This paper examines some performance measures to be considered as an alternative of the Sharpe Ratio. More specifically, we analyze allocation problems taking into consideration portfolio selection models based on different performance ratios. For each allocation problem, we compare the maximum expected utility observing all the portfolio selection approaches proposed here. We also discuss an e...

The Sharpe ratio function is a commonly used risk/return measure in financial econometrics. To estimate this function, most existing methods take two-step procedure that first estimates the mean and volatility functions separately then applies plug-in method. In paper, we propose direct method via local maximum likelihood to simultaneously negative log-volatility as well their derivatives. We e...

Data Envelopment Analysis (DEA) has been long employed as a popular methodology to evaluate the performance of various production activities with multiple inputs and outputs. However, an important issue is that the production process in the real world inevitably generates undesirable outputs (like wastes and pollutants) along with desirable outputs. Therefore, the undesirable outputs should be ...

The building blocks of the Sharpe ratio—expected returns and volatilities— are unknown quantities that must be estimated statistically and are, therefore, subject to estimation error. This raises the natural question: How accurately are Sharpe ratios measured? To address this question, I derive explicit expressions for the statistical distribution of the Sharpe ratio using standard asymptotic t...

In this paper, we used several elaborate return-to-risk methods to investigate the risk-adjusted performances of five soft commodities. Regarding only level risk, found that cocoa had highest risk losses, followed by orange juice. Cotton and coffee lowest losses. However, according output, cotton was worst asset in which invest because it negative average returns. contradistinction, sugar a rel...

We develop a method for pricing counterparty risk by using good deal bounds. The method imposes a new restriction in the arbitrage free model by setting upper bounds on the Sharpe ratios of the assets. The potential prices which are eliminated represent unreasonably good deals. The constraint on the Sharpe ratio translates into a constraint on the stochastic discount factor. Thus, one can obtai...

We propose to train trading systems by optimizing financial objective functions via reinforcement learning. The performance functions that we consider as value functions are profit or wealth, the Sharpe ratio and our recently proposed differential Sharpe ratio for online learning. In Moody & Wu (1997), we presented empirical results in controlled experiments that demonstrated the advantages of ...

We propose to train trading systems by optimizing financial objective functions via reinforcement learning. The performance functions that we consider are profit or wealth, the Sharpe ratio and our recently proposed differential Sharpe ratio for online learning. In Moody & Wu (1997), we presented empirical results that demonstrate the advantages of reinforcement learning relative to supervised ...