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Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility

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  • Lindblad, Annika

Abstract

I use the GARCH-MIDAS framework of Engle et al. (2013) to examine the relationship between the macro economy and stock market volatility, focusing on the role played by survey-based sentiment indicators compared to macroeconomic variables. I find that once the information in sentiment indicators is controlled for, backward-looking macroeconomic data does not include useful information for predicting stock return volatility. On the other hand, forward-looking macroeconomic variables remain useful for forecasting stock market volatility after sentiment data is taken into account. The term spread is the best predictor for stock return volatility over long horizons.

Suggested Citation

  • Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:80266
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    Keywords

    stock market volatility; volatility components; MIDAS; survey data; macro finance link;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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