The present paper investigates the performance of open-ended, growth-oriented equity schemes for the period from April 2011 to March 2015 of transition economy. Daily closing NAV of different schemes have been used to calculate the returns from the fund schemes. BSE-sensex has been used for market portfolio. The historical performance of the selected schemes were evaluated on the basis of Sharp...

Artificial neural networks are used in conjunction with the Sharpe-Linter form of the Capital Asset Pricing Method (CAPM) to predict when the returns on U.S. stocks will be greater than financial risk models would predict. The advantage of using a nonlinear approach is to model the financial system more accurately than linear techniques. The Sharpe-Lintner form is used to control for risk and d...

In this thesis we will use Random Forests to define a trading strategy. Using this powerful machine learning technique, we will try to predict the daily price changes of financial products that move similarly over the long term, so-called cointegrated pairs. We propose a way to adjust our portfolio based on these prediction, while limiting our risk. Firstly, we test our strategy on data generat...

The objective of this work was to evaluate which nonlinear model [Davidson (1942, 1944), Stinner et al. (1974), Sharpe & DeMichele (1977), and Lactin et al. (1995)] best describes the relationship between developmental rates of the different instars and stages of Alabama argillacea (Hübner) (Lepidoptera: Noctuidae), and temperature. A. argillacea larvae were fed with cotton leaves (Gossypium hi...

We explore implications of the rational theory of momentum and reversal in Vayanos and Woolley (2011) for empirical work and portfolio management. We compute closed-form Sharpe ratios of various implementations of momentum and value strategies, of combinations of these strategies, and for general investment horizons. For plausible parameter values, the correlation between momentum and value ret...

We use a log-normal framework to examine the effect of preferences on the market price for risk, that is, the Sharpe ratio. In our framework, the Sharpe ratio can be calculated directly from the elasticity of the stochastic discount factor with respect to consumption innovations as well as the volatility of consumption innovations. This can be understood as an analytical shortcut to the calcula...

If we exclude the assumption of normality in return distributions, the classical risk–reward Sharpe Ratio becomes a questionable tool for ranking risky projects. In line with Sharpe thinking, a general risk–reward ratio suitable to compare skewed returns with respect to a benchmark is introduced. The index includes asymmetrical information on: (1) ‘‘good’’ volatility (above the benchmark) and ‘...

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 calculate the partition function of partially quenched chiral perturbation theory in the epsilon regime at next-to-leading order using the supersymmetry formulation developed by Sharpe and Shoresh. We include a nonzero imaginary chemical potential and show that the finite-volume corrections to the low-energy constants Σ and F for the partially quenched partition function, and hence for spect...

This paper examines the impact of hedge fund redemption restrictions such as lockup period, notice period, and redemption period on fund flow, risk, and performance. We first examine the effects of redemption restrictions conditional on past poor performance. We then examine the differential impact of redemption restrictions under different market conditions. We find that during normal periods,...