2016/08/11 by Atul Deshpande, Deshpande, Atul, B. Ross Barmish +1
Decision Sciences · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #Computational Finance (q-fin.CP) #FOS: Economics and business #Financial Markets and Investment Strategies #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods
paper · pdf · doi:10.48550/arxiv.1608.03636
openalex publication_date 2016/08/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Pairs trading is a market-neutral strategy that exploits historical\ncorrelation between stocks to achieve statistical arbitrage. Existing\npairs-trading algorithms in the literature require rather restrictive\nassumptions on the underlying stochastic stock-price processes and the\nso-called spread function. In contrast to existing literature, we consider an\nalgorithm for pairs trading which requires less restrictive assumptions than\nheretofore considered. Since our point of view is control-theoretic in nature,\nthe analysis and results are straightforward to follow by a non-expert in\nfinance. To this end, we describe a general pairs-trading algorithm which\nallows the user to define a rather arbitrary spread function which is used in a\nfeedback context to modify the investment levels dynamically over time. When\nthis function, in combination with the price process, satisfies a certain\nmean-reversion condition, we deem the stocks to be a tradeable pair. For such a\ncase, we prove that our control-inspired trading algorithm results in positive\nexpected growth in account value. Finally, we describe tests of our algorithm\non historical trading data by fitting stock price pairs to a popular spread\nfunction used in literature. Simulation results from these tests demonstrate\nrobust growth while avoiding huge drawdowns.\n