Advertisement

Eurasian Business Review

, Volume 7, Issue 3, pp 313–353 | Cite as

The application of technical trading rules developed from spot market prices on futures market prices using CAPM

  • Hakan Er
  • Adnan Hushmat
Original Paper

Abstract

Futures markets have seen a phenomenal success since their inception both in developed and developing countries during the last four decades. This success is attributable to the tremendous leverage the futures provide to market participants. This study contributes to the literature by analyzing a trading strategy which benefits from this leverage by using the Capital Asset Pricing Model (CAPM) and cost-of-carry relationship. We apply the technical trading rules developed from spot market prices, on futures market prices using a CAPM based hedge ratio. Historical daily prices of twenty stocks from each of the ten markets (five developed markets and five emerging markets) are used for the analysis. Popular technical indicators, along with artificial intelligence techniques like Neural Networks and Genetic Algorithms, are used to generate buy and sell signals for each stock and for portfolios of stocks. The performance of the trading strategies is then calculated and compared. The results show that, although equal amounts invested in both spot and futures markets, the profit from the strategies applied on futures is considerably higher than that from the spot market in both developed and emerging markets. Moreover, the overall performance of the artificial intelligence strategies is far better than the traditional ones.

Keywords

Futures CAPM Technical indicators Artificial intelligence Emerging markets Neural networks Genetic programming 

