IDEAS home Printed from https://ideas.repec.org/p/hhs/gunsru/2007_008.html
   My bibliography  Save this paper

Similarities and differences between statistical surveillance and certain decision rules in finance

Author

Listed:
  • Bock, David

    (Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University)

  • Andersson, Eva

    (Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University)

  • Frisén, Marianne

    (Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University)

Abstract

Financial trading rules have the aim of continuously evaluating available information in order to make timely decisions. This is also the aim of methods for statistical surveillance. Many results are available regarding the properties of surveillance methods. We give a review of financial trading rules and use the theory of statistical surveillance to find properties of some commonly used trading rules. In addition, a nonparametric and robust surveillance method is proposed as a trading rule. Evaluation measures used in statistical surveillance are compared with those used in finance. The Hang Seng Index is used for illustration.

Suggested Citation

  • Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Similarities and differences between statistical surveillance and certain decision rules in finance," Research Reports 2007:8, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
  • Handle: RePEc:hhs:gunsru:2007_008
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/2077/8476
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sweeney, Richard J, 1986. "Beating the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 41(1), pages 163-182, March.
    2. E. Andersson, 2002. "Monitoring cyclical processes. A non-parametric approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 973-990.
    3. Frisén, Marianne, 2007. "Principles for Multivariate Surveillance," Research Reports 2007:4, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    4. Blondell, David & Hoang, Philip & Powell, John G. & Shi, Jing, 2002. "Detection of Financial Time Series Turning Points: A New CUSUM Approach Applied to IPO Cycles," Review of Quantitative Finance and Accounting, Springer, vol. 18(3), pages 293-315, May.
    5. Moore, Geoffrey H. & Boehm, Ernst A. & Banerji, Anirvan, 1994. "Using economic indicators to reduce risk in stock market investments," International Journal of Forecasting, Elsevier, vol. 10(3), pages 405-417, November.
    6. Marianne Frisén, 2003. "Statistical Surveillance. Optimality and Methods," International Statistical Review, International Statistical Institute, vol. 71(2), pages 403-434, August.
    7. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, August.
    8. Neely, C. J. & Weller, P. A., 2003. "Intraday technical trading in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 22(2), pages 223-237, April.
    9. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
    10. John M. Maheu & Thomas H. McCurdy, 2004. "News Arrival, Jump Dynamics, and Volatility Components for Individual Stock Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 755-793, April.
    11. Christopher J. Neely, 1997. "Technical analysis in the foreign exchange market: a layman's guide," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 23-38.
    12. Allan Layton & Masaki Katsuura, 2001. "A new turning point signalling system using the Markov switching model with application to Japan, the USA and Australia," Applied Economics, Taylor & Francis Journals, vol. 33(1), pages 59-70.
    13. Christian Sonesson & David Bock, 2003. "A review and discussion of prospective statistical surveillance in public health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(1), pages 5-21, February.
    14. Przemysław Śliwa & Wolfgang Schmid, 2005. "Monitoring the cross-covariances of a multivariate time series," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 61(1), pages 89-115, February.
    15. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, vol. 64(4), pages 549-571, October.
    16. Andersson, Eva & Bock, David & Frisén, Marianne, 2007. "Modeling influenza incidence for the purpose of on-line monitoring," Research Reports 2007:5, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    17. Bock, David, 2007. "Consequences of using the probability of a false alarm as the false alarm measure," Research Reports 2007:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    18. Ivanova, Detelina & Lahiri, Kajal & Seitz, Franz, 2000. "Interest rate spreads as predictors of German inflation and business cycles," International Journal of Forecasting, Elsevier, vol. 16(1), pages 39-58.
    19. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    20. Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
    21. Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Statistical Surveillance of Epidemics: Peak Detection of Influenza in Sweden," Research Reports 2007:6, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    22. Zarnowitz, Victor & Moore, Geoffrey H, 1982. "Sequential Signals of Recession and Recovery," The Journal of Business, University of Chicago Press, vol. 55(1), pages 57-85, January.
    23. Hans Dewachter, 1997. "Sign predictions of exchange rate changes: Charts as proxies for Bayesian inferences," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 133(1), pages 39-55, March.
    24. Layton, Allan P., 1996. "Dating and predicting phase changes in the U.S. business cycle," International Journal of Forecasting, Elsevier, vol. 12(3), pages 417-428, September.
    25. Andersson, Eva, 2007. "Effect of dependency in systems for multivariate surveillance," Research Reports 2007:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    26. Ansgar Steland, 2002. "Nonparametric monitoring of financial time series by jump-preserving control charts," Statistical Papers, Springer, vol. 43(3), pages 401-422, July.
    27. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    28. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    29. Frisén, Marianne, 2007. "Optimal Sequential Surveillance for Finance, Public Health, and Other Areas," Research Reports 2007:2, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    30. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    31. Dewachter, Hans, 2001. "Can Markov switching models replicate chartist profits in the foreign exchange market?," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 25-41, February.
    32. David Bock & Eva Andersson & Marianne Frisén, 2005. "Statistical surveillance of cyclical processes with application to turns in business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 465-490.
    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. Schiöler, Linus, 2009. "Explorative analysis of spatial patterns of influenza incidences in Sweden 1999—2008," Research Reports 2008:5, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    2. Schiöler, Linus & Frisén, Marianne, 2008. "On statistical surveillance of the performance of fund managers," Research Reports 2008:4, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    3. Andersson, Eva, 2008. "Hotelling´s T2 Method in Multivariate On-line Surveillance. On the Delay of an Alarm," Research Reports 2008:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    4. Bock, David & Pettersson, Kjell, 2007. "Explorative analysis of spatial aspects on the Swedish influenza data," Research Reports 2007:10, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    5. Bock, David, 2007. "Evaluations of likelihood based surveillance of volatility," Research Reports 2007:9, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.

