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Trading VIX on volatility forecasts: another volatility puzzle?

Author

Listed:
  • Stavros Degiannakis

    (Bank of Greece and Panteion University)

  • Panagiotis Delis

    (Bank of Greece and University of Piraeus)

  • George Filis

    (University of Patras)

  • George Giannopoulos

    (Kingston University and University of West Attica)

Abstract

This study evaluates the economic usefulness of stock market implied volatility forecasts, based on their ability to improve the short-run trading decision-making process. The current literature aligns the forecast horizon with the frequency of the trading decision in order to evaluate different forecasting frameworks. By contrast, the premise of our paper is that these should not be necessarily related, but rather the evaluation should be based on the actual needs of the end-user. Thus, we evaluate whether the multiple days ahead stock market volatility forecasts vis-Ã -vis the 1-day ahead forecasts can improve the 1-day ahead trading profits from VIX and the S&P500 futures. Our results suggest that indeed the 1-day ahead trading profits are significantly improved when the trading decisions are based on longer-term volatility forecasts. More specifically, the highest trading gains are obtained when using the 22-days-ahead forecasts. The results hold true for both VIX and S&P500 futures day-ahead trading. Although there is no theoretical background regarding the fact that forecasting and trading horizons should not be aligned, we strongly motivate this potential issue, both from the statistical and financial point of views.

Suggested Citation

  • Stavros Degiannakis & Panagiotis Delis & George Filis & George Giannopoulos, 2025. "Trading VIX on volatility forecasts: another volatility puzzle?," Working Papers 336, Bank of Greece.
    • Handle: RePEc:bog:wpaper:336
    DOI: 10.52903/wp2025336
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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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