In this paper, several identities concerning expectation, variance, covariance, cumulative distribution functions, the coefficient of variation, and the Lorenz curve are obtained and they are used in establishing theoretical results. Furthermore, a graphical representation of the variance is...

The purpose of our present study is to strike out suitable models to explain the growth pattern and to forecast for urban population in SAARC countries. Using the data from UNPD for the years 1950 to 2000 in five years interval, we fitted both exponential and ARMA models. We found the...

This study investigates models for overnight interest rate volatility in Turkey and USA using the Asymmetric GARCH models and determines the best forecasting volatility models. These models are then completed with the use of out of sample forecasting. The best forecasting volatility models were...

Community-Based Health Insurance (CBHI) is an emerging concept for providing financial protection against the cost of illness and improving access to quality health services for low-income rural households who are excluded from formal insurance. CBHI is currently being provided in some rural...

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...

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...

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...