Trading Strategy Overfitting
Quantifying how much of the backtest is search bias rather than edge.
A backtest is easy to pass and hard to trust. The interesting question is never the equity curve — it is how much of that curve survives out-of-sample data, realistic costs, and parameter perturbation. That is what we test for.
On a trading strategy overfitting engagement this means starting from what you already have — an idea, a spreadsheet, a running system, or a set of results that do not add up — and working from there rather than insisting on a rebuild. Where the honest answer is that the work is not worth doing, that is what you will be told.
What you get
- Event-driven backtests that model fills, spread, slippage and financing
- Walk-forward and out-of-sample protocols designed before results are seen
- Monte Carlo and sensitivity analysis on parameters and trade ordering
- A written verdict, including when the honest answer is that the edge is not there
How the work runs
Scope
A short call and a written scope: what the system must do, what data it needs, what counts as done. Fixed price where the scope allows it.
Build
Work in reviewable increments, with running code you can see rather than a status update. Assumptions are surfaced as they arise, not at the end.
Test
Independent testing against the acceptance criteria agreed in the scope, including the failure cases.
Handover
Source code, documentation and a walkthrough. You own the result and can maintain it without us.
Tell us what you are trying to build
Describe the problem and we will tell you plainly whether we can help, roughly what it would take, and what it would cost. If it is not a fit, we will say so.
Test My Strategy