Artificial Trade Program analyzes historical price data across multiple timeframes and market regimes, then generates entry and exit signals with documented drawdown behavior. No discretionary overrides. No emotional exposure to the position.
The platform is built around a fixed process. Each stage removes a specific source of discretionary error from the execution chain.
The system processes tick-level and macro data in parallel, ranking signal quality by statistical significance rather than recency. Correlated inputs are discounted automatically to reduce redundant weighting.
Position sizing adjusts to realized volatility. Stop-loss levels are derived from historical maximum adverse excursion for each instrument, not from fixed percentage rules applied uniformly across markets.
The same underlying models run across single accounts and multi-strategy portfolios. No re-calibration is required when asset class, position size, or account structure changes.
Every strategy is tested against a minimum of ten years of historical data before deployment. Backtests include transaction costs, slippage assumptions, and out-of-sample validation periods that are excluded from model training.
Predictive accuracy and drawdown figures are published per strategy in the documentation, alongside sample size and testing period. Figures are updated after each model retraining cycle, not adjusted for marketing purposes.
The model does not run a single strategy. It selects and weights logic based on the measured state of the market at any given time.
When intraday range expands beyond historical norms, position sizing contracts automatically and signal thresholds tighten. This filters short-term noise from genuine directional moves and limits exposure during erratic price action.
In extended trends, the model extends holding periods and widens trailing stops based on measured trend persistence rather than fixed time exits. Positions are allowed to run as long as the underlying trend statistics hold.
Artificial Trade Program does not promise outsized returns. It is built to reduce the variance of trading outcomes by removing discretionary decisions from execution. Every signal is the output of a documented, testable process, not a forecast presented as certainty.
Strategy logic, backtest parameters, and known limitations are available in the documentation. Users are expected to review methodology and constraints before allocating capital.
Documentation includes backtest parameters, drawdown statistics, and current model constraints for each supported market.