Basis Trade

A basis trade seeks to profit from the difference between the spot price of an asset and its futures price, known as the basis. The strategy relies on convergence between spot and futures prices as the contract approaches expiration.

How It Works

The goal is to capture the change in basis, not a directional move in the underlying.

Use Cases

Basis trades are common in commodities, fixed income, and equity index futures. They are used by arbitrageurs and by institutions seeking to lock in funding or carry advantages.

Risks

Key risks include funding costs, margin requirements, delivery constraints, and changes in the basis due to liquidity or credit stress. Execution costs and borrowing availability can also affect profitability.

Edge Sources

Strategies seek an edge from structural effects, behavioral biases, risk premia, or informational advantages. A clear statement of the edge helps determine where and when the strategy should work.

The edge should be tested across multiple market regimes to avoid overreliance on a narrow historical period.

Process and Workflow

A disciplined workflow typically includes signal generation, risk checks, execution planning, and post trade review. Each step should be standardized to reduce discretionary errors.

Automation can improve consistency, but manual oversight is still important when market conditions change.

Risk Controls

Key controls include position sizing, stop placement, and exposure limits by asset or factor. Risk should be expressed in both price and dollar terms to avoid surprises.

Scenario analysis is useful for understanding the impact of gaps, volatility spikes, and liquidity shocks.

Costs and Capacity

Transaction costs, slippage, and financing can erode expected returns. The strategy should be tested with realistic cost assumptions and with an estimate of capacity.

A strategy that works at small size may fail at scale if liquidity is limited.

Evaluation

Evaluate performance using risk adjusted metrics such as Sharpe, drawdown, and hit rate. Stability of returns and adherence to the strategy rules are as important as headline profit.

Example Scenario

Consider a liquid instrument with stable spreads and average volatility. A rule based implementation can be tested on a multi year sample and then on an out of sample period. The goal is to verify that the behavior of Basis Trade is consistent across regimes and that the edge does not depend on a narrow set of conditions.

Implementation Checklist

Operational Notes

Definitions and conventions should be consistent across datasets and venues. A small difference in data fields or session boundaries can change outcomes, especially for short term strategies. Document inputs and assumptions so results can be reproduced.

If the concept depends on exchange rules or broker behavior, confirm those rules for the specific venue. Operational details often explain why a trade behaved differently than expected.

Stress Scenarios

During volatility spikes, liquidity can evaporate and price gaps can appear. Under these conditions, indicators can lag, order types can misfire, and spreads can widen sharply.

Stress testing the concept against fast markets, thin liquidity, and sudden news helps reveal hidden risks. If a strategy only works in calm conditions, size and timing should reflect that.

Documentation Tips

Keep a short checklist of the rules, parameters, and decision points. Record how the concept is used in live trading and compare it to backtest assumptions. This makes future refinement easier and reduces drift in execution.

Common Questions

Traders often ask how sensitive results are to parameter choices, how the concept behaves in different regimes, and whether it scales with size. Answering these questions early improves reliability and prevents overfitting.

Checklist

Checklist

Checklist

Checklist