The Variance Risk Premium and Fundamental Uncertainty
Conrad and Loch (2015) study the volatility risk premium in equities using classical time-series methods. The abstract does not mention a benchmark, an out-of-sample test, transaction costs, multiple testing or the size of the universe.
“We find that the new measure has strong predictive ability for future U.S. aggregate stock market returns and rationalize this result by showing that the new measure effectively isolates fundamental uncertainty as the factor that drives the variance risk premium.”
AssetEquities
StrategyVolatility risk premium
TechniqueClassical time series
GeographyUS
Also stated: Fundamentals, Options-implied
Missing from abstract: benchmark, 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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