the beta of the underlying cash flow, the beta of a security is a function of the maturity of the cash flow. For parameter values estimated from U.S. data, the security beta i...

We propose to train trading systems and portfolios by optimizing objective functions that directly measure trading and investment performance. Rather than basing a trading system on forecasts or training via a supervised learning algorithm using labelled trading data, we train our systems using recurrent reinforcement learning (RRL) algorithms. The performance functions that we consider for rei...

30 English translation © 2006 M.E. Sharpe, Inc., from the Russian text “‘Edinitsy’ i urovni deiatel’nosti,” in Iazyk i rechevaia deiatel’nost’ v obshchei i pedagogicheskoi psikhologii (Moscow and Voronezh: IPO MODEK, 2001), pp. 66– 82. Published with the permission of Dmitry A. Leontiev. Translated by Nora Favorov. Journal of Russian and East European Psychology, vol. 44, no. 3, May–June 2006, ...