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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.

Suggested Citation

  • 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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    Cited by:

    1. 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.
    2. Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
    3. Kizys, Renatas & Pierdzioch, Christian, 2010. "The business cycle and the equity risk premium in real time," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 711-722, October.
    4. Ansgar Belke & Marcel Wiedmann, 2013. "Money, Stock Prices and Central Banks – Cross-Country Comparisons of Cointegrated VAR Models," ROME Working Papers 201308, ROME Network.
    5. Martha Cecilia García & Aura María Jalal & Luis Alfonso Garzón & Jorge Mario López, 2013. "Métodos para predecir índices Bursátiles," REVISTA ECOS DE ECONOMÍA, UNIVERSIDAD EAFIT, December.
    6. 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.
    7. repec:zbw:rwirep:0435 is not listed on IDEAS
    8. 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.
    9. 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.
    10. Christian Pierdzioch, 2012. "Macroeconomic Factors and the German Real Estate Market: A Stock-Market-Based Forecasting Experiment," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 87-96, May.

    More about this item

    JEL classification:

    • 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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