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Forecasting stock market volatility with macroeconomic variables in real time

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  • Pierdzioch, Christian
  • Döpke, Jörg
  • Hartmann, Daniel

Abstract

We compare forecasts of stock market volatility based on real-time and revised macroeconomic data. To this end, we use a new dataset on monthly real-time macroeconomic variables for Germany. The dataset covers the period 1994-2005. We use statistical criteria, a utility-based criterion, and an options-based criterion to evaluate volatility forecasts. Our main result is that the statistical and economic value of volatility forecasts based on real-time macroeconomic data is comparable to the value of forecasts based on revised macroeconomic data.

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  • Pierdzioch, Christian & Döpke, Jörg & Hartmann, Daniel, 2008. "Forecasting stock market volatility with macroeconomic variables in real time," Journal of Economics and Business, Elsevier, vol. 60(3), pages 256-276.
    • Handle: RePEc:eee:jebusi:v:60:y:2008:i:3:p:256-276
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    3. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
    4. Ansgar Belke & Marcel Wiedmann, 2018. "Dissecting long-run and short-run causalities between monetary policy and stock prices," International Economics and Economic Policy, Springer, vol. 15(4), pages 761-786, October.
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    6. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss," Resources Policy, Elsevier, vol. 47(C), pages 95-107.
    7. Chao Liang & Yongan Xu & Zhonglu Chen & Xiafei Li, 2023. "Forecasting China's stock market volatility with shrinkage method: Can Adaptive Lasso select stronger predictors from numerous predictors?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3689-3699, October.
    8. Ming-Hsiang Chen, 2010. "Federal Reserve Monetary Policy and US Hospitality Stock Returns," Tourism Economics, , vol. 16(4), pages 833-852, December.
    9. Chen, Qiang & Gong, Yuting, 2019. "The economic sources of China's CSI 300 spot and futures volatilities before and after the 2015 stock market crisis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 102-121.
    10. repec:zbw:rwirep:0435 is not listed on IDEAS
    11. Ansgar Belke & Marcel Wiedmann, 2013. "Monetary Policy, Stock Prices and Central Banks - Cross-Country Comparisons of Cointegrated VAR Models," Ruhr Economic Papers 0435, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    12. Delia-Elena Diaconaşu, 2015. "CENTRAL AND EASTERN EUROPEAN STOCK MARKETS IN TIMES OF CRISIS (International Conference "Recent Advances in Economic and Social Research", 13-14 mai 2015, București)," Institute for Economic Forecasting Conference Proceedings 151205, Institute for Economic Forecasting.
    13. Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
    14. Dimitrios Subeniotis & Dimitrios Papadopoulos & Ioannis Tampakoudis & Athina Tampakoudi, 2011. "How Inflation, Market Capitalization, Industrial Production and the Economic Sentiment Indicator Affect the EU-12 Stock Markets," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 105-120.
    15. Zhang Wu & Terence Tai-Leung Chong, 2021. "Does the macroeconomy matter to market volatility? Evidence from US industries," Empirical Economics, Springer, vol. 61(6), pages 2931-2962, December.
    16. Belke, Ansgar & Wiedmann, Marcel, 2013. "Monetary Policy, Stock Prices and Central Banks - Cross-Country Comparisons of Cointegrated VAR Models," Ruhr Economic Papers 435, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    17. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
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    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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