We study optimal hedging design for returns on an Italian equity mutual fund index since 2008. Alternative hedging instruments include one-month futures contracts for FTSE-MIB, FTSE100 and Xetra DAX. We use bivariate models of our Italian equity mutual fund index and each hedging instrument to...

Some researchers, for example, Koop [1], and Sims [2], have advocated for Bayesian alternatives to unit-root testing over the classical approach using the augmented Dickey-Fuller test (ADF). This paper studies the power of what Koop [1] has called the Objectiveʺ Bayesian approach to unit-root...

This paper presents a study of Artificial Neural Network (ANN) and Bayesian Network (BN) for use in stock index prediction. The data from Nigerian Stock Exchange (NSE) market are applied as a case study. Based on the rescaled range analysis, the neural network was used to capture the...

This paper introduces a new parametric measure of productivity change using the hyperbolic distance function. More specifically, the paper first estimates a stochastic translog hyperbolic distance function, which satisfies regularity conditions, using the Bayesian approach. Then it derives an...

Using the maximum likelihood method, in order to estimate Half-Normal stochastic frontier production models, entails several practical di±culties that, perhaps, have not been su±ciently emphasised. In employing FRONTIER software, we analyse the case in which the estimation obtained suggests...

In this study, a vector autoregression (VAR) model with time-varying parameters (TVP) to predict the daily Indian rupee (INR)/US dollar (USD) exchange rates for the Indian economy is developed. The method is based on characterization of the TVP as an optimal control problem. The methodology is a...

This study examines the impact of volatility shifts on volatility persistence for three major sector indices of Istanbul Stock Exchange (ISE) and ISE National 100 index over the period beginning from 1997 and ending in 2009. The exponential generalized autoregressive conditional...

This paper develops a framework for evaluating the importance of the arrival of new information for forecasting, estimation, and decision making. By fusing known and recently developed statistical tests and concepts, the paper provides guidelines for detecting outliers, influential observations,...

Contemporary financial risk management is significantly based on the analysis of time series of returns. One of the most significant errors frequently committed by analysts is the predominant use of normal distributions when it is clear that the returns are not normal. Copula models and models...

Persistent current account deficits were observed in some developing countries that are received substantial foreign capital in the last decades. This has raised the issue of sustainability and increased the volume of studies about the measures of sustainable current account deficits in the...