Brent–WTI Spread Trading with Least-Squares Price Forecasting
Summary
The article introduces Brent and West Texas Intermediate (WTI), describing differences in crude quality, production geography, and access to transport. It then presents a classic spread-trading premise: deviations of the Brent–WTI price spread from a baseline may revert, creating possible trades in Brent. The author argues that changing oil markets motivate testing whether spread information relates to future Brent prices instead of relying only on the traditional mean-reversion rule.
The proposed supervised model uses historical Brent prices, the Brent–WTI spread, and an intercept as inputs, then fits coefficients with a least-squares objective calculated through a matrix pseudo-inverse. The article describes plotting the spread and implementing the calculations in MQL5, followed by a strategy-tester evaluation. It calls the strategy profitable but also reports irregular drawdown periods and volatile oil markets. The supplied text gives no detailed performance figures or test conditions, and it notes that other benchmarks, crack spreads, and stronger risk management could be investigated.
Key ideas
- Brent and WTI differ in crude properties and accessibility, factors relevant to their relative prices.
- A traditional spread strategy expects deviations from a baseline to move back toward equilibrium.
- The proposed supervised model uses Brent price history, the Brent–WTI spread, and an intercept to forecast Brent prices.
- A matrix pseudo-inverse provides least-squares coefficients by minimizing squared prediction errors.
- The reported backtest is described as profitable but subject to irregular drawdowns, with limited test detail in the supplied text.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.