Efficiency and Stability of Transaction Systems Based on Simple, Exponentially and Linearly Weighted Moving Averages
Abstract
Theoretical background: Most papers are dedicated to the problem of optimizing transaction systems only for a single asset or index. In the literature there is a noticeable lack of comprehensive studies related to the entire group of assets.
Purpose of the article: Optimization of transaction systems based on the intersection of the moving average and the closing price (signal of purchase and sale) for 404 shares listed on the Warsaw Stock Exchange. For each equity, the survey covered 5,000 sessions or less if shares were traded in a shorter time horizon. The moving average types used in the study were: Simple Moving Average (SMA), Linearly Weighted Average (WMA) and Exponentially Weighed Average (EMA). In subsequent parts of the article, a ranking of moving averages was conducted and the stability of transactional systems was assessed.
Research methods: The following methods were used in the study: 1) moving averages optimizing the transaction system – correlation analysis of rates of return and of moving averages lengths, linear regression, 2) ranking of transaction system effectiveness – simple and weighted rates of return rankings, 3) analysis of transaction system stability – correlation of the first and second moving average lengths that bring the two highest rates of return, the determination factor for moving average pairs and rates of return, as well as the WF ratio (average decrease in the effectiveness of the 16 best transaction systems per unit rate of return of the best transaction system).
Main findings: The obtained results clearly indicate that for all types of averages, transaction systems were optimized in the vast majority by short-term averages, which confirms the investors’ tendency to proceed transactions with a speculative rather than investment bias. Conducted ranking of the effectiveness of three types of moving averages (WMA, SMA, EMA) unambiguously indicated that for the most part the highest rates of return were obtained for transaction systems based on WMA, before SMA and EMA. The differences in the effectiveness of trading systems based on WMA and SMA were small, but systems using these two types of moving averages proved to be much more efficient than systems based on EMA.Keywords
Full Text:
PDF (Język Polski)References
Achelis, S. (1998). Analiza techniczna od A do Z. Warszawa: Wydawnictwo LT&P.
Appel, G. (2005). Technical Analysis Power Tools for Active Investors. New York: Prentice Hall Publishing.
Aronson, D. (2007). Evidence-based Technical Analysis. Hoboken: John Wiley & Sons.
Bolton, J., Boetticher, S. von (2015). Momentum Trading on the Johannesburg Stock Exchange after the Global Financial Crisis. Procedia Economics and Finance, 24. doi:10.1016/S2212-5671(15)00619-X
Brock, W., Lakonishok, H., LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. Journal of Finance, 47(5). doi:10.1111/j.1540-6261.1992.tb04681.x
Czuba, M., Kaszuba, B. (2009). Porównanie efektów stosowania średnich ruchomych w analizie finansowych szeregów czasowych polskiego rynku akcji. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu. Nauki o Finansach, (75).
Faber, M. (2007). A Quantitative Approach to Tactical Asset Allocation. Journal of Wealth Management, 9(4). doi:10.3905/jwm.2007.674809
Fifiled, S., Power, D., Knipe, D. (2008). The performance of moving average rules in emerging stock markets. Applied Financial Economics, 18(19). doi:10.1080/09603100701720302
Filar, W., Kąkol, W. (2013). Znaczenie średnich ruchomym w podejmowaniu decyzji inwestycyjnych na giełdzie. Modern Management Review, 18(20).
Gatley, E. (1999). Cena i czas. Zarys metod analizy technicznej. Warszawa: WIG-PRESS.
Górska, A. (2008). Zastosowanie narzędzi analizy technicznej w bezpośrednim i pośrednim inwestowaniu w towary. Zeszyty Naukowe SGGW. Ekonomika i Organizacja Gospodarki Żywności, (71).
Górska, A. (2011). Wykorzystanie strategii inwestycyjnych opartych na analizie technicznej do handlu towarami z WGT SA. Zeszyty Naukowe SGGW. Problemy Rolnictwa Światowego, (11).
