You will get Custom Trading Bot & Algorithmic Trading Agent
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Project details
Project Summary: End-to-End Reinforcement Learning Trading System
This project delivers a complete, production-ready quantitative trading system designed using a research-driven and engineering-focused approach. The objective is to build, validate, and deploy algorithmic trading strategies powered by reinforcement learning (RL), covering the entire lifecycle from initial research and modeling to paper trading, monitoring, and optional live execution.
Unlike experimental or prototype-level trading bots, this project emphasizes robustness, risk control, transparency, and real-world deployability. The system is designed to operate under realistic market conditions, incorporating transaction costs, slippage, latency considerations, and strict capital management rules. The end result is a fully implemented trading framework suitable for institutional-style workflows, proprietary trading, or advanced individual use.
This project delivers a complete, production-ready quantitative trading system designed using a research-driven and engineering-focused approach. The objective is to build, validate, and deploy algorithmic trading strategies powered by reinforcement learning (RL), covering the entire lifecycle from initial research and modeling to paper trading, monitoring, and optional live execution.
Unlike experimental or prototype-level trading bots, this project emphasizes robustness, risk control, transparency, and real-world deployability. The system is designed to operate under realistic market conditions, incorporating transaction costs, slippage, latency considerations, and strict capital management rules. The end result is a fully implemented trading framework suitable for institutional-style workflows, proprietary trading, or advanced individual use.
AI Development Type
Deep Learning, Model Tuning, Recommendation SystemAI Tools
Amazon SageMaker, Keras, MATLAB, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, PyTorch, Sonnet, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$1,000
|
Standard
$2,000
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | |
Detailed Code Comments | - | ||
Knowledge Graph | - | - | |
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - |
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BA
Badr A.
Feb 11, 2026
30 minute consultation
OS
Omer S.
Jan 9, 2026
Machine Learning Expert for Stock Market Trend Forecasting
Good, work
OS
Omer S.
Dec 30, 2025
Machine Learning Expert for Stock Market Trend Forecasting
Great job
DF
Daniel F.
Nov 15, 2025
Optimal Refinancing Model Research
Giorgi is dedicated, professional, and delivers high-quality work.
GK
Guram K.
Jul 20, 2025
Analyzing paper on multiple bot trading systm
About Giorgi
Quant Trading Systems Architect | AI-Powered Bots | Kraken & IBKR API
100%
Job Success
Tbilisi, Georgia - 6:52 pm local time
WHAT I BUILD
⚡ End-to-End Trading Bots
Full pipeline: signal generation → order execution → risk management
Exchange integration: Kraken, Interactive Brokers, Binance, Bybit APIs
Low-latency execution via REST & WebSocket connections
Multi-asset support: crypto, equities, futures, forex
🧠 AI/ML-Driven Alpha Generation
Deep Reinforcement Learning agents (PPO, A2C, SAC) for adaptive strategy optimization
LSTM/Transformer models for price trajectory forecasting
Ensemble methods: XGBoost, LightGBM, Random Forest for feature-rich prediction
Online learning systems that adapt to regime changes
📰 Real-Time News & Sentiment Alpha
Live news ingestion from Bloomberg, Reuters, Twitter/X, Reddit, Telegram
NLP pipelines: FinBERT, GPT-based sentiment extraction
Event-driven trading: earnings, FOMC, CPI, geopolitical triggers
Alternative data integration: social sentiment scores, fear & greed indices, on-chain metrics
📊 Quantitative Research & Backtesting
Walk-forward optimization with out-of-sample validation
Monte Carlo simulations for strategy robustness
Realistic market microstructure modeling (slippage, partial fills, latency)
Statistical edge validation: Sharpe, Sortino, Calmar, max drawdown analysis
TECHNICAL ARSENAL
Languages: Python, R, SQL, MQL5
ML/DL: PyTorch, TensorFlow, scikit-learn, stable-baselines3
NLP: HuggingFace Transformers, spaCy, FinBERT, LangChain
Data: pandas, NumPy, Polars, Apache Kafka, TimescaleDB
Backtesting: Backtrader, VectorBT, QuantConnect, Zipline
Execution: ccxt, ib_insync, Alpaca API
Infra: Docker, AWS, GCP, Redis, PostgreSQL
Viz: Power BI, Plotly, Streamlit dashboards
MY DEVELOPMENT PROCESS
Phase 1 → Strategy Discovery & Alpha Research
Phase 2 → Feature Engineering & Model Development
Phase 3 → Rigorous Backtesting & Stress Testing
Phase 4 → Paper Trading Validation
Phase 5 → Live Deployment with Kill Switches & Risk Controls
Phase 6 → Continuous Monitoring & Model Retraining
CREDENTIALS
🎓 PhD in Statistics & Data Science 🏦 10+ years in quantitative finance 🏛️ Former Team Lead — National Bank of Georgia 💼 Institutional experience: TBC Bank, IFC, hedge funds ($500M+ AUM) ⭐ Top Rated on Upwork | 5-Star Client Feedback
IDEAL PROJECTS
✅ Custom trading bot development (crypto, stocks, futures) ✅ RL-based portfolio optimization agents ✅ Sentiment-driven trading systems ✅ Existing strategy automation & optimization ✅ Quant research & alpha discovery ✅ High-frequency data pipeline architecture
Steps for completing your project
After purchasing the project, send requirements so Giorgi can start the project.
Delivery time starts when Giorgi receives requirements from you.
Giorgi works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Definition
Understand target market, trading horizon, risk limits, and deployment goals.
Data Preparation
Collect and preprocess historical market data and features.