Investing in VIX futures based on rolling GARCH models forecasts
A 2020 paper by Bilyk, Sakowski and Ślepaczuk on the volatility risk premium in volatility and options, using classical time-series methods on a 2013–2019 sample: the abstract mentions excess returns and a benchmark and leaves out an out-of-sample test, transaction costs, multiple testing and the size of the universe.
“We found out that using the daily data over the seven-year period (2013-2019), strategy based on the fGARCH-TGARCH and GJR-GARCH specifications outperformed those of the GARCH and EGARCH models, and performed slightly below the “buy-and-hold” S&P 500 strategy.”
AssetVolatility and optionsfutures, indices
StrategyVolatility risk premium
TechniqueClassical time series
GeographyUS
Also stated: Daily, 2013–2019, Excess return, Long-short, Long-only, benchmark
Missing from abstract: out-of-sample test, costs, multiple testing, universe
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The paper's neighbourhoodVolatility risk premium by year
FamilyVolatility risk premium102Momentum and trend following289Factor investing240Machine learning return prediction15318 more · 900
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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