The Dynamic Conditional Correlation model of Engle has made the estimation of multivariate GARCH models feasible for reasonably big vectors of securities’ returns. In the present paper we show how Engle’s twosteps estimate of the model can be easily extended to elliptical conditional...

This paper tests a partially Segmented ICAPM using an asymmetric multivariate GARCH specification for two developed markets, two emerging markets and World market. We find that this asymmetric process provides a significantly better fit of the data than a standard symmetric process. The evidence...

The classical Quadratic Programming (QP) formulation of the well-known portfolio selection problem has traditionally been regarded as cumbersome and time consuming. This paper formulates two additional models, (i) maximin, and (ii) minimization of mean absolute deviation. Data from 67 securities...

Based on the Partial Distribution (Feng Dai, 2001), a new model to price an asset (MPA) is given. Going a step further, this paper puts forward the Multivariate Partial Distribution (MPD) for the first time. By use of MPD, we could gain a new kind of model for pricing the group assets (MPGA), in...

This paper was prepared for the purpose of presenting the methodology and uses of the Monte Carlo simulation technique as applied in the evaluation of investment projects to analyse and assess risk. The first part of the paper highlights the importance of risk analysis in investment appraisal....

This study examines the forecastability of ASEAN-5 stock market returns using linear and non-linear time series models. Time series models with GARCH errors are also considered. Based on formal econometrics tests, this study shows that the behaviour of these returns do not follow random walk...

This paper gives an overview of some issues related to market aluation, focusing on the developments on the New York equity markets. The 42.4 p.c. fall in the S&P 500 price index between 24 March 2000 - when it reached its all-time high - and 31 December 2002 is situated in a very long term...

The aim of this paper is to develop and apply Neural Network (NN) models in order to forecast regional employment patterns in Germany. NNs are statistical tools based on learning algorithms with a distribution over a large amount of quantitative data. NNs are increasingly deployed in the social...