Self-Generated Trading History as a Source of Statistical Edge

Summary

The paper argues that a trading strategy can improve its results by using its own historical trading information to decide whether new orders should execute. It presents this conditioning as necessary for a statistical edge and claims that, for a strategy that ignores its own trading history, a modified strategy can be constructed to improve profit and loss systematically under general conditions.

The authors formalize the idea with a decision mechanism and report simulations and real-world trading evidence as validation and illustration. The supplied description does not specify the mechanism's details, the assumptions precisely, or the settings and measurements behind the evidence. It therefore conveys a broad principle rather than enough information to assess implementation, costs, or how robust the claimed improvements are in particular markets.

Key ideas

• A strategy’s own historical trading information can inform whether its new orders execute.
• The paper presents conditioning order execution on that information as necessary for statistical edge.
• It claims a strategy using self-generated history can improve on one that does not, under general conditions.
• A decision mechanism, simulations, and real-world evidence are used to support the argument.

Tags

# On a fundamental statistical edge principle


# On a fundamental statistical edge principle









This paper establishes that conditioning the probability of execution of new orders on the self-generated historical trading information (HTI) of a trading strategy is a necessary condition for a statistical trading edge. It is shown, in particular, that, given any trading strategy S that does not use its own HTI, it is always possible to construct a new strategy S* that yields a systematically increasing improvement over S in terms of profit and loss (PnL) by using the self-generated HTI. This holds true under rather general conditions that are frequently met in practice, and it is proven through a decision mechanism specifically designed to formally prove this idea. Simulations and real-world trading evidence are included for validation and illustration, respectively.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.