118 lines
6.7 KiB
Markdown
118 lines
6.7 KiB
Markdown
# Backtesting + Optuna + MT5-Verification Stack — Knowledge Base
|
||
|
||
A blueprint for building a **personal trading-strategy research lab**: a fast Python
|
||
backtesting engine, a Bayesian parameter optimizer (Optuna), and an automated bridge to the
|
||
**MetaTrader 5 Strategy Tester** that cross-checks every result against the real terminal.
|
||
|
||
This is a **knowledge base, not a code drop.** It describes the *architecture, algorithms, rules,
|
||
and tooling* so you can build your own version from scratch — with **your own** Expert Advisors,
|
||
**your own** strategies, and **your own** presets. There are no ready-made engines or strategy
|
||
files here on purpose: you supply those from your own MQL5 bots (ideally open-source EAs you own
|
||
or have the right to use).
|
||
|
||
---
|
||
|
||
## What this stack does for you
|
||
|
||
You have MQL5 Expert Advisors and a pile of ideas to test. The MetaTrader Strategy Tester is
|
||
accurate but **slow** — a single multi-year backtest with a real-tick model can take 10–30 minutes,
|
||
and an exhaustive optimization can run for days. That kills iteration speed.
|
||
|
||
This stack solves it with a **two-tier model**:
|
||
|
||
1. **Tier 1 — a fast Python "mirror engine"** that reproduces your EA's trade logic bar-by-bar over
|
||
pre-downloaded historical data. It is an *approximation* (more on fidelity below), but it runs a
|
||
full multi-year backtest in **seconds**, so you can rank thousands of parameter combinations with
|
||
Optuna in the time MT5 would run a handful.
|
||
|
||
2. **Tier 2 — MetaTrader 5 as the gold standard.** Only the **finalists** from the Python search are
|
||
compiled and run in the real Strategy Tester. The Python number gets you the *shortlist*; the MT5
|
||
number is what you trust for anything that goes live.
|
||
|
||
```
|
||
Idea ─► Python mirror engine ─► Optuna search (thousands of trials, fast)
|
||
│
|
||
▼
|
||
2–3 diverse finalists
|
||
│
|
||
▼
|
||
MetaTrader 5 Strategy Tester (gold standard)
|
||
│
|
||
▼
|
||
Python-vs-MT5 comparison table ─► keep / discard / iterate
|
||
```
|
||
|
||
The whole point is **disciplined isolation**: the engine is frozen and trusted, instruments are
|
||
described by data not code, every hypothesis is an isolated experiment, and only triple-checked
|
||
results are promoted. That discipline is what keeps a research lab from rotting into a pile of
|
||
one-off scripts that nobody can reproduce.
|
||
|
||
---
|
||
|
||
## Who this is for
|
||
|
||
- You run **MetaTrader 5** and write or use **MQL5** Expert Advisors.
|
||
- You want to test and optimize strategies **much faster** than the MT5 optimizer allows.
|
||
- You are comfortable with **Python** (intermediate) and the command line.
|
||
- You can run **MT5 on Windows** — either on the same machine (simplest) or on a separate
|
||
Windows box/VPS that your Python machine talks to.
|
||
|
||
You do **not** need to be a quant. The hard parts (engine fidelity, Bayesian search, robustness
|
||
testing) are explained from first principles.
|
||
|
||
---
|
||
|
||
## How to read this KB
|
||
|
||
Start with `CLAUDE.md` if you plan to use an AI coding assistant (Claude Code, Cursor, etc.) to
|
||
build this with you — it is an **adaptive setup playbook** that profiles *your* machine and OS and
|
||
walks the install from zero. Otherwise read the numbered docs in order:
|
||
|
||
| # | Doc | What you get |
|
||
|---|-----|--------------|
|
||
| — | [`CLAUDE.md`](CLAUDE.md) | Adaptive AI-assistant playbook: profiles your device, drives install from scratch. Doubles as `AGENTS.md`. |
|
||
| 01 | [`01-stack-and-install.md`](01-stack-and-install.md) | The exact tech stack, every library, where to get it, and how to install — per OS. |
|
||
| 02 | [`02-architecture.md`](02-architecture.md) | The layered architecture and data flow. The mental model for everything else. |
|
||
| 03 | [`03-engine-design.md`](03-engine-design.md) | How to design your own bar-by-bar engine. Grid logic used as the worked example. Fidelity vs MT5. |
|
||
| 04 | [`04-isolation-rules.md`](04-isolation-rules.md) | The isolation discipline: frozen engines, forks, separated instruments/strategies, curated registry. |
|
||
| 05 | [`05-config-and-inputs.md`](05-config-and-inputs.md) | How test inputs are kept *separate*: instrument config, parameter space, the pre-run wizard, lot/money mode. |
|
||
| 06 | [`06-optimization-and-robustness.md`](06-optimization-and-robustness.md) | Optuna objective design, constraints, diverse top-N selection, and anti-overfit robustness layers. |
|
||
| 07 | [`07-mt5-bridge.md`](07-mt5-bridge.md) | Connecting to MT5: compiling EAs, auto-running the tester, parsing reports, comparing Python vs MT5. Local-Windows and remote variants. |
|
||
| 08 | [`08-workflow-cycle.md`](08-workflow-cycle.md) | The full repeatable cycle: hypothesis → scaffold → stats → optimize → verify → promote. |
|
||
|
||
---
|
||
|
||
## The 30-second mental model
|
||
|
||
- **The engine knows nothing about your strategy.** It takes bars + entry signals + stop/target
|
||
prices and simulates fills. All strategy math lives in *caller* code. (Doc 02–03.)
|
||
- **The engine is frozen.** You never edit a validated engine to test an idea — you fork it,
|
||
prove the fork reproduces the original 1:1 with the change off, then test. (Doc 04.)
|
||
- **Instruments are data, not code branches.** Tick value, spread model, swap, lot steps — all in a
|
||
per-symbol config object. The engine reads everything from it. (Doc 05.)
|
||
- **Search inputs are declared, not scattered.** Every tunable parameter, its range, and its
|
||
constraints live in one declared search space; one wizard captures the run settings; one YAML
|
||
records the answers so any run is reproducible. (Doc 05–06.)
|
||
- **Python ranks, MT5 decides.** Fast Python search produces a shortlist; MT5 produces the trusted
|
||
number; a comparison table is saved for every finalist. (Doc 03, 06, 07.)
|
||
|
||
---
|
||
|
||
## What you must bring yourself
|
||
|
||
This KB is deliberately empty of trading IP. To build a working lab you supply:
|
||
|
||
- **Your MQL5 EA(s)** — compiled `.ex5` plus source `.mq5`, and any custom indicators they call.
|
||
- **Your strategy logic** — encoded once in Python (the caller) so the mirror engine can run it.
|
||
- **Your presets** — the `.set` files / input templates you want to test and optimize.
|
||
- **Historical data** — downloaded from your broker via MT5 (the stack includes a recipe).
|
||
- **A broker demo account** — for the MT5 Strategy Tester runs.
|
||
|
||
Everything else — the architecture, the optimizer, the MT5 bridge, the robustness checks, and the
|
||
rules that hold it together — is described in the docs above.
|
||
|
||
---
|
||
|
||
*This KB is brand-free and self-contained. Drop the folder into a Git repository, open it with your
|
||
AI coding assistant, and build your own lab.*
|