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

Er H., Hushmat A.

EURASIAN BUSINESS REVIEW, cilt.7, sa.3, ss.313-353, 2017 (SSCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7 Sayı: 3
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1007/s40821-016-0056-2
  • Dergi Adı: EURASIAN BUSINESS REVIEW
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.313-353
  • Anahtar Kelimeler: Futures, CAPM, Technical indicators, Artificial intelligence, Emerging markets, Neural networks, Genetic programming, STOCK INDEX FUTURES, INTERNATIONAL EVIDENCE, FOREIGN-EXCHANGE, FUND MANAGERS, OPEN OUTCRY, RISK, ARBITRAGE, PROFITABILITY, EQUILIBRIUM, STRATEGIES
  • Akdeniz Üniversitesi Adresli: Evet

Özet

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.