IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v41y2014icp156-165.html
   My bibliography  Save this article

Relationship between the trading behavior of three institutional investors and Taiwan Stock Index futures returns

Author

Listed:
  • Lai, Hung-Cheng
  • Wang, Kuan-Min

Abstract

The relations between institutional investors' behavior and futures returns are examined in this study. Evidence suggests that net trading volume by foreign investors and investment trust have forecasting power for futures returns. In addition, the study applies a time-varying parameter vector autoregressive (TVP-VAR) approach to estimate the relative effects of trading behavior by institutional investors on futures returns over time. The impact of open interest by three institutional investors is decreasing over the recent years. This implies that the value for open interest information from three major institutional investors is gradually declining in Taiwan.

Suggested Citation

  • Lai, Hung-Cheng & Wang, Kuan-Min, 2014. "Relationship between the trading behavior of three institutional investors and Taiwan Stock Index futures returns," Economic Modelling, Elsevier, vol. 41(C), pages 156-165.
  • Handle: RePEc:eee:ecmode:v:41:y:2014:i:c:p:156-165
    DOI: 10.1016/j.econmod.2014.05.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999314001746
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2014.05.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hong, Harrison & Yogo, Motohiro, 2012. "What does futures market interest tell us about the macroeconomy and asset prices?," Journal of Financial Economics, Elsevier, vol. 105(3), pages 473-490.
    2. Sanders, Dwight R. & Boris, Keith & Manfredo, Mark, 2004. "Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports," Energy Economics, Elsevier, vol. 26(3), pages 425-445, May.
    3. Stelios D. Bekiros & Alessia Paccagnini, 2016. "Policy‐Oriented Macroeconomic Forecasting with Hybrid DGSE and Time‐Varying Parameter VAR Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 613-632, November.
    4. Bessembinder, Hendrik & Seguin, Paul J., 1993. "Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(1), pages 21-39, March.
    5. Frans A. De Roon & Theo E. Nijman & Chris Veld, 2000. "Hedging Pressure Effects in Futures Markets," Journal of Finance, American Finance Association, vol. 55(3), pages 1437-1456, June.
    6. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    7. Hung Chih Li & Chao Hsien Lin & Teng Yuan Cheng & Syouching Lai, 2013. "How Different Types of Traders Behave in the Taiwan Futures Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(12), pages 1097-1117, December.
    8. Bhargava, Vivek & Malhotra, D.K., 2007. "The relationship between futures trading activity and exchange rate volatility, revisited," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 95-111, April.
    9. Gary B. Gorton & Fumio Hayashi & K. Geert Rouwenhorst, 2013. "The Fundamentals of Commodity Futures Returns," Review of Finance, European Finance Association, vol. 17(1), pages 35-105.
    10. Changyun Wang, 2003. "Investor sentiment, market timing, and futures returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(12), pages 891-898.
    11. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    12. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    13. Buchanan, W. K. & Hodges, P. & Theis, J., 2001. "Which way the natural gas price: an attempt to predict the direction of natural gas spot price movements using trader positions," Energy Economics, Elsevier, vol. 23(3), pages 279-293, May.
    14. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
    15. Manish Kumar, 2010. "A Time-Varying Parameter Vector Autoregression Model for Forecasting Emerging Market Exchange Rates," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 3(2), pages 21-39, December.
    16. Wang, Changyun & Yu, Min, 2004. "Trading activity and price reversals in futures markets," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1337-1361, June.
    17. Sato, Joao R. & Morettin, Pedro A. & Arantes, Paula R. & Amaro Jr., Edson, 2007. "Wavelet based time-varying vector autoregressive modelling," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5847-5866, August.
    18. Bekiros, Stelios, 2014. "Forecasting with a state space time-varying parameter VAR model: Evidence from the Euro area," Economic Modelling, Elsevier, vol. 38(C), pages 619-626.
    19. Bessembinder, Hendrik & Chan, Kalok, 1992. "Time-varying risk premia and forecastable returns in futures markets," Journal of Financial Economics, Elsevier, vol. 32(2), pages 169-193, October.
    20. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    21. Michael Dewally & Louis H. Ederington & Chitru S. Fernando, 2013. "Determinants of Trader Profits in Commodity Futures Markets," Review of Financial Studies, Society for Financial Studies, vol. 26(10), pages 2648-2683.
