Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies

被引:23
作者
Fiszeder, Piotr [1 ,2 ]
Malecka, Marta [3 ]
机构
[1] Nicolaus Copernicus Univ Torun, Torun, Poland
[2] Prague Univ Econ & Business, Prague, Czech Republic
[3] Univ Lodz, Lodz, Poland
来源
EQUILIBRIUM-QUARTERLY JOURNAL OF ECONOMICS AND ECONOMIC POLICY | 2022年 / 17卷 / 04期
关键词
volatility models; high-low range; robust estimation; invasion of Ukraine; war; WORLD-WAR-II; GARCH MODELS; RANGE; OUTLIERS; RISK; MARKETS; RETURNS; PRICES; VALUES;
D O I
10.24136/eq.2022.032
中图分类号
F [经济];
学科分类号
02 ;
摘要
Research background: The Russian invasion on Ukraine of February 24, 2022 sharply raised the volatility in commodity and financial markets. This had the adverse effect on the accuracy of volatility forecasts. The scale of negative effects of war was, however, market-specific and some markets exhibited a strong tendency to return to usual levels in a short time. Purpose of the article: We study the volatility shocks caused by the war. Our focus is on the markets highly exposed to the effects of this conflict: the stock, currency, cryptocurrency, gold, wheat and crude oil markets. We evaluate the forecasting accuracy of volatility models during the first stage of the war and compare the scale of forecast deterioration among the examined mar-kets. Our long-term purpose is to analyze the methods that have the potential to mitigate the effect of forecast deterioration under such circumstances. We concentrate on the methods designed to deal with outliers and periods of extreme volatility, but, so far, have not been investigated empiri-cally under the conditions of war. Methods: We use the robust methods of estimation and a modified Range-GARCH model which is based on opening, low, high and closing prices. We compare them with the standard maximum
引用
收藏
页码:939 / 967
页数:29
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