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The purpose of this paper is to investigate and test for changes in investor risk aversion and the stochastic discount factor (SDF) using options data on the West Texas Intermediate crude oil futures contract during the 2007-2011 period.

Risk aversion functions and SDFs are estimated using parametric approaches before and after four specific dates of interest. The dates are: the summer 2008 end of the bull market regime; the late 2008 credit freeze trough; the BP Deepwater Horizon explosion; and the Libyan uprising.

Absolute risk aversion functions and SDFs are significantly flatter (less decreasing in wealth) after the end of the bull market and the credit freeze trough. After these two market reversals, oil market participants were less risk-averse for low levels of wealth but more risk-averse for high wealth levels. Oil market investors also increased their valuation of anticipated future wealth in average states of nature relative to very high or very low-asset return states after reversals. The BP explosion and the Libyan uprising led to steeper risk aversion functions (decreasing more rapidly in wealth) and SDF. Oil market investors were more risk-averse for lower future wealth, but less risk-averse for higher future wealth. Oil market investors increased their valuation of anticipated future wealth in extreme states of nature relative to average states of nature after both dates.

Documenting statistically and economically significant changes in oil market investors’ attitude toward risk and inter-temporal appetite for risk in relation to changes in financial and political conditions.

This chapter proposes a nonparametric estimator of the risk neutral density (RND) based on cross-sectional European option prices. The authors recast the arbitrage-free equation for option pricing as a functional linear regression model where the regressor is a curve and the independent variable is a scalar corresponding to the option price. Then, the authors show that the RND can be viewed as the solution of an ill-posed integral equation. To estimate the RND, the authors use an iterative method called Landweber-Fridman (LF). Then, the authors establish the consistency and asymptotic normality of the estimated RND. These results can be used to construct a confidence interval around the curve. Finally, some Monte Carlo simulations and application to the S&P 500 options show that this method performs well compared to alternative methods.

In this research, we analyze the impact of catastrophe events on risk-neutral densities which can be implied from European option markets. As catastrophe events we consider the destruction of the nuclear power plant at Fukushima and the downgrading of U.S. sovereign debt in 2011. In an event study, we analyze the impact on European blue chip index options traded at EUREX. We find that after a short adaption period, probability mass of especially risk-neutral density functions derived from long-term options is shifted toward the right side. Thus, very good states of the economy become more expensive indicating higher prices for deep out-of-the-money options. This signifies that there has been speculation on a recovery of the German stock market after the shocks.

To propose a new methodology to infer the risk‐neutral default probability curve of a generic firm XYZ from equity options prices.

It is assumed that the market is arbitrage‐free and the “market” probability measure implied in the equity options prices to the pricing of credit risky assets is applied. First, the equity probability density function of XYZ is inferred from a set of quoted equity options with different strikes and maturities. This function is then transformed into the probability density function of the XYZ assets and the term structure of the “option implied” XYZ default probabilities is calculated. These default probabilities can be used to price corporate bonds and, more generally, single‐name credit derivatives as “exotic” equity derivatives.

Equity derivatives and credit derivatives have ultimately the same (unobservable) underlying, the XYZ assets value. A model that considers any security issued by XYZ as derivatives on the firm's assets can be used to price these securities in a consistent way to each other and/or detect relative/value opportunities.

The paper offers both a pricing tool for traded single‐name credit risky assets or a relative value tool in liquid markets.

The purpose of this paper is to investigate the risk appetite in Hong Kong real estate and property security markets in the recent episode of global financial crisis.

An advanced methodology developed from the previous risk appetite measurement and Markov Chain Monte Carlo simulation is used. Traditional research on risk appetite had never been applied to the real estate market before because no options underlying properties exist. However, this paper makes a contribution that in the absence of options, risk appetite indicators are derived for the real estate and property security markets.

The empirical results show that the risk appetite for the real estate market started to fall markedly in the third quarter of 2008, matching the very period of the Sub‐prime Mortgage Crisis in the USA. By contrast, those for the property security index were stabilizing in that period. This implies that investors' risk attitude to the real estate market differs from that to the property security market. Furthermore, the correlations between the index prices and the corresponding risk appetite in each market suggest that investors are “risk neutral” in the real estate market, while they are “risk lovers” in the property security market.

This paper, to the authors' best knowledge, is the first study to explore the risk appetite indicator in the real estate market, which could enable us to shed new light on the market price movement from the perspective of investors' market sentiment.

To implement the model described in the companion paper, “Pricing credit risk through equity options calibration, part 1 – theory,” and show how to calculate the price of a set of coupon bonds issued by a US telecommunications and media company, AOL Time Warner, based on the information retrieved by the AOL equity derivatives market.

The risk‐neutral density function of AOL Time Warner's stock is inferred from options volatilities; from there, the AOL assets risk neutral density function is calculated together with the default probabilities at different dates in the future. Finally, a set of AOL coupon bonds are priced accordingly and compared to market prices.

The AOL model‐theoretical prices are close to market prices, meaning that it is possible to perform relative‐value analysis in the risky bonds market based on the equity markets information.

The paper shows how easily the model can be used as a tool for performing relative‐value analysis between the equity options and the credit markets by using real market data.

This study investigates a forecasting power of volatility curvatures and risk neutral densities implicit in KOSPI 200 option prices by analyzing minute by minute historical index option intraday trading data from January of 2007 to January of 2011. We begin by estimating implied volatility functions and risk neutral price densities based on non-parametric method every minute and by calculating volatility curvature and skewness premium. We then compare the daily rate of return of the signal following trading strategy that we buy (sell) a stock index when the volatility curvature or skewness premium increases (decreases) with that of an intraday buy-and-hold strategy that we buy a stock index on 9:05AM and sell it on 2:50PM. We found that the rate of return of the signal following trading strategy was significantly higher than that of the intraday buy-and-hold strategy, which implies that the option prices have a strong forecasting power on the direction of stock market. Another finding is that the information contents of option prices disappear after three or four minutes.

The purpose of this paper is to investigate the impact of Federal Open Market Committee (FOMC) meetings and the changes of the target rates on stock market uncertainty.

Multivariate regression analysis is applied to the historical data of VIX, FOMC meetings and target rates. Subtle relations are revealed by further categorizing the FOMC meetings into being scheduled and unscheduled and distinguishing the signs of the changes in VIX and target rates. CPI and the prime rate are used for robustness test.

The authors first examine the relation between FOMC meetings and target surprises; the results indicate that unscheduled FOMC meetings heavily impact the target surprises. Then, the authors investigate the relation between FOMC meetings and VIX changes; the results show that both unscheduled and scheduled FOMC meetings impact VIX, where the impacts of scheduled FOMC meetings are more substantial. The authors also analyze the responses of VIX to the target surprises, and the results reveal that there is an asymmetric effect of target surprises on VIX, where the influences of the scheduled positive target surprises are more significant. Finally, by examining the relation between the FOMC meeting and the risk-neutral density of the VIX option, the authors conclude that both KURT and SKEW are more affected by unscheduled FOMC meetings.

Deeper dimensions of the relations between VIX, FOMC meetings and target rates are analyzed and more insightful understandings of such relations are gained.