Forecasting multidimensional tail risk at short and long horizons

Polanski, Arnold and Stoja, Evarist (2017) Forecasting multidimensional tail risk at short and long horizons. International Journal of Forecasting, 33 (4). 958–969. ISSN 0169-2070

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    Abstract

    We define the Multidimensional Value at Risk (MVaR) as a natural generalization of VaR. This generalization makes a number of important applications possible. For example, many techniques developed for VaR can be applied to MVaR directly. As an illustration, we employ VaR forecasting and evaluation techniques. One of our forecasting models builds on the progress made in the volatility literature and decomposes MVaR into long-term trend and short-term cycle components. We compute short- and long-term MVaR forecasts for several multidimensional time series and discuss their (un)conditional accuracy.

    Item Type: Article
    Uncontrolled Keywords: multidimensional risk,multidimensional value at risk,long horizon forecasting,two-factor decomposition
    Faculty \ School: Faculty of Social Sciences > School of Economics
    Depositing User: Pure Connector
    Date Deposited: 10 May 2017 06:05
    Last Modified: 06 Nov 2018 15:46
    URI: https://ueaeprints.uea.ac.uk/id/eprint/63443
    DOI: 10.1016/j.ijforecast.2017.05.005

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