We analyze the performance of RiskMetrics, a widely used methodology for measuring market risk. Based on the assumption of normally distributed returns, the RiskMetrics model completely ignores the presence of fat tails in the distribution function, which is an important feature of financial data. Nevertheless, it was commonly found that RiskMetrics performs satisfactorily well, and therefore t...

This work describes applications of probability and statistics in RiskMetrics TM , J P Morgan's methodology for quantifying market risk. The methodology implements an analytical approach to nancial risk in trading, arbitrage, and investment based on the statistics of market moves in equities, bonds, currencies and commodities. The public unveiling of RiskMetrics TM in October of 1994 attracted ...

The objective of this study is to investigate the predictability of model based forecasts and the VIX index on forecasting future volatility of S&P 500 index daily returns. The study period is from January 1990 to December 2010, including 5291 observations. A variety of time series models were estimated, including random walk model, GARCH (1,1), GJR(1,1) and EGARCH (1,1) models. The study resul...

We develop a model based on the theory of incomplete contracts for how ownership structure of interorganizational systems (IOS) can affect information exploitation and IT adoption. Our model yields several propositions that suggest the appropriate strategic actions that a firm may take when there is potential for IOS adopters to question whether adopting the IOS will be value maximizing. We ana...

In this paper we present a new type of multivariate GARCH model which we call the composed MGARCH and factor composed MGARCH models. We show sufficient conditions for the covariance stationarity of these processes and proof of the invariance of the models under linear combinations, an important property for factor modeling. Furthermore, we introduce an α-stable version of these models and fit a...

This paper proposes a new model for calculating VaR where the user is free to choose any probability distributions for daily changes in the market variables and parameters of the probability distributions are subject to updating schemes such as GARCH. Transformations of the probability distributions are assumed to be multivariate normal. The model is appealing in that the calculation of VaR is ...