I and my team (UBIQTech) hold 55 granted patents with 20 more pending, proving our ability to consistently innovate and excel. With a 100% project success ratio and a portfolio of satisfied global clients, we thrive on challenging projects that demand creativity, precision, and scalability. CORE COMPETENCIES:- - Generative AI, Predictive Analytics, Deep Learning, Computer Vision - Agentic AI, Workflow Automation, MCPs, AI Agents, Physical AI - Vector Database Integration for intelligent knowledge management and semantic search. - Rust-based IoT & AI Systems for performance-critical applications. - Embedded Systems, Smart Sensors, Industrial IoT, Digital Twins - AI-Augmented IoT Analytics, Cloud-Integrated AI, Edge AI, real-time automation solutions. My Latest Projects - ANPR (Automatic Number Plate Recognition) – Real-time vehicle monitoring and route tracking system. - MoldRix IoT Device – Predictive maintenance and production monitoring solution for industrial efficiency. - HypoText GEO – Advanced geo-intelligence platform for data-driven decision-making. - Smart Gas Detection System – IoT-based workplace safety solution. - Non-Invasive Glucose Monitoring Device – Biomedical innovation using advanced sensors. - AI-Powered Classroom Monitoring – Intelligent system for enhancing educational environments. - Battery Management System – Optimized energy efficiency for critical applications. I am happy to schedule a demo or provide deeper insights into any of the following projects to showcase real-world impact and technical excellence: Automatic Number Plate Recognition – Real-time vehicle monitoring and route tracking system. MoldRix IoT Device – Predictive maintenance and production monitoring solution for industrial efficiency. HypoText GEO – Advanced geo-intelligence platform for data-driven decision-making. Smart Gas Detection System – IoT-based workplace safety solution.MoldRix IoT Device – Manufacturing automation and predictive maintenance AI-Powered Classroom Monitoring – Intelligent system for enhancing educational environments. Battery Management System – Optimized energy efficiency for critical applications. Interested in exploring how these solutions can transform your business? Let’s schedule a demo and discuss your vision.

I’m a Mathematics & Computing (Integrated M.Sc.) graduate(CGPA- 9.67) from IIT Kharagpur with professional experience in machine learning, quantitative research, data science, and software engineering. I specialize in building mathematically rigorous, data-driven systems that move cleanly from research to production. My work sits at the intersection of advanced mathematics, ML/AI, and real-world engineering—allowing me to not only design sophisticated models, but also validate, optimize, and deploy them reliably in production environments. 🔹 What I Do Machine Learning & Data Science Predictive modeling, feature engineering, and statistical learning Time-series analysis, forecasting, and model validation ML pipelines in Python (NumPy, Pandas, Scikit-Learn, PyTorch) Quantitative Research & Finance Systematic trading strategy design and backtesting Alpha research: mean reversion, momentum, statistical arbitrage Portfolio optimization using Black-Litterman, Glasso, meta-heuristics Risk modeling, Sharpe optimization, drawdown control Reinforcement Learning & Optimization RL-based decision systems (DQN + LSTM) Meta-heuristic optimization (PSO, Simulated Annealing) ML-driven asset allocation and strategy optimization Software & Backend Engineering Production-grade Python and Java development Backend services with strong testing, CI/CD, and reliability guarantees Clean, modular, well-documented, performance-optimized code 🔹 Professional Experience Development Engineer — Standard Chartered GBS (Full-Time) Built secure, high-quality backend services for financial platforms Migrated large codebases from Java 8 → Java 17, improving performance and maintainability Increased automated test coverage to ~60% across multiple repositories through robust unit and integration testing Brain Research Consultant — WorldQuant Designed and optimized 30+ alpha strategies, achieving Sharpe ratios up to 3.0 Controlled pairwise correlation and improved robustness of signals Focused on Sharpe ratio, ROE, and risk-adjusted performance Quantitative Researcher — Indxx Private Limited