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Volatility, global information, and market conditions: a study in futures markets

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  • Hung‐Gay Fung
  • Gary A. Patterson

Abstract

This study examined the behavior of return volatility in relation to the timing of information flow under different market conditions influenced by trading volume and market depth. We emphasized information flow during trading and nontrading periods that may represent domestic and offshore information in the global trading of currencies. Test results show that volatility was negatively related to market depth; that is, deeper markets had relatively less return volatility. Additionally, the effect that market depth had on volatility was superseded by information within trading volume. Test results focusing on the timing of information flow reveal that in low‐volume markets, the volatility of nontrading‐period returns exceeded the volatility of trading‐period returns. However, when trading volume was high, this pattern was reversed and conformed to the observations of earlier articles. Our findings proved to be robust across time, different currency markets, and different measures of return volatility. We also observed a trend toward greater integration between foreign and U.S. financial markets; the U.S. market increasingly emphasized information from nontrading periods to supplement information arriving during trading periods. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:173–196, 2001

Suggested Citation

  • Hung‐Gay Fung & Gary A. Patterson, 2001. "Volatility, global information, and market conditions: a study in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(2), pages 173-196, February.
  • Handle: RePEc:wly:jfutmk:v:21:y:2001:i:2:p:173-196
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    Cited by:

    1. Vijay Singal & Jitendra Tayal, 2020. "Risky short positions and investor sentiment: Evidence from the weekend effect in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 479-500, March.
    2. Chan, Leo H. & Nguyen, Chi M. & Chan, Kam C., 2015. "A new approach to measure speculation in the oil futures market and some policy implications," Energy Policy, Elsevier, vol. 86(C), pages 133-141.
    3. Nanying Wang & Jack E. Houston, 2016. "The Co-Movement between Non-GM and GM Soybean Prices in China: Evidence from Dalian Futures Market (2004-2014)," Applied Economics and Finance, Redfame publishing, vol. 3(4), pages 37-47, November.
    4. Chan, Kam C. & Chan, Leo H. & Nguyen, Chi M., 2020. "Forecasting oil futures market volatility in a financialized world: Why speculative activities matter," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
    6. Wang, Nanying & Houston, Jack E., 2015. "The Co-movement between Non-GM and GM Soybean Price in China: Evidence from China Futures Market," 2015 Conference, August 9-14, 2015, Milan, Italy 211914, International Association of Agricultural Economists.
    7. Hung-Gay Fung & Liuqing Mai & Lin Zhao, 2016. "The effect of nighttime trading of futures markets on information flows: evidence from China," China Finance and Economic Review, Springer, vol. 4(1), pages 1-16, December.

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