    22. Bessembinder, Hendrik, 1992. "Systematic Risk, Hedging Pressure, and Risk Premiums in Futures Markets," Review of Financial Studies, Society for Financial Studies, vol. 5(4), pages 637-667.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ya-Wen Lai, 2023. "Impact of futures’ trader types on stock market quality: evidence from Taiwan," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 417-436, June.
    2. Huang, Jianbai & Li, Yingli & Zhang, Hongwei & Chen, Jinyu, 2021. "The effects of uncertainty measures on commodity prices from a time-varying perspective," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 100-114.
    3. Arumugam, Devika, 2023. "Algorithmic trading: Intraday profitability and trading behavior," Economic Modelling, Elsevier, vol. 128(C).
    4. Boubekeur Baba & Güven Sevil, 2021. "Bayesian analysis of time-varying interactions between stock returns and foreign equity flows," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-25, December.
    5. Yen-Hsien Lee & Wen-Chien Liu & Chia-Lin Hsieh, 2017. "Informed Trading of Futures Markets During the Financial Crisis: Evidence from the VPIN," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(9), pages 123-132, September.
    6. Gong, Xu & Lin, Boqiang, 2018. "Time-varying effects of oil supply and demand shocks on China's macro-economy," Energy, Elsevier, vol. 149(C), pages 424-437.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guillermo Llorente & Jiang Wang, 2020. "Trading and information in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(8), pages 1231-1263, August.
    2. Yu-Lun Chen & Yin-Feng Gau & Wen-Ju Liao, 2016. "Trading activities and price discovery in foreign currency futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 793-818, May.
    3. Kilian, Lutz & Baumeister, Christiane, 2014. "A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil," CEPR Discussion Papers 10162, C.E.P.R. Discussion Papers.
    4. Yu, Dan & Chen, Chuang & Wang, Yudong & Zhang, Yaojie, 2023. "Hedging pressure momentum and the predictability of oil futures returns," Economic Modelling, Elsevier, vol. 121(C).
    5. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).
    6. Massimo Guidolin & Manuela Pedio, 2018. "Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors," BAFFI CAREFIN Working Papers 1886, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    7. Emanuel Kohlscheen & Jouchi Nakajima, 2021. "Steady‐state growth," International Finance, Wiley Blackwell, vol. 24(1), pages 40-52, April.
    8. repec:ipg:wpaper:19 is not listed on IDEAS
    9. Valenti, Daniele & Manera, Matteo & Sbuelz, Alessandro, 2020. "Interpreting the oil risk premium: Do oil price shocks matter?," Energy Economics, Elsevier, vol. 91(C).
    10. Daskalaki, Charoula & Skiadopoulos, George & Topaloglou, Nikolas, 2017. "Diversification benefits of commodities: A stochastic dominance efficiency approach," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 250-269.
    11. Yannick Le Pen & Benoît Sévi, 2013. "Futures Trading and the Excess Comovement of Commodity Prices," Working Papers halshs-00793724, HAL.
    12. Smimou, K., 2017. "Does gold Liquidity learn from the greenback or the equity?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 461-479.
    13. repec:ipg:wpaper:2013-019 is not listed on IDEAS
    14. Loïc Maréchal, 2023. "A tale of two premiums revisited," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 580-614, May.
    15. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    16. Ziran Li & Dermot J. Hayes, 2022. "The hedging pressure hypothesis and the risk premium in the soybean reverse crush spread," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 428-445, March.
    17. Jo, Yonghwan & Kim, Jihee & Santos, Francisco, 2022. "The impact of liquidity risk in the Chinese banking system on the global commodity markets," Journal of Empirical Finance, Elsevier, vol. 66(C), pages 23-50.
    18. Cifuentes, Sebastián & Cortazar, Gonzalo & Ortega, Hector & Schwartz, Eduardo S., 2020. "Expected prices, futures prices and time-varying risk premiums: The case of copper," Resources Policy, Elsevier, vol. 69(C).
    19. Daskalaki, Charoula & Skiadopoulos, George & Topaloglou, Nikolas, 2017. "Diversification benefits of commodities: A stochastic dominance efficiency approach," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 250-269.
    20. Miffre, Joëlle, 2016. "Long-short commodity investing: A review of the literature," Journal of Commodity Markets, Elsevier, vol. 1(1), pages 3-13.
    21. Mutafoglu, Takvor H. & Tokat, Ekin & Tokat, Hakki A., 2012. "Forecasting precious metal price movements using trader positions," Resources Policy, Elsevier, vol. 37(3), pages 273-280.
    22. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.

    More about this item

    Keywords

    Institutional investors; TVP-VAR model; Futures trading behavior;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:41:y:2014:i:c:p:156-165. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.