Options on bond futures: Isolating the risk premium

The introduction of unspanned sources of risk (and frictions) implies that option prices include a risk premium. Prima facie evidence of the existence of risk premia in option prices is contained in the implied volatility smile patterns reported in the literature. This article isolates the risk premium (defined as the simple difference between estimated and observed option prices) on options on U.K. Gilts, German Bunds, and U.S. Treasury bond futures using models that include price jumps and stochastic volatility. This study finds that single and multi‐factor stochastic volatility models with jumps may explain the empirical regularities observed in bond futures. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:169–215, 2003     

The role of financial investors in determining the commodity futures risk premium

I develop and test a model to study the interaction between the commodity and stock markets. This study attempts to clarify the debate about the effect of financialization on commodity markets. Theoretically, the futures risk premium is determined by hedging pressure, stock market returns, and the commodity–equity correlation. Empirically, the effect of the stock market on the energy market became significantly greater for the futures risk premium in the period following the 2008 crisis. Furthermore, hedging pressure is a strong explanatory variable for the futures risk premium in various circumstances.     

Commodity futures trading performance using neural network models versus ARIMA models

Neural networks trading returns are compared out-of-sample with traditional ARIMA returns for corn, silver, and deutsche mark. Results show that neural network and ARIMA models had positive returns, and at about the same levels. However, deutsche mark was less profitable and returns were not statistically different from zero, in contrast to corn and silver. © 1998 John Wiley & Sons, Inc. Jrl Fut Mark 18: 965–983, 1998     

Certainty equivalent,risk premium and asset pricing

This paper attempts to determine the certainty equivalent of an uncertain future cash flow or value through the option pricing method, and builds models of certainty equivalent and certainty equivalent coefficient. Based on the model of certainty equivalent coefficient, this paper further derives models of risk premium and risk-adjusted discount rate. The latter is a new capital asset pricing model (CAPM) accounting for total risk rather than with only the systematic risk accounted for as in the current CAPM. The reliability in relevant financial analysis, valuation, decision making and risk management may be enhanced with these new models.     

Industry variance risk premium,cross-industry correlation,and expected returns

We investigate the variance risk premium (VRP) and implied correlation (IC) at the industry level. Using the index and sector exchange-traded fund options, we construct-sector VRPs and cross-sector IC measures. Sector VRPs predict sector returns, and adding the average sector VRP with IC improves predictability. Combining the average sector VRP and IC outperforms the market VRP in predicting market returns both in-sample and out-of-sample and generates sizeable economic values. We document a strong spillover effect from sector VRPs to the market VRP. The average sector VRP and cross-sector IC contain information beyond the market VRP and cross-stock IC.     

Risk management with options and futures under liquidity risk

Futures hedging creates liquidity risk through marking to market. Liquidity risk matters if interim losses on a futures position have to be financed at a markup over the risk‐free rate. This study analyzes the optimal risk management and production decisions of a firm facing joint price and liquidity risk. It provides a rationale for the use of options on futures in imperfect capital markets. If liquidity risk materializes, the firm sells options on futures in order to partly cover this liquidity need. It is shown that liquidity risk reduces the optimal hedge ratio and that options are not normally used before a liquidity need actually arises. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:297–318, 2009     

Market power and systematic risk

This paper examines the relationship between market power variables and the systematic risk, beta, of a firm. The study controls for the effects of dividend policy, liquidity, and earnings growth. Market power is measured by firm size (both sales and assets), proportion of industry sales, and the industry's four-firm concentration ratio. The study finds only a weak relationship between individual firm market power and firm risk, but there is evidence of a strong negative relationship between industry concentration and the market risk of the firms in an industry. This indicates that firms in concentrated industries experience lower capital costs than firms in less-concentrated industries. The existence of limit pricing is suggested as an explanation for this finding.