Statistical, Quantitative & Machine Learning Algorithms

Uses a hybrid TCNN-LSTM neural network with attention mechanism to predict price direction and generate trading signals.

Uses LSTM-PPO reinforcement learning to trade XAUUSD via MetaTrader5.

Algorithm inspired by dingo hunting behavior, using group attack, chase, and scavenging strategies.

Combines neural network, evolutionary ensemble, and local rule engine for trading decisions.

Uses GARCH and LSTM to assess entry setups and their worthiness.

Optimization algorithm based on cricket behavior and sound propagation

Uses Sliding Window Median and Bidirectional LSTM for dynamic trailing stop adjustments in Z-type markets.

Uses ecological concepts to model the search for solutions in optimization problems.

Trades the previous-day high/low breakout on XAUEUR with a fixed lot size and target.

Uses Wavelet-Thresholding to clean log-returns and LSTM to interpret the cleaned data for dynamic lot sizing in volatile markets.

Neural network-based trading robot for XAUUSD with strict rules and institutional-grade execution.

Classifies market regime using ADX, Hurst exponent, and lag-1 autocorrelation, then trades according to the regime.

Eagle Strategy (ES) is a metaheuristic algorithm inspired by the hunting behavior of eagles, combining global exploration with local exploitation.

Trades XAUUSD using a neural network filter and ATR-based exits after a trend breakout.

Seeks directional changes in gold after completed candles, with trend and volatility checks helping to filter entries.

Uses ADX and DI crossovers with a Bayesian HPO gate and Random Forest classifier for trade signals.

A single-model machine-learning EA for XAUUSD that uses an ONNX classifier and RSI direction filter to manage directional exposure.

A trading bot using LSTM neural network for GBPUSD trades with engulfing patterns, volume analysis, and pivot-based signals.

A professional-grade Neural Network Trading System for MetaTrader 5.

Trading Expert Advisor based on deep reinforcement learning, game theory, and causal analysis.

AI-driven trading strategy using LSTM for time-series forecasting and dynamic market adaptation.

Hybrid algorithm combining boid rules with neural network learning for optimization tasks.

Adaptive regime detection and 4-layer capital protection for XAUUSD on M15 timeframe.

A simple neural network-based optimization algorithm inspired by self-organizing natural systems.

Algorithm that improves weaker solutions by borrowing ideas from successful ones, reducing the temperature over time.

Online logistic regression with SGD for adaptive trade signal filtering.

Combines Larry Williams Outside Bar strategy with AI for trade prediction.

Breakout strategy for NASDAQ 100 using pre-market calculations and ATR buffer.

A sophisticated MT5 Expert Advisor designed to pass the FundingPips 1-step $10,000 challenge.

Trades BTCUSD using a Q-PASS model trained on historical data and fine-tuned with PPO, with a live demo account.

Combines Kalman filter, ROC, Stochastic, and TEMA to generate high-confidence entry signals.

A machine learning-powered ensemble trading system for XAUUSD on M15 timeframe.

Combines machine learning-based market structure classification with rule-based trade execution.

Uses Q-learning to adaptively manage positions and optimize trading in response to market conditions.

Algorithm that uses blood type inheritance to mutate and select parameters in optimization.

Trades SPY put credit spreads based on LSTM-predicted volatility changes.

Uses a simple neural network (perceptron) based on iAC indicator values to determine trades.

HybridEA uses a hybrid approach combining mean-reversion and trend-following strategies based on market regime detection.

Uses Longstaff-Schwartz LSM to estimate continuation value and decide on optimal trade exit.

Uses MACD crossovers with a regime filter and Random Forest classifier for position sizing.

AI-driven multi-timeframe trading system for Bitcoin with 6 ONNX models and 3-Stage Progressive Ratchet Engine.

Professional-grade, institutional-grade trading system with objective market regime detection and advanced trade management.

Grid-based automated trading strategy for AUDCAD on H1 timeframe.

Enters trades when price breaks beyond extreme highs or lows on weekly timeframe, confirmed by daily moving averages and a statistical model.

A machine learning-based classification strategy using Lorentzian Distance Classifier and additional filters for trading signals.

Self-training GPT neural network EA for XAUUSD H1

Uses RNN models to predict Taiwan stock prices and generate trading signals.

Automated trading Expert Advisor using machine learning to analyze multiple timeframes and execute trades based on BUY, NEUTRAL, and SELL signals.

Contrarian trading strategy exploiting short-term mean reversion in GBP/INR following significant USD/INR movements.

Trades US500 CFD using a LightGBM 3-class classifier on S&P 500 daily bars.

Looks for upward breakouts supported by market strength during a defined trading session.

A quantum computing-based trading strategy with continuous learning and adaptive prediction.

A single-candle liquidity strategy with multi-level limit orders and risk management.

A complex AI-driven trading algorithm that uses LSTM networks and traditional technical analysis to predict market movements, with features like dynamic lot sizing and recovery mode.

A local AI-based scalping expert advisor for MetaTrader 4 using neural networks, evolutionary ensemble, and rule-based engine.

A strategy using three independent ML agents: entry signal generator, entry filter, and trade manager.

Systematic trend following with seven volatility-normalised trend signals and Kalman filter.

Detects directional change events and predicts overshoot length with genetic programming, then trades based on weighted voting and genetic algorithm optimization.

Combines price action and volume analysis to confirm trend breakouts.

Trend-following trading system based on signals from two AbsolutelyNoLagLwma indicators.

Trades mean reversion across a portfolio of instruments, closing positions when the distance from the recent middle has come back.

Automated gold trading strategy with dual-directional compression-breakout logic and auto regime detection.

A fully automated Expert Advisor for XAUUSD based on a breakout strategy with machine learning for trade selection.

Adapts trading strategy based on current market regime (trending, ranging, volatile)

A contrarian system that buys on fresh lows and sells on fresh highs within a 50-bar window, holding for 6 days.

A trend following strategy with out-of-sample validation and robust performance metrics.

Selects stocks based on recent risk-adjusted performance and dynamically rebalances the portfolio.

A purpose-built Expert Advisor for trading Gold (XAUUSD) with AI-enhanced strategy logic and built-in risk management.

Dynamic Trend-Following System using real-time market feature analysis and AI prediction.

Uses correlation and z-score to determine entry and exit points, with adjustable parameters for correlation calculation and z-score threshold.

Automated trading system that evaluates raw Bid and Ask quote behavior for entry and exit decisions.

Genetic algorithm with 3-condition AND logic for entry/exit

A multi-gate filter system for trading cryptocurrency CFDs (BTCUSD, ETHUSD) that passes signals through six independent checks before execution.

A Freqtrade strategy using LightGBM with 77 engineered features for crypto trading.

Combines three AI signal layers with adaptive learning and Bayesian signal fusion for trading.

Multi-timeframe machine learning EA with independent models for H4, H1, and M15, and an entry filter for final decision.

Precision-engineered trading system with multiple independent triggers and adaptive risk management.

A mean-reversion strategy with automatic lookback selection and optional detrending, using z-scores and regime filters.

A fully autonomous AI trading Expert Advisor for XAUUSD on the 5-minute timeframe.