Trading robots and advisors
Logic, parameters, code and metrics of each advisor — together with the method of testing it before real money.
A robot does not remove risk — it merely executes given rules without emotion. So each write-up states in which conditions the algorithm degrades and which loss limits to set before launch.
ScalperX Pro
A high-frequency scalper on an EMA ribbon with a volume filter and execution latency under 20 ms.
View the breakdown →TrendRider EA
A classic trend-following EA on the EMA50/EMA200 crossover with an ATR trailing stop.
View the breakdown →GridMaster FX
A grid EA with an ATR-adaptive step and a strict level limit.
View the breakdown →NewsHunter Bot
A straddle EA trading volatility around macroeconomic data releases.
View the breakdown →QuantArb Engine
A triangular arbitrage engine with direct access to multiple venues.
View the breakdown →RangeBreaker
An EA that breaks out of the session opening range with a volume filter.
View the breakdown →PairsBalancer
Statistical pairs arbitrage based on cointegration and the spread z-score.
View the breakdown →SafeMartin Lite
A softened martingale with a strict step limit and an emergency stop of the series.
View the breakdown →MultiSignal Bot
An ensemble of three independent signals with voting and risk-parity weighting.
View the breakdown →VWAP Reversion Bot
An intraday VWAP-reversion EA with a time stop and a volatility filter.
View the breakdown →Testing advisors
Three mandatory testing stages before real money:
- Backtest — a run on historical data with realistic costs.
- Forward test — live operation on a demo account without intervention.
- Optimization — parameter tuning with a mandatory out-of-sample check against overfitting.
Common mistakes when building robots
- Overfitting parameters to a specific historical period.
- Look-ahead bias — using data in the signal that was not available at decision time.
- Ignoring costs: spread, commission, slippage.
- No limit on daily or weekly loss.