We examine the volatility-volume relation in futures markets using volume data categorized by type of trader. We find that the positive volatility-volume relation is driven by the general public, a group of traders who are distant from the trading f loor and therefore without precise information on order f low. Clearing members and f loor traders who observe order f low often decrease volatility. Our findings are consistent with Shalen's~1993! hypothesis that uninformed traders who cannot differentiate liquidity demand from fundamental value change increase volatility.* Florida International University and Florida Atlantic University, respectively. We thank the reviewer and the editor, René Stulz, for insightful comments and suggestions concerning the concepts and exposition of this article. We also thank

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We examine the pricing performance of VIX option models. Such models possess a wide-range of underlying characteristics regarding the behavior of both the S&P500 index and the underlying VIX. Our tests employ three representative models for VIX options: Whaley (1993), Grunbichler and Longstaff (1996), Carr and Lee (2007), Lin and Chang (2009), who test four stochastic volatility models, as well as to previous simulation results of VIX option models. We find that no model has small pricing errors over the entire range of strike prices and times to expiration. In particular, out-of-the-money VIX options are difficult to price, with Grunbichler and Longstaff 's mean-reverting model producing the smallest dollar errors in this category. Whaley's Black-like option model produces the best results for in-the-money VIX options. However, the Whaley model does under/overprice out-of-the-money call/put VIX options, which is opposite the behavior of stock index option pricing models. VIX options exhibit a volatility skew opposite the skew of index options.

We examine the return‐implied volatility relation by employing “commodity” option VIXs for the euro, gold, and oil. This relation is substantially weaker than for stock indexes. We propose several potential reasons for these unusually weak results. Also, gold possesses an unusual positive contemporaneous return coefficient, which is consistent with a demand volatility skew rather than the typical investment skew. Moreover, the euro and gold are not asymmetric. We relate the results to trading strategies, algorithmic trading, and behavioral theories. An important conclusion of the study is that important differences exist regarding implied volatility for certain types of assets that have not yet been explained in the literature; namely, the results in this study concerning commodity ETFs versus stock indexes, plus previous research on stock indexes versus individual stocks, and the pricing of stock index options versus individual stock options. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:261–281, 2014

We examine the diversification benefits of using individual futures contracts instead of simply a commodity index. We determine the ex‐ante, ex‐post, and stability results for optimal Markowitz portfolios, investigate the instability between the ex‐ante and ex‐post results, and compare our results to traditional and naïve portfolios. The ex‐ante complete futures portfolio dominates the traditional and naive portfolios and the ex‐post portfolio outperforms the naïve portfolio. The instability between the ex‐ante and ex‐post results is primarily driven by the time‐varying returns of the individual assets rather than by risk. Finally, the Sharpe portfolio results are essentially identical to the Markowitz results. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 33:343‐368, 2013

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The volume–volatility relationship during the dissemination stages of information flow is examined by analyzing various theories relating volume and volatility as complementary rather than competing models. The mixture of distributions hypothesis, sequential arrival of information hypothesis, the dispersion of beliefs hypothesis, and the noise trader hypothesis all add to the understanding of how volume and volatility interact for different types of futures traders. An integrated picture of the volume–volatility relationship is provided by investigating the dynamic linear and nonlinear associations between volatility and the volume of informed (institutional) and uninformed (the general public) traders. In particular, the trading behavior explanation for the persistence of futures volatility, the effect of the timing of private information arrival, and the response of institutional traders to excess noise trading risk is examined. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:963–992, 2008