    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. Bock, David & Pettersson, Kjell, 2007. "Explorative analysis of spatial aspects on the Swedish influenza data," Research Reports 2007:10, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    2. Bock, David, 2007. "Evaluations of likelihood based surveillance of volatility," Research Reports 2007:9, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    3. Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Statistical Surveillance of Epidemics: Peak Detection of Influenza in Sweden," Research Reports 2007:6, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    4. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    5. Lee, Chun I & Gleason, Kimberly C. & Mathur, Ike, 2001. "Trading rule profits in Latin American currency spot rates," International Review of Financial Analysis, Elsevier, vol. 10(2), pages 135-156.
    6. Pettersson, Kjell, 2008. "On curve estimation under order restrictions," Research Reports 2007:15, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    7. Andersson, Eva, 2008. "Hotelling´s T2 Method in Multivariate On-line Surveillance. On the Delay of an Alarm," Research Reports 2008:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    8. Andersson, Eva & Kühlmann-Berenzon, Sharon & Linde, Annika & Schiöler, Linus & Rubinova, Sandra & Frisén, Marianne, 2007. "Predictions by early indicators of the time and height of yearly influenza outbreaks in Sweden," Research Reports 2007:7, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    9. Guanqing Liu, 2019. "Technical Trading Behaviour: Evidence from Chinese Rebar Futures Market," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 669-704, August.
    10. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
    11. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    12. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    13. BEN OMRANE, Walid & VAN OPPEN, Hervé, 2004. "The predictive success and profitability of chart patterns in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2004035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Schiöler, Linus & Frisén, Marianne, 2008. "On statistical surveillance of the performance of fund managers," Research Reports 2008:4, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    15. Frisén, Marianne, 2011. "Methods and evaluations for surveillance in industry, business, finance, and public health," Research Reports 2011:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    16. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    17. David Bock & Eva Andersson & Marianne Frisén, 2005. "Statistical surveillance of cyclical processes with application to turns in business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 465-490.
    18. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    19. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857, April.
    20. Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 257-279, September.

    More about this item

    Keywords

    Trading rules; Hidden Markov model; Filter rule; Moving average; Statistical surveillance;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hhs:gunsru:2007_008. 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: Linus Schiöler (email available below). General contact details of provider: http://www.statistics.gu.se/ .

    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.