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Score Driven Exponentially Weighted Moving Average and Value-at-Risk Forecasting
Company: Tinbergen Institute
Year Of Publication: 2014
Month Of Publication: July
Resource Link: Click here to open
Pages: 29
Download Count: 0
View Count: 1633
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 7-31-2014
Publisher: Administrator
We present a simple new methodology to allow for time-variation in volatilities using a recursive updating scheme similar to the familiar RiskMetrics approach. It exploits the link between exponentially weighted moving average and integrated dynamics of score driven time varying parameter models. The novel feature of our approach is that the parameter dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model nests several available extensions of the EWMA method proposed in the literature. It can be easily extended to handle dynamics of higher-order moments, and to the other preferred choice of forecasting distribution. We apply our method to Value-at-Risk forecasting with Student's t distributions and show that the new method is competitive to or better than earlier methods for volatility forecasting of stock returns and exchange rates.
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Lucas, Andre Sign in to follow this author
Zhang, Xin Sign in to follow this author
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