JEL Classification

G14 G17 G19 

References

  1. Allen, F., & Karjalainen, R. (1999). Using genetic algorithms to find technical trading rules. Journal of Financial Economics, 51(2), 245–271.CrossRefGoogle Scholar
  2. Bessembinder, H., & Chan, K. (1995). The profitability of technical trading rules in the Asian stock markets. Pacific-Basin Finance Journal., 7, 257–284.CrossRefGoogle Scholar
  3. Bhattacharya, U., & Galpin, N. (2011). The global rise of the value-weighted portfolio. Journal of Financial and Quantitative Analysis, 46(03), 737–756.CrossRefGoogle Scholar
  4. Blennerhassett, M., & Bowman, R. G. (1998). A change in market microstructure: the switch to electronic screen trading on the New Zealand stock exchange. Journal of International Financial Markets, Institutions and Money, 8(3), 261–276.CrossRefGoogle Scholar
  5. Block, S. B., & French, D. W. (2002). The effect of portfolio weighting on investment performance evaluation: The case of actively managed mutual funds. Journal of economics and finance, 26(1), 16–30.CrossRefGoogle Scholar
  6. Brown, P., & Walter, T. (2013). The CAPM: theoretical validity, empirical intractability and practical applications. Abacus, 49(S1), 44–50.CrossRefGoogle Scholar
  7. Butterworth, D., & Holmes, P. (2001). The hedging effectiveness of stock index futures: evidence for the FTSE-100 and FTSE-Mid250 indexes traded in the UK. Applied Financial Economics, 11(1), 57–68.CrossRefGoogle Scholar
  8. Cecchetti, S. G., Cumby, R. E., Figlewski, S. (1988). Estimation of the optimal futures hedge. The Review of Economics and Statistics, 70(4), 623–630.CrossRefGoogle Scholar
  9. Chance, D., & Brooks, R. (2010). Introduction to derivatives and risk management. Cengage LearningGoogle Scholar
  10. Cheung, Yin-Wong, Chinn Menzie, D., & Marsh, Ian W. (2004). How do UK-based foreign exchange dealers think their market operates? International Journal of Finance and Economics., 9(4), 289–306.CrossRefGoogle Scholar
  11. Cheung, Yin-Wong, & Wong, C. Y. P. (2000). A survey of market practitioners’ views on exchange rate dynamics. Journal of International Economics, 51(2), 401–419.CrossRefGoogle Scholar
  12. Cornell, B., & French, K. R. (1983). The pricing of stock index futures. Journal of Futures Markets, 3(1), 1–14.CrossRefGoogle Scholar
  13. Cumming, D., Johan, S., & Li, D. (2011). Exchange trading rules and stock market liquidity. Journal of Financial Economics, 99(3), 651–671.CrossRefGoogle Scholar
  14. Dempster, M. A. H., & Jones, C. M. (2001). A real-time adaptive trading system using genetic programming. Quantitative Finance., 1(2001), 397–413.CrossRefGoogle Scholar
  15. Er, H., & Hushmat, A. (2012). The impact of the leverage provided by the futures on the performance of technical indicators: Evidence from Turkey. International Journal of Economics and Finance Studies., 4(2), 2012.Google Scholar
  16. Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417.CrossRefGoogle Scholar
  17. Figlewski, S. (1984). Hedging performance and basis risk in stock index futures. The Journal of Finance, 39(3), 657–669.CrossRefGoogle Scholar
  18. Figlewski, S. (1985). Hedging with stock index futures: Theory and application in a new market. Journal of Futures Markets, 5(2), 183–199.CrossRefGoogle Scholar
  19. Frino, A., McInish, T. H., & Toner, M. (1998). The liquidity of automated exchanges: New evidence from German Bund futures. Journal of International Financial Markets, Institutions and Money, 8(3), 225–241.CrossRefGoogle Scholar
  20. Gehrig, Thomas, & Menkhoff, Lukas. (2006). Extended evidence on the use of technical analysis in foreign exchange. International Journal of Finance and Economics., 11, 327–338.CrossRefGoogle Scholar
  21. Holland, J. H. (1962). Outline for a logical theory of adaptive systems. Journal of the ACM (JACM), 9(3), 297–314.CrossRefGoogle Scholar
  22. Holmes, P. (1996). Stock index futures hedging: hedge ratio estimation, duration effects, expiration effects and hedge ratio stability. Journal of Business Finance and Accounting, 23(1), 63–77.CrossRefGoogle Scholar
  23. Hull, J. C. (2009). Options, futures, and other derivatives. NJ: Pearson Education.Google Scholar
  24. Ko, K. C., Lin, S. J., Su, H. J., & Chang, H. H. (2014). Value investing and technical analysis in Taiwan stock market. Pacific-Basin Finance Journal, 26, 14–36.CrossRefGoogle Scholar
  25. Koza, J. R. (1992). Genetic programming: on the programming of computers by means of natural selection (Vol. 1). MIT press.Google Scholar
  26. Koza, J. R, Goldberg D., Fogel D., & Riolo R. (1996). Proceedings, first annual conference on genetic programming, MIT Press, MA, USA.Google Scholar
  27. Krausz, J., Lee, S. Y., & Nam, K. (2009). Profitability of nonlinear dynamics under technical trading rules: Evidence from Pacific Basin Stock markets. Emerging Markets Finance and Trade, 45(4), 13–35.CrossRefGoogle Scholar
  28. Lafuente, J. A., & Novales, A. (2003). Optimal hedging under departures from the cost-of-carry valuation: Evidence from the Spanish stock index futures market. Journal of Banking & Finance, 27(6), 1053–1078.CrossRefGoogle Scholar
  29. Lintner, J. (1965). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. The review of economics and statistics, 47(1), 13–37.CrossRefGoogle Scholar
  30. MacKinlay, A. C., & Ramaswamy, K. (1988). Index-futures arbitrage and the behavior of stock index futures prices. Review of Financial Studies, 1(2), 137–158.CrossRefGoogle Scholar
  31. Menkhoff, L., & Schmidt U. (2005). The use of trading strategies by fund managers: Some first survey evidence. Applied Economics, 37(15), 1719–1730.Google Scholar
  32. Menkhoff, L. (2010). The use of technical analysis by fund managers: International evidence. Journal of Banking & Finance, 34(11), 2573–2586.CrossRefGoogle Scholar
  33. Moosa, I., & Li, L. (2011). Technical and fundamental trading in the Chinese stock market: Evidence based on time-series and panel data. Emerging markets finance and trade, 47(sup1), 23–31.CrossRefGoogle Scholar
  34. Mossin, J. (1966). Equilibrium in a capital asset market. Econometrica, 34(4), 768–783.CrossRefGoogle Scholar
  35. Mullins, D. W. (1982). Does the capital asset pricing model work? Harvard Business Review, 60(1), 105–114.Google Scholar
  36. Mulvey, J. M., & Kim, W. C. (2008). Active equity managers in the US: Do the best follow momentum strategies? The Journal of Portfolio Management, 34(2), 126–134.CrossRefGoogle Scholar
  37. Park, C. H., & Irwin, S. H. (2007). What do we know about the profitability of technical analysis? Journal of Economic Surveys, 21(4), 786–826.CrossRefGoogle Scholar
  38. Pirrong, C. (1996). Market liquidity and depth on computerized and open outcry trading systems: A comparison of DTB and LIFFE bund contracts. Journal of Futures Markets, 16(5), 519–543.CrossRefGoogle Scholar
  39. Qu, H., & Li, X. (2014). Building technical trading system with genetic programming: A new method to test the efficiency of Chinese stock markets. Computational Economics, 43(3), 301–311.CrossRefGoogle Scholar
  40. Richie, N., Daigler, R. T., & Gleason, K. C. (2008). The limits to stock index arbitrage: Examining S&P 500 futures and SPDRs. Journal of Futures Markets, 28(12), 1182–1205.CrossRefGoogle Scholar
  41. Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance., 19, 425–442.Google Scholar
  42. Taylor, M. (2000). The Use of Technical Analysis in the London Stock Market. INQUIRE (Institute for Quantitative Investment Research) September 2000 conference, Gleneagles Hotel, Scotland, UKGoogle Scholar
  43. Tian, G. G., Wan, G. H., & Guo, M. (2002). Market efficiency and the returns to simple technical trading rules: new evidence from US equity market and Chinese equity markets. Asia-Pacific Financial Markets, 9(3–4), 241–258.CrossRefGoogle Scholar
  44. Tse, Y., & Zabotina, T. V. (2001). Transaction costs and market quality: Open outcry versus electronic trading. Journal of Futures Markets, 21(8), 713–735.CrossRefGoogle Scholar
  45. Vickers, D. (1994). Economics and the antagonism of time: Time, uncertainty, and choice in economic theory. University of Michigan Press.Google Scholar
  46. Wang, J. J., Wang, J. Z., Zhang, Z. G., & Guo, S. P. (2012). Stock index forecasting based on a hybrid model. Omega, 40(6), 758–766.CrossRefGoogle Scholar
  47. White, H. (2000). A reality check for data snooping. Econometrica, 68(5), 1097–1126.CrossRefGoogle Scholar
  48. Yadav, P. K., & Pope, P. F. (1990). Stock index futures arbitrage: International evidence. Journal of Futures Markets, 10(6), 573–603.CrossRefGoogle Scholar
  49. Yadav, P. K., & Pope, P. F. (1994). Stock index futures mispricing: Profit opportunities or risk premia? Journal of Banking & Finance, 18(5), 921–953.CrossRefGoogle Scholar
  50. Yang, W., & Allen, D. E. (2005). Multivariate GARCH hedge ratios and hedging effectiveness in Australian futures markets. Accounting and Finance, 45(2), 301–321.CrossRefGoogle Scholar

Copyright information

© Eurasia Business and Economics Society 2016

Authors and Affiliations

  1. 1.Department of Business AdministrationAkdeniz UniversityAntalyaTurkey

Personalised recommendations