IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v69y2005i1p151-161.html
   My bibliography  Save this article

Speculation and destabilisation

Author

Listed:
  • Radalj, Kim F.
  • McAleer, Michael

Abstract

In the context of flexible exchange rates, Milton Friedman proposed that speculation must exert a stabilising influence on prices to remain profitable. This generated a substantial amount of predominantly theoretical research into the behaviour of speculators, for which the results seem to depend critically upon the assumptions. Such theoretical models need to be tested against empirical evidence to determine whether speculators behave in a destabilising manner. Using recent theoretical developments in the literature on modelling financial volatility, this paper tests the significance of speculators and their contributions to describing weekly volatilities across a series of currency, metals and commodity markets. As the time-varying conditional volatility GARCH model and its variants have been criticised for lacking economic content, incorporating speculators into such models contributes to an accommodation of this criticism. The economic implications from establishing the importance of speculators are far-reaching. Policymakers often discuss the imposition of a Tobin tax to curb speculation, so it must be established that speculators behave in economically destructive ways. The inclusion of speculators is also likely to yield superior forecasting models of volatility, and hence more efficient pricing of derivative instruments.

Suggested Citation

  • Radalj, Kim F. & McAleer, Michael, 2005. "Speculation and destabilisation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 69(1), pages 151-161.
  • Handle: RePEc:eee:matcom:v:69:y:2005:i:1:p:151-161
    DOI: 10.1016/j.matcom.2005.02.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475405000650
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2005.02.028?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. Shalen, Catherine T, 1993. "Volume, Volatility, and the Dispersion of Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 405-434.
    2. James Tobin, 1978. "A Proposal for International Monetary Reform," Eastern Economic Journal, Eastern Economic Association, vol. 4(3-4), pages 153-159, Jul/Oct.
    3. Hart, Oliver D & Kreps, David M, 1986. "Price Destabilizing Speculation," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 927-952, October.
    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. Baillie, Richard T & Bollerslev, Tim, 2002. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 60-68, January.
    6. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    7. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    8. Chang, Eric C. & Michael Pinegar, J. & Schachter, Barry, 1997. "Interday variations in volume, variance and participation of large speculators," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 797-810, June.
    9. M. F. Omran & E. McKenzie, 2000. "Heteroscedasticity in stock returns data revisited: volume versus GARCH effects," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 553-560.
    10. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    11. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    12. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    13. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    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. He, Ling-Yun & Fan, Ying & Wei, Yi-Ming, 2009. "Impact of speculator's expectations of returns and time scales of investment on crude oil price behaviors," Energy Economics, Elsevier, vol. 31(1), pages 77-84, January.

    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. Changyun Wang, 2002. "The effect of net positions by type of trader on volatility in foreign currency futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(5), pages 427-450, May.
    2. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    3. Geir H. Bjønnes & Dagfinn Rime & Haakon O. Aa. Solheim, 2002. "Volume and Volatility in the FX-Market: Does it matter who you are?," CESifo Working Paper Series 786, CESifo.
    4. Jinliang Li, 2016. "When noise trading fades, volatility rises," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 475-512, October.
    5. Chionis, Dionysios & MacDonald, Ronald, 1997. "Some tests of market microstructure hypotheses in the foreign exchange market," Journal of Multinational Financial Management, Elsevier, vol. 7(3), pages 203-229, October.
    6. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
    7. Chuang, Wen-I & Liu, Hsiang-Hsi & Susmel, Rauli, 2012. "The bivariate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility," Global Finance Journal, Elsevier, vol. 23(1), pages 1-15.
    8. Aris Kartsaklas, 2018. "Trader Type Effects On The Volatility‐Volume Relationship Evidence From The Kospi 200 Index Futures Market," Bulletin of Economic Research, Wiley Blackwell, vol. 70(3), pages 226-250, July.
    9. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    10. Chuang, Wen-I & Lee, Bong-Soo, 2006. "An empirical evaluation of the overconfidence hypothesis," Journal of Banking & Finance, Elsevier, vol. 30(9), pages 2489-2515, September.
    11. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    12. Yao, Yi & Yang, Rong & Liu, Zhiyuan & Hasan, Iftekhar, 2013. "Government intervention and institutional trading strategy: Evidence from a transition country," Global Finance Journal, Elsevier, vol. 24(1), pages 44-68.
    13. Niklas Wagner & Terry Marsh, 2005. "Surprise volume and heteroskedasticity in equity market returns," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 153-168.
    14. Rannou, Yves & Barneto, Pascal, 2016. "Futures trading with information asymmetry and OTC predominance: Another look at the volume/volatility relations in the European carbon markets," Energy Economics, Elsevier, vol. 53(C), pages 159-174.
    15. Ho, Kin-Yip & Zheng, Lin & Zhang, Zhaoyong, 2012. "Volume, volatility and information linkages in the stock and option markets," Review of Financial Economics, Elsevier, vol. 21(4), pages 168-174.
    16. Sensoy, Ahmet & Serdengeçti, Süleyman, 2019. "Intraday volume-volatility nexus in the FX markets: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 1-12.
    17. Lillyn L. Teh & Werner F. M. de Bondt, 1997. "Herding Behavior and Stock Returns: An Exploratory Investigation," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 133(II), pages 293-324, June.
    18. Henryk Gurgul & Roland Mestel & Tomasz Wojtowicz, 2007. "Distribution of volume on the American stock market," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 1, pages 143-163.
    19. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    20. Michael McAleer & Kim Radalj, 2013. "Herding, Information Cascades and Volatility Spillovers in Futures Markets," Journal of Reviews on Global Economics, Lifescience Global, vol. 2, pages 307-329.

    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:matcom:v:69:y:2005:i:1:p:151-161. 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.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.