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A comprehensive look at financial volatility prediction by economic variables

Author Info

  • Charlotte Christiansen
  • Maik Schmeling
  • Andreas Schrimpf

Abstract

What drives volatility on financial markets? This paper takes a comprehensive look at the predictability of financial market volatility by macroeconomic and financial variables. We go beyond forecasting stock market volatility (by large the focus in previous studies) and additionally investigate the predictability of foreign exchange, bond, and commodity volatility by means of a data-rich modeling methodology which is able to handle a potentially large number of predictor variables. In line with previous research, we find relatively little economically meaningful predictability of stock market volatility. By contrast, volatility in foreign exchange, bond, and commodity markets appears predictable by macro and financial predictors both in-sample and out-of-sample.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 27 (2012)
Issue (Month): 6 (09)
Pages: 956-977

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Handle: RePEc:wly:japmet:v:27:y:2012:i:6:p:956-977
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Find related papers by JEL classification:
  • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
  • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
  • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
  • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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Cited by:

  1. Becker, Christoph & Schmidt, Wolfgang M., 2013. "Stressing correlations and volatilities — A consistent modeling approach," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 174-194.
  2. Dimpfl, Thomas & Jank, Stephan, 2011. "Can Internet search queries help to predict stock market volatility?," University of Tuebingen Working Papers in Economics and Finance 18, University of Tuebingen, Faculty of Economics and Social Sciences.
  3. Nektarios Aslanidis & Charlotte Christiansen & Christos S. Savva, 2013. "Risk-Return Trade-Off for European Stock Markets," CREATES Research Papers 2013-31, School of Economics and Management, University of Aarhus.
  4. Nektarios Aslanidis & Charlotte Christiansen, 2012. "Quantiles of the Realized Stock-Bond Correlation and Links to the Macroeconomy," CREATES Research Papers 2012-34, School of Economics and Management, University of Aarhus.
  5. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
  6. Fabian Baetje & Lukas Menkhoff, 2015. "Equity Premium Prediction: Are Economic and Technical Indicators Instable?," Kiel Working Papers 1987, Kiel Institute for the World Economy.
  7. Charlotte Christiansen & Jonas Nygaard Eriksen & Stig V. Møller, 2013. "Forecasting US Recessions: The Role of Sentiments," CREATES Research Papers 2013-14, School of Economics and Management, University of Aarhus.
  8. Nektarios Aslanidis & Charlotte Christiansen & Neophytos Lambertides & Christos S. Savva, 2014. "Idiosyncratic Volatility Puzzle: Influence of Macro-Finance Factors," CREATES Research Papers 2014-45, School of Economics and Management, University of Aarhus.
  9. Sévi, Benoît, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Economic Modelling, Elsevier, vol. 31(C), pages 189-197.

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