Investment behaviour, techniques and choices have evolved in the options markets since the launch of options trading in 1973. Today, we are entering the field of Big Data and the explosion of information, which has become the main feature of science, impacts investors' decisions and their...

In usual pricing approaches for weather derivatives, forward-looking information such as meteorological weather forecasts is not considered. Thus, important knowledge used by market participants is ignored in theory. By extending a standard model for the daily temperature, this paper allows the...

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...

This paper describes a method for computing risk-neutral density functions based on the option-implied volatility smile. Its aim is to reduce complexity and provide cookbook-style guidance through the estimation process. The technique is robust and avoids violations of option no-arbitrage...

The illiquidity of long-maturity options has made it difficult to study the term structures of option spanning portfolios. This paper proposes a new estimation and inference framework for these option-implied term structures that addresses long-maturity illiquidity. By building a sieve estimator...

We propose a new predictor of real economic activity (REA), namely the representative investor's implied relative risk aversion (IRRA) extracted from S&P 500 option prices. IRRA exploits the forward-looking information in option prices. It increases as risk averse investors enter the market,...

In this paper we develop the first estimator of the covariance matrix that relies solely on forward-looking information. This estimator only uses price information from a cross-section of plain-vanilla options. In an out-of-sample study for US blue-chip stocks we show that a minimum-variance...

We develop a new family of estimators of the covariance matrix that relies solely on forwardlooking information. It uses only current prices of plain-vanilla options. In an out-of-sample study we show that a minimum-variance strategy based on these fully-implied estimators outperforms several...

Building Risk-Neutral Density (RND) from options data is one useful form of extracting market expectations about a financial variable. For a sample of IDI (Brazilian Interbank Deposit Rate Index) options from 1998 to 2009, this paper estimates the option-implied Risk-Neutral Densities for the...