Modeling Financial Time Series withS-PLUS(Second Edition)

The Econometric Modelling of Financial Time Series Second edition

Modeling Financial Time Series With S - Plus

Econometric Modeling of Financial Time Series Volatility Using Software Packages

The article is devoted to the comparative analysis of software packages in financial time series modeling. The most common among economists packages R, Eviews and Gretl are considered. Volatility is often used as a rough approximation to measuring of overall risk financial instruments. Polish stock index WIG for the modeling of financial time series volatility was chosen. Econometric model of f...

Computational Intelligence Methods for Financial Time Series Modeling

In this paper, the combination of unsupervised clustering algorithms with feedforward neural networks in exchange rate time series forecasting is studied. Unsupervised clustering algorithms have the desirable property of deciding on the number of partitions required to accurately segment the input space during the clustering process, thus relieving the user from making this ad hoc choice. Combi...

Dynamical Products of Experts for Modeling Financial Time Series

Predicting the “Value at Risk” of a portfolio of stocks is of great significance in quantitative finance. We introduce a new class models, “dynamical products of experts” that treats the latent process over volatilities as an inverse Gamma process. We show that our multivariate volatility models significantly outperform all related Garch and stochastic volatility models which are in popular use...