We examine whether the option market leads the stock market with respect to positive in addition to negative price discovery. We document that out-of-themoney (OTM) option prices, which determine the Risk-Neutral Skewness (RNS) of the underlying stock return's distribution, can embed positive...

This paper introduces a new technique to infer the risk-neutral probability distribution of an asset from the prices of options on this asset. The technique is based on using the trading volume of each option as a proxy of the informativeness of the option. Not requiring the implied probability...

We provide a new method to derive the state price density per unit probability based on option prices and GARCH model. We derive the risk neutral distribution using the result in Breeden and Litzenberger (1978) and the historical density adapting the GARCH model of Barone-Adesi, Engle, and...

In this paper we model the adjustment process of European Union Allowance (EUA) prices to the releases of announcements at high-frequency controlling for intraday periodicity, volatility clustering and volatility persistence. We find that the high-frequency EUA price dynamics are very well...

This paper empirically examines price formation in the European Union Emissions Trading Scheme (EU ETS). Our analysis shows that unexpected allocations of European Union Allowances (EUAs) lead to pronounced price reactions of the expected signs. Moreover, we find evidence that the adjustment of...

This paper introduces a new technique to infer the risk-neutral probability distribution of an asset from the prices of options on this asset. The technique is based on using the trading volume of each option as a proxy of the informativeness of the option. Not requiring the implied probability...

In this paper, information processing in spot and forward freight markets with respect to the Organization of the Petroleum Exporting Countries (OPEC) output announcements is investigated. We use the event study methodology to study returns in tanker freight spot and forward markets around OPEC...

We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision parameter of the DP process is calibrated to the...

We characterize how informed investors trade in the options market ahead of corporate news when they receive private, but noisy, information about (i) the timing of the announcement and (ii) its impact on stock prices. Our theoretical framework generates a rich set of predictions about the...

In this paper, we introduce two classes of indices which can be used to measure the market perception concerning the degree of dependency that exists between a set of random variables, representing different stock prices at a fixed future date. The construction of these measures is based on the...