Pairs trading using cointegration for an investment bank

Categories: Financial Services
  • Situation

    An American investment bank pulled out from its physical commodity trading activity due the new regulation. Its proprietary trading desk was given the task of expanding its trading activities to cover commodity futures contracts.

  • Complication
    In the absence of asset-backed trading, commodity price risk can represent a major challenge. Statistical arbitrage strategies are an alternative but they also come with a sizable risk. The client was open to trial new strategies that prove to be profitable with a limited downside risk.
  • Solution
    We designed and implemented a cross-commodity trading strategy that had a well thought-over set of risk management rules. The strategy was thoroughly back-tested on commodity futures contracts spanning the period of 2013-2014. The strategy yielded a Sharpe ratio of 1.54
[title_pink bottom_margin="20" small_text=""]More details[/title_pink] [accordion style="2"] [toggle title="Pairs trading strategies"][row]
  Pairs trading strategies are market-neutral long/short trading strategies designed to exploit short-term deviations from a long-run equilibrium pricing relationship between two assets. Typical pairs trading strategies include:
[list_arrow][item]Fundamentally-driven strategies (e.g. going short overvalued assets and long undervalued ones)[/item][item]Statistical arbitrage convergence/divergence strategies that are based on correlation and other non-parametric decision rules[/item][/list_arrow]
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Why co-integration is more relevant than correlation?
[/row] [/toggle] [toggle title="Why co-integration is more relevant than correlation"] [row] graph1-small   Co-integration is not the same as correlation:
[list_arrow][item]Standard correlation estimation methods induce an apparent stability that is purely an artifact of the method, while the true nature of underlying dependency is obscured.[/item][item]Unlike correlation, co-integration refers not to co-movements in returns, but to co-movements in raw asset prices.[/item][item]If spreads are mean reverting, then asset prices are tied together in the long term by some common stochastic trend, and we say the asset prices are co-integrated.[/item][/list_arrow]
[/row] [/toggle] [toggle title="How to design co-integration trading strategies?"][row]

Typical questions which must be answered when developing a pairs trading strategy include:

From a risk management perspective, it is also important to specify maximum allowable time to maintain open trading positions, maximum allowable Value at Risk (VaR), and further possible risk reducing measures such as stop-loss triggers.

How to select winning pairs using co-integration?
[/row] [/toggle] [toggle title="How to select winning pairs using co-integration?"][row]

We use the Johansen test for co-integration to select trading pairs:

What are the criteria for selecting winning pairs?

We focus on trading pairs exhibiting:

How to select the investment space?
[/row] [/toggle] [toggle title="How to select the investment space?"][row]
What are the main risks involved?
[/row] [/toggle] [toggle title="What are the main risks involved?"][row]

The main risk exposure to commodity specific events:

How to define successful trading rules?
[/row] [/toggle] [toggle title="How to define successful trading rules?"][row]

Trading and risk management rules should be defined and adhered to as follows:

How to back-test the strategy?
[/row] [/toggle] [toggle title="How to back-test the strategy?"] [row]
[su_list icon="icon: arrow-circle-right" icon_color="#110d5a"]
    Strategies should not only be back-tested against historical data but also through a forward looking approach based on simulations:
  • Simulation should preserve the dynamics of the underlying commodities, namely, mean-reversion, seasonality, auto-correlation.
  • The resulting spread should be comparable to the historical spread.
  • Running the strategy on simulated paths should take into account realistic market frictions : bid-ask spread, transaction costs, public holidays, liquidity and so on.
Does it work?
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How we can help
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    We have the skills and experience to support you in:
[list_arrow][item]Designing tailored co-integration trading strategies.[/item][item]Implementing such strategies in various programming languages (e.g. C++, Python, Matlab) and interfacing them with your trading system[/item][item]Designing comprehensive back-testing framework for your trading strategies using both historical and forward looking (simulations) approaches[/item] [item]Providing advice in other quantitative trading strategies[/item][/list_arrow]
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