Algorithm
development.
Your trading strategy as a finished algorithm — built and validated to standards made for real live trading.
Four platforms, built natively.
No lowest common denominator — full use of each platform API. Always delivered with source code and documentation.
MT5 Expert Advisors
MQL5 · .ex5 + source + docs
The execution layer for live and prop accounts (FTMO etc.): validated rule sets as fully automated EAs — with integrated risk management, DST-safe session logic and behavior that matches the backtest 1:1.
- ·Expert Advisors (EAs)
- ·Custom indicators
- ·Backtesting & optimization
- ·Position sizing & risk management
Pine Script Strategies
Pine Script v5 · Pine code + guide
The chart cockpit for discretionary decisions: making setups, session levels and context (e.g. dealer gamma) visible, with alerts instead of constant screen time — clean, multi-timeframe and guaranteed free of repaint tricks.
- ·Pine Script v5
- ·Overlay & panel indicators
- ·Alert systems
- ·Multi-timeframe analysis
cTrader cBots
C# (.NET) · cBot + source code
The choice for full execution control: cBots in C# with direct access to the order API — fine-grained order logic, clean architecture, complete logging so every fill is traceable.
- ·Automated cBots
- ·Custom indicators
- ·API integrations
- ·Portfolio management
Python & Research
Python 3.x · Scripts + documentation
The research and validation layer everything else stands on: backtesting pipelines, data engineering, walk-forward and Monte Carlo validation — the machinery behind every research paper on this site.
- ·Backtesting frameworks
- ·Broker & data API integration
- ·Data analysis & ML
- ·Walk-forward & Monte Carlo
The approach — and why the result holds.
Most trading systems fail not on the idea but on weak validation. A backtest on coarse data with optimistic fills almost always produces a pretty curve — the very one that falls apart in a real account. The approach flips that: before a strategy counts as good, every effort is made to break it.
- 01
Refute first, then trust. Every strategy is deliberately attacked — across data, parameters and market regimes. What survives may go live.
- 02
Costs from the start. Spread and slippage are in every metric. What only works gross does not work.
- 03
Real data. Tick/M1 data straight from the broker, quote origin checked — no fill that never existed.
- 04
Out-of-sample & walk-forward. Optimized on one window, tested on the next unseen one — rolling over years.
- 05
Monte Carlo & regimes. Trade order, parameter sensitivity, crash, bear and chop — not just the one good year.
- 06
Lean logic, clean code, hard risk. Clear rules over optimized indicator stacks; logging, configurable parameters, position sizing, stop & drawdown limits built in.
- 07
Live-forward is the only truth. Every backtest comes from known data — and edges decay. This is stated openly instead of hidden.
From request to delivery.
From first request to delivery — five clear steps with timelines. The methodology above lives in step 4.
Initial consultation & analysis
1–2 days
Clarify strategy, requirements and fit for automation — free and honest. If an idea will not hold, that is said up front.
Concept & specification
2–3 days
Precise entry/exit/risk rules in writing — approved before a single line of code.
Development
1–4 weeks
Clean, maintainable code with logging and configurable parameters, with regular progress updates.
Validation
3–5 days
The strategy runs the full validation protocol (see Methodology above) — what fails here does not go live.
Delivery & support
30 days support
Finished algorithm + source code, documentation, install help and 30 days of support.
First call free.
Analyze requirements, get an honest assessment — whether and how your strategy can be automated.
Get in touchPast results are not indicative of future performance. All algorithms are delivered with documented backtests.