Built ML-driven portfolio optimization frameworks Combined Particle Swarm Optimization and Simulated Annealing Improved portfolio Sharpe by 10% and reduced risk metrics by 12% Mathematics Expert — Micro1 (Freelance) Designed high-difficulty, original mathematical problems Created Project Euler–style challenges with competition-grade rigor 🔹 Selected Client Engagements (Upwork & Contract Work) Quantitative Validation & Automation Architect — Æthux (Atlas Project) Architected a production-grade validation, explainability, and CI/CD framework for quantitative investment models Built deterministic test harnesses for Black-Litterman and Monte Carlo engines Implemented model explainability (SHAP/LIME), drift detection, and automated evidence pipelines Delivered an auditable, compliance-ready analytics stack used for production decision-making Macro Economist — Inverse Financial Model & TAM Study Developed an inverse financial model for a novel digital marketplace Conducted a comprehensive Total Addressable Market (TAM) analysis Co-authored a white paper detailing economic incentives and market dynamics (Details shared within NDA constraints.) 🔹 Research & Technical Projects Neural Black-Litterman Model (Master’s Thesis) Integrated LSTM-based return forecasting with Black-Litterman allocation, achieving 25.3% annualized returns and strong risk-adjusted performance on NIFTY & S&P 500. Advanced Statistical Arbitrage with Reinforcement Learning Implemented OU, distance-based, and RL-driven mean-reverting strategies using DQN + LSTM. Cryptocurrency Momentum & Reversal Strategies Identified short-term reversals and long-term momentum with Sharpe ratios up to 3.0. Robust Glasso Portfolio Optimization Improved Sharpe by 13.7% and reduced turnover using robust precision matrix estimation; research paper under review. 🔹 Tools & Skills Languages: Python, Java, C, C++, SQL ML / Data: NumPy, Pandas, Scikit-Learn, PyTorch, Backtrader Backend & Dev: Spring Boot, GitHub, CI/CD, JUnit, Mockito Math & Stats: Probability, Stochastic Processes, Optimization, Time Series, Financial Mathematics

I help traders, hedge funds, and startups build profitable trading bots, quantitative models, and AI-powered automation systems using Python and modern AI/LLM technologies. I’m a Quant Developer and Quantitative Analyst with 3+ years of hands-on experience in derivatives, algorithmic trading, statistical modeling, and AI-driven financial systems. I’ve delivered production-ready trading bots, backtesting engines, and automation tools — with $10,000+ earnings and 100% Job Success on Upwork. My expertise combines quantitative finance, Python development, and AI/LLM integration to build robust systems that perform reliably in live markets. 🚀 What I Can Build for You • Algorithmic trading bots (stocks, options, crypto, forex) • Backtesting engines with performance analytics and risk metrics • AI-powered trading tools using LLMs and machine learning • Trading automation tools with broker and market data API integration • Quantitative models for alpha generation and portfolio optimization • Trade execution systems and automation dashboards • Financial data pipelines and research tools 💼 Technologies & Tools Programming & Quant: Python (Pandas, NumPy, scikit-learn, backtrader), statistical modeling, quantitative research Trading Platforms: MetaTrader 5 (MQL5), TradeStation, MultiCharts, broker API integrations AI & Automation: LLM integration, AI automation systems, data analysis, workflow automation Data & APIs: Financial data APIs, live market feeds, execution APIs, custom integrations 📊 Proven Experience Includes • Building live trading bots with full automation • Developing backtesting systems with historical and live data • Creating automation tools that reduce manual trading workload • Quantitative research and alpha strategy development • Integrating broker APIs and real-time data systems ✅ What You Can Expect • Production-quality, clean, and scalable code • Strong quantitative and technical expertise • Reliable communication and fast delivery • Focus on performance, risk management, and real-world deployment If you're looking for a serious Quant Developer who understands both trading and technology, I can help you build reliable and scalable trading and automation systems. Available for long-term and high-value projects.

