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.
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Figlewski (1984, 1985), Holmes (1996), Butterworth and Holmes (2001), Lafuente and Novales (2003) and Yang and Allen (2005) are among the many studies on the hedging effectiveness of the SIFs. Cornell and French (1983), MacKinlay and Ramaswamy (1988), Yadav and Pope (1990, 1994), Butterworth and Holmes (2001) and Richie et al. (2008) are examples of the vast literature on SIF arbitrage.
The markets selected are US, UK, Australia, Germany, and Hong Kong, China, South Korea, India, Mexico and Turkey. They are among the most important financial markets in the developed and emerging economies.
EMH (Fama 1970) has been one of building blocks of finance theory over the past four decades. It describes an efficient market as a market where all the prices reflect their investment value. Market efficiency was later classified into three forms: weak-form efficiency, semi-strong-form efficiency and strong-form efficiency. In a market where information is cheaply and widely available to all the investors, the prices should reflect all the information available as investors are assumed to respond instantaneously to any new information arriving to the market.
In “Appendix 1”, the trading volumes of the spot and futures that are included in our sample are presented in a table. In 2014, in eight countries included in our sample, trading volumes in futures markets are higher than spot market volumes. Only in Turkey and Australia, spot market volumes exceed those of futures markets.
The countries are classified on the basis of MSCI Inc. classification.
Based on the Market Capitalization Monthly Report of World Federation of Exchanges-October 2015.
Based on the statistics issued by World Federation of Exchanges on January 31, 2015.
The samples of stocks selected from other markets also include a similar mixture of stocks. They are not shown here due to space constraints.
We assume that we invest in local risk-free securities when we are out of market.
Transaction cost in spot market is assumed to be 0.1 % per transaction for all the exchanges.
To avoid spurious regression, all the return series are tested for unit root using ADF (Augmented Dickey Fuller) unit root test. All the series meet stationarity condition. The unit root test results and regression results are not shown here because of space constraints; and can be provided if required.
Margin requirement in futures is assumed to be 10 % of the transaction amount for all the markets.
Even though validity of using CAPM to examine whether forecasters are successful in their market-timing activity is theoretically questionable, CAPM is also used to evaluate portfolio performance in active portfolio management and market timing studies.
The detailed results for all the stocks are not presented here due to space constraints.
Again, the detailed results for all the stocks are not presented here due to space constraints.
The results are not shown here due to space constraints and can be provided upon request.
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Er, H., Hushmat, A. The application of technical trading rules developed from spot market prices on futures market prices using CAPM. Eurasian Bus Rev 7, 313–353 (2017). https://doi.org/10.1007/s40821-016-0056-2
- Technical indicators
- Artificial intelligence
- Emerging markets
- Neural networks
- Genetic programming