Intraday pairs trading strategies on high frequency data: the case of oil companies

DOI10.1080/14697688.2016.1184304zbMath1402.91717OpenAlexW2411480806MaRDI QIDQ4555060

Hélyette Geman, Lo-Bin Chang, Bo Liu

Publication date: 19 November 2018

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://eprints.bbk.ac.uk/id/eprint/15328/1/15328.pdf

zbMATH Keywords

transaction costshigh frequency datapairs tradingquantitative trading strategiesconditional modellingdoubly mean-reverting model

Mathematics Subject Classification ID

Portfolio theory (91G10)

Related Items (7)

Bertram's pairs trading strategy with bounded risk ⋮ Pairs trading with a mean-reverting jump–diffusion model on high-frequency data ⋮ Analytic value function for a pairs trading strategy with a Lévy-driven Ornstein–Uhlenbeck process ⋮ Revealing pairs-trading opportunities with long short-term memory networks ⋮ Exploiting social media with higher-order Factorization Machines: statistical arbitrage on high-frequency data of the S&P 500 ⋮ A flexible regime switching model with pairs trading application to the S&P 500 high-frequency stock returns ⋮ A CLOSED-FORM SOLUTION FOR OPTIMAL ORNSTEIN–UHLENBECK DRIVEN TRADING STRATEGIES

Uses Software

• LBFGS-B

Cites Work

• Loss protection in pairs trading through minimum profit bounds: A cointegration approach
• Empirical scaling laws and the aggregation of non-stationary data
• Maximum likelihood features for generative image models
• Statistical arbitrage in the US equities market
• Empirical properties of asset returns: stylized facts and statistical issues
• A Limited Memory Algorithm for Bound Constrained Optimization
• Pairs trading: optimal thresholds and profitability
• Pairs trading based on statistical variability of the spread process

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