In this article, we are investigating the effects of returns and expenses of hedge funds in terms of natural logarithmic monthly returns and expenses in terms of fees of long/short equity and arbitrage hedge funds. We have applied a Vector Error Correction model, (VEC) and a Granger causality to...

Using a value at risk methodology, VaR, we demonstrate the extent to which the mean-variance approach underestimates the tail risk of the probability distribution. We compare the long and short - run performance returns after fees deduction with the expected losses that are recorded at...

In this article, we have tested a linear Gaussian state space model and the kalman filter in testing ARMA(2,3) models of the natural logarithmic monthly market returns of the US 1838 bond debenture closed-end fund. The aim is to estimate expectations that arises from the interaction of...

Autoregressive Conditional Heteroskedastic models (ARCH), and Generalized Autoregressive Conditional Heteroskedastic models, (GARCH) take into account the non-linearity that arises in the financial time series. Well known anomalies such as the calendar effects, January effect and seasonality's...