A general parametric framework is developed for pricing S&P500 options. Skewness and leptokurtosis in stock returns as …

. For a nominal variable, the quality of a prediction is measured by the probability of error; for a numeric variable, it is …Statistics is commonly taught as a set of techniques to aid in decision making, by extracting information from data. It … establish a set of probability models which can be used to predict values of one or more variables. Such a model constitutes …

properties of test statistics for cointegration when the aggregate data consists of heterogeneous individuals. …

conditional residuals. When used together, these residuals allow identification of outliers, model mis-specification and mean …

assumed to be Gaussian, the resulting prediction distribution may have an infinite variance beyond a certain forecasting … approximation causes no serious problems for parameter estimation or for forecasting one or two steps ahead. However, for longer …-term forecasts the true prediction intervals become increasingly skewed, whereas those based on the Gaussian approximation may have a …

prediction intervals which incorporate an allowance for sampling error associated with parameter estimates. The effect of …The problem of constructing prediction intervals for linear time series (ARIMA) models is examined. The aim is to find …