Grebenkov, D., Serror, J. (2014). Following a trend with an exponential moving average: Analytical results for a Gaussian model. Physica A: Statistical Mechanics and its Applications, 394. doi:10.1016/j.physa.2013.10.007
Gwilym, O., Clare, A., Seaton, J., Thomas, S. (2010). Price and Momentum as Robust Tactical Approaches to Global Equity Investing. Journal of Investing, 19(3). doi:10.3905/joi.2010.19.3.080
Hochheimer, C. (1978). Computers Can Help You to Trade the Futures Markets. New York: Commodity Yearbook, Commodity Research Bureau.
Juszczuk, P., Kozak, J. (2016). Paradygmat programowania proceduralnego w procesie budowy systemów automatycznych bazujących na średnich kroczących. Studia Informatica Pomerania, (39).
Katsanos, M. (2009). Intermarket Trading Strategies. Chichester: Wiley & Sons.
Kaufman, P. (1978). Commodity Trading Systems and Methods. New York: John Wiley & Sons.
Kaufman, P. (2013). Trading Systems and Methods. New York: John Wiley & Sons.
Keltner, C. (1960). How to Make Money in Commodities. Kansas City: The Keltner Statistical Service.
Kilgallen, T. (2012). Testing the Simple Moving Average across Commodities, Global Stock Indices, and Currencies. Journal of Wealth Management, 15(1). doi:10.3905/jwm.2012.15.1.082
LeBeau, C., Lucas, D. (2016). Komputerowa analiza rynków terminowych. Warszawa: WIG-PRESS.
Letkowski, D. (2014). Wykorzystanie średnich ruchomych w analizie inwestycji giełdowych – dobór modelu i długość próby. Acta Universitatis Lodziensis. Folia Oeconomica, (2).
Mastalerz-Kodzis, A. (2013). Zastosowanie funkcji Höldera w modelu FRAMA. Studia Ekonomiczne, (159).
Mitra, S. (2011). Usefulness of Moving Average Based Trading Rules in India. International Journal of Business and Management, 6(7). doi:10.5539/ijbm.v6n7p199
Moskowitz, T., Ooi, Y., Pedersen, L. (2012). Time series momentum. Journal of Financial Economics, 104.
Murphy, J. (1995). Analiza techniczna. Warszawa: WIG-PRESS.
Nisson, S. (1996). Świece i inne japońskie metody analizowania wykresów. Warszawa: WIG-PRESS.
Nowakowski, J., Borowski, K. (2005). Zastosowanie teorii Carolana i Fischera na rynku kapitałowym. Warszawa: Difin.
Pring, M. (1998). Podstawy analizy technicznej. Warszawa: WIG-PRESS.
Raudys, A., Pabarskaite, Z. (2018). Optimizing the smoothness and accuracy of moving average for stock price data. Technological and Economic Development of Economy, 24(3).
Salamaga, P. (2013). Zastosowanie metody średniej kroczącej do badania zyskowności inwestycji na polskim rynku kapitałowym. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu. Nauki o Finansach, (323).
Skalrew, A. (1980). Technical of Professional Commodity Chart Analysis. New York: Commodity Research Bureau.
Tarczyński, W., Łuniewska, M. (2004). Dywersyfikacja ryzyka na polskim rynku kapitałowym. Warszawa: Wydawnictwo Placet.
Witkowska, D., Matuszewska, A., Kompa, K. (2008). Wprowadzenie do ekonometrii dynamicznej i finansowej. Warszawa: Wydawnictwo SGGW.
Zalewski, G. (2001). Kontrakty terminowe w praktyce. Warszawa: WIG-PRESS.
DOI: http://dx.doi.org/10.17951/h.2019.53.4.21-41
Date of publication: 2019-12-31 08:37:16
Date of submission: 2019-04-30 13:06:30
Statistics
Indicators
Refbacks
- There are currently no refbacks.
Copyright (c) 2019 Krzysztof Borowski
This work is licensed under a Creative Commons Attribution 4.0 International License.