I implement the accounting-based risk measurement approach in equity valuation proposed by Nekrasov and Shroff (2009) for the German market using monthly data from 2002 to 2019. The empirical analysis shows that value estimates based on this risk measurement approach produce a significantly...

We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...

Inflation expectation is acknowledged to be an important indicator for policy makers and financial investors. To capture a more accurate real-time estimate of inflation expectation on the basis of financial markets, we propose an arbitrage-free model across different countries in a...

We propose a conditional model of asset returns in the presence of common factors and downside risk. Specifically, we generalize existing latent factor models in three ways: we show how to estimate the threshold which identifies the 'disappointment' event triggering the bad state of the world; we...

This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create...

We examine how extreme market risks are priced in the cross-section of asset returns at various horizons. Based on the frequency decomposition of covariance between indicator functions, we define the quantile cross-spectral beta of an asset capturing tail-specific as well as horizon-, or...

We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a stock's return (liquidity) is lowest at the same time when the market liquidity (return) is lowest....