Abstract
The main goal of the paper is to introduce different models to calculate the amount of money that must be allocated to each stock in a statistical arbitrage technique known as pairs trading. The traditional allocation strategy is based on an equal weight methodology. However, we will show how, with an optimal allocation, the performance of pairs trading increases significantly. Four methodologies are proposed to set up the optimal allocation. These methodologies are based on distance, correlation, cointegration and Hurst exponent (mean reversion). It is showed that the new methodologies provide an improvement in the obtained results with respect to an equal weighted strategy.
Highlights
Efficient Market Hypothesis (EMH) is a well-known topic in finance
For testing the results through the different models introduced in this paper, we will use the components of the Nasdaq 100 index technological sector,for the period between January 1999 and December 2003, coinciding with the “dot.com” bubble crash and the period between January 2007 and December 2012, this period coincides with the financial instability caused by the “subprime” crisis
If we compare the Equal weight (EW) method with the other methods proposed we obtain the following: minimal Hurst exponent is better than EW in 58% of the cases, minimal distance is better than EW in 58% of the cases, correlation is better than EW in 67% of the cases, cointegration is better than EW in 58% of the cases and volatility is better than EW in 50% of the cases
Summary
Efficient Market Hypothesis (EMH) is a well-known topic in finance. An investor in an efficient market will not be able to obtain a significant advantage over a benchmark portfolio or a market index trading based on historical data (for a review see Reference [1,2]). Some researchers have shown that the use of historical data as well as trading techniques is sometimes possible due to temporal markets anomalies. Despite that most of economists consider that these anomalies are not compatible with an efficient market, recent papers have shown new perspectives called Fractal Market Hypothesis (FMH) and Adaptive Market Hypothesis (AMH), that tries to integrate market anomalies into the efficient market hypothesis. The EMH was questioned by the mathematician Mandelbrot in 1963 and after the economist
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