log-returns and their volatility with the aim of analysing which risk factors and which distribution features provide a …-returns and volatility offer the best trade-off between model performance and parsimony …

We develop a theoretical trading conditioning model subject to price volatility and return information in terms of … transaction volume probability to describe price volatility uncertainty and intensity. Applying the model to high frequent data …

stability. A case in point is the abrupt market crash of short volatility strategies on February 5th 2018. In this paper, we …

used to derive a measure of the volatility of interest rate and also that of the Prices. This is achieved by exploiting the …

are obtained and applied to numerically analyze the impact of the agents' risk aversion on the implied volatility of … pricing ; implied volatility. …

We derive robust good-deal hedges and valuations under combined model ambiguity about the drift and volatility of asset …-arbitrage bounds. In mathematical terms, it demands however that not just ambiguities about the volatility but also about the drift …

incomplete financial markets may increase volatility in asset prices significantly …

We analyze the joint cross-section of monthly S&P500 stock index options and monthly CBOE Volatility Index options by … stochastic volatility model and Distributionally Robust Optimization. Significant pricing errors appear if the Stochastic …-of-the-money volatility index puts appears particularly appealing to pure market risk averters. The evidence against option market efficiency …