Combining Futures Fundamentals with Quantitative Trading Logic
Summary
This profile follows a quantitative trader’s shift from intraday models toward medium-frequency futures strategies grounded in industry knowledge. He argues that statistical relationships alone can be fragile: attractive historical fits may reflect correlation rather than causation, and a holdout period from the same historical dataset does not establish real out-of-sample performance. Live trading is the more meaningful test.
The approach combines fundamental supply-and-demand reasoning with quantitative analysis and execution. For example, tight coke inventories, strong demand, and futures trading below elevated spot prices supported a bullish view. Relative value between steel and its inputs can also be analyzed through steel mill margins and the production response to profits or losses. The account describes adapting models during the 2015 market turmoil and emphasizes checking both supporting and opposing explanations before trading.
These are practitioner observations, not a controlled performance study. The document gives no reproducible strategy specification or systematic results, and its examples do not establish that fundamental logic will remain predictive. It also stresses ongoing research and risk awareness as market conditions change.
Key ideas
- Historical correlations can produce attractive backtests without a durable causal explanation.
- Real market deployment provides a stronger test than dividing historical data into training and test periods.
- Industry knowledge can guide futures models by explaining supply, demand, inventories, and production incentives.
- Relative value between a commodity and its inputs can be assessed through producer margins.
- Trading decisions benefit from weighing opposing explanations and adapting when market conditions shift.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.