Pairs Trading Using Fractional Cointegration Approach and Its Comparison with Cointegration Approach

Abstract

The objective of this research is to apply the recently developed fractional cointegration vector autoregressive (FCVAR) model in developing pairs trading model and compare the results to that of the cointegration approach. To the best of our knowledge, there are no papers on fractional cointegration approach to date. Hence, this paper would be the first practical research based on fractional cointegration on futures market.

As the focus of this paper in on short-term trading positions, minute intraday interval prices are used to estimate the model and execute the trading strategies. First, we form two portfolios, “FCI” and “CI”. FCI is created using fractional cointegration and CI using cointegration approach. Then, using an estimation window of specific length, fractional cointegration test and cointegration test are preformed to verify the existence of fractional cointegration and cointegration relationship between the selected pair respectively. At last, the long-term equilibrium is estimated using Fractional Vector Error Correction Model (FVECM) for FCI and Vector Error Correction Model (VECM) for CI and based on this estimation the trading strategy is implemented.

The results show that the fractional cointegration approach yields statistically significant higher returns than the cointegration approach. The number of trades is also lower for fractional cointegration approach, which further contributes to the performance of the strategy. Finally, on a risk-adjusted level, the fractional cointegration approach has a higher Sortino ratio compared to the cointegration approach.

Furthermore, window sizes are optimized and the best and worst window sizes for both the cointegration and fractional cointegration estimation window and trading window is reported.

Keywords: Pairs Trading, Fractional Cointegration, Fractional Vector Error Correction Model, Mean Reversion

JEL Classification: G11, G12, G14