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MACHINE LEARNING

Trading AI

A machine-learning trading engine that blends three model families into one ensemble, validated walk-forward and wired to live order-flow monitoring with Telegram alerts.

AI

Outcomes

3-model

Ensemble

Walk-forward

Validation

Live

Order Flow

Real-time

Telegram Signals

The Problem

Single-model trading systems overfit and break the moment market regimes shift. Manual monitoring can't keep up with live order flow, and signals that aren't surfaced in real time are worthless.

Our Solution

We engineered an ensemble that combines gradient-boosted trees (XGBoost), a sequence model (LSTM) and a reinforcement-learning agent (PPO), evaluated with walk-forward validation to guard against overfitting. The engine monitors live order flow and pushes actionable signals straight to Telegram.

Key Features

What We Built

01

Ensemble Models

XGBoost, LSTM and a PPO reinforcement-learning agent combined into a single decision ensemble.

02

Walk-Forward Validation

Rolling train/test windows that test the strategy the way it would actually trade, reducing overfit.

03

Live Order-Flow Monitoring

Real-time market and order-flow analysis feeding the engine continuously.

04

Telegram Signals

Generated signals delivered instantly to Telegram so decisions reach you in real time.

Built With

PythonXGBoostLSTMPPOTelegram

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