StMAR Toolbox: A MATLAB Toolbox for Student's t Mixture Autoregressive Models

18 Pages Posted: 31 Aug 2018

See all articles by Mika Meitz

Mika Meitz

University of Helsinki - Department of Political and Economic Studies

Daniel P. A. Preve

Singapore Management University

Pentti Saikkonen

University of Helsinki - Department of Statistics

Date Written: August 23, 2018

Abstract

This document provides an overview of the StMAR Toolbox, a MATLAB toolbox specifically designed for simulation, estimation, diagnostic, and forecasting of the Student’s t mixture autoregressive (StMAR) model proposed by Meitz, Preve & Saikkonen (2018). The StMAR model is a new type of mixture autoregressive model with observation dependent mixing weights. Its stationary formulation implies that both the conditional and unconditional distributions of its AR component models are Student’s t, and that the conditional variances of these models are of ARCH type. The conditional and unconditional distributions of the StMAR model are both mixtures of Student’s t distributions. This makes it suitable for modelling time series with excess kurtosis, regime switching, multimodality, persistence, and conditional heteroskedasticity. Potential applications in finance include the modelling and forecasting of return, interest rate, and volatility proxy series, but researchers and practitioners from other fields can also use the toolbox without any modifications. The StMAR Toolbox is free and publicly available software.

Keywords: Mixture Model, Regime Switching, Conditional Heteroskedasticity, Student’s t Distribution, Financial Econometrics, Numerical Optimization, Parallel Computing, MATLAB

JEL Classification: C22, C46, C53, C58, C61, C63, C87

Suggested Citation

Meitz, Mika and Preve, Daniel P. A. and Saikkonen, Pentti, StMAR Toolbox: A MATLAB Toolbox for Student's t Mixture Autoregressive Models (August 23, 2018). Available at SSRN: https://ssrn.com/abstract=3237368 or http://dx.doi.org/10.2139/ssrn.3237368

Mika Meitz

University of Helsinki - Department of Political and Economic Studies

P.O. Box 54
FIN-00014 Helsinki
Finland

Daniel P. A. Preve (Contact Author)

Singapore Management University ( email )

90 Stamford Road
Singapore, 178903
Singapore

Pentti Saikkonen

University of Helsinki - Department of Statistics ( email )

Finland
+09 191 24867 (Phone)

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