I am a quantitative / systematic trader that also helps others with all things related to running algorithmic trading systems. With 8 years of dedicated experience in financial markets, including extensive trading in the Futures and Options (F&O) segment of Indian markets, I offer a comprehensive understanding of trading dynamics and strategies. My expertise extends to developing Real-Time Trading Applications, Back Testing/Modeling Trading Strategies, data collection/storing, portfolio and position risk management, etc. using Python and TradingView as my primary tools. I am a skilled python programmer that writes well documented and organized code that is easy to follow and build upon. I provide even more value with my trading knowledge and experience. I've developed more than 60 successful projects to date helping Retail and Institutional Clients, and look forward to taking on many more. No matter how large or small the project, I am capable of completing it in a timely and effective manner. THINGS I CAN HELP YOU WITH : 🌟 Algo Trading Bot / Application - Coding your strategy and integrating it with brokers api in python. Fast, Accurate, Efficient, Documented code deployed on cloud or locally. 🌟 TradingView + Python - Trading Logic and Signals are coded in TradingView Pine Script and trade execution is done through Python and Brokers API. 🌟 Equity Markets - Indian Markets, US Markets, major Global Markets using broker APIs. Direct Equity, Futures and Options, Delta Trading. Experience with Interactive Brokers, TD Ameritrade, E-Trade, Zerodha, Kotak, Upstox, IIFL, Angel and others. If it supports algo trading, I've either developed on or can very quickly learn how to. 🌟 Crypto Markets - Binance, Kucoin and all major Crypto Exchanges. Grid Trading, Arbitarage Trading, Option or Futures. 🌟 TradingView PineScript - Custom Indicator Development, Modification or bug fixing in existing Indicator or strategy, Generate and Send Alerts to Trading Bot or Messaging Channel. 🌟 BackTesting - Develop Custom Backtesting modules based on your needs, or using open source libs like VecorBT, BackTrader, BackTesting, etc. in python further optimised with . Fine Tune or optimise parameters based on market conditions. 🌟 Risk Management - Integrated Position Sizing, Portfolio Risk Analysis, daily limits for trades, profits or loss. 🌟 Data Analysis & Visualization - Analyse data with Pandas, Numpy, Numba, Scipy and view it in excel or webapp. Charting Libraries such as Seaborn, Tableau or MatPlotLib and seamless integration with MySQL, PostGreSQL or others. 🌟 Signal and Trade Messages - Get Custom Messages on Signal / Order / Trade on Telegram, Discord, WhatsApp, E-Mail, etc. 🌟 User Interface - Request Custom Website in React js with FastAPI or Dash Webapp, Simple Excel / G Sheet, GUI App build with PyQT. 💼 Work Approach: Shoot me a message and lets chat over zoom via the Upwork integration and quickly discuss your project needs. The consultations are free, and last as long as needed. It can be 2 minutes or 2 hours. My goal during this call is to ask you as many questions as I need until my brain clicks and fully understands your project. 🤝 Let's Collaborate: If you're seeking a skilled professional to enhance your trading operations or develop custom solutions, I'm here to help. Let's discuss your requirements in detail and explore how we can collaborate to achieve success in the dynamic world of financial markets. Feel free to reach out, and let's embark on this journey together. Kind regards 😊 Have a good day and stay safe, Harsh Kantariya.

I'm a Top Rated quantitative developer on Upwork, currently completing my MS in Data Science at Harvard, with production experience building and shipping algorithmic trading systems across futures, options, and equities. My work spans the full pipeline: from signal research and rigorous backtesting through execution architecture and live broker deployment. Over the years I've collaborated with professional traders, systematic fund managers, and independent CTAs on strategy research, execution system builds, and quantitative infrastructure — working with live accounts and real capital, not toy portfolios. - Research Philosophy Most algorithmic trading research fails before it reaches live markets. The reasons are almost always the same: data snooping bias, fragile parameterization, fill simulation that doesn't reflect actual execution, and strategy logic never stress-tested against regime change. My research process is designed to make it hard to fool yourself. That means strict chronological train/test splits with no parameter bleedthrough, walk-forward optimization over anchored and rolling windows, block bootstrap for inference on autocorrelated returns, and parameter sweep frameworks built to expose fragility rather than maximize backtest metrics. A strategy that only works on one parameterization isn't a strategy, it's a coincidence. I care about robustness across parameter space, regime stability, and understanding exactly why a signal works before scaling it. I work extensively in QuantConnect's LEAN engine for research-grade backtesting and live account deployment, though deployment targets vary by strategy and client stack. IB TWS via ibapi, Tradovate, and NinjaTrader are all in regular rotation depending on execution requirements. I build custom analytics layers on top of backtest output: Sharpe decomposition, drawdown attribution, execution cost modeling, and signal decay analysis, because standard tearsheet metrics rarely tell the full story. - Strategy Coverage My research spans futures (NQ, ES), SPX and index options, ETFs, and crypto. Strategy types I've built and validated in production include intraday momentum and trend-following systems, mean reversion and stat-arb frameworks, breakout and scalp architectures with dynamic sizing tiers, options strategies including iron condors, defined-risk vertical spreads, 45-DTE and 0DTE SPX structures with delta-based hedge logic, and GEX (gamma exposure) driven directional frameworks using open-interest-weighted dealer positioning data. It's an area where the signal literature is still thin and where getting the methodology right matters more than most people acknowledge. - Execution Engineering The research-to-live gap is where most systems break. I build execution infrastructure that closes that gap: Interactive Brokers TWS via ibapi with state machine architectures, order ladder geometry, true breakeven calculations with commission and slippage factored in, and hedge math for multi-leg positions. On the NQ/ES side I've built and audited scalp bot execution logic on Tradovate, integrated Databento for professional tick data pipelines with proper validation against reference data, and developed Pine Script strategies and indicators on TradingView for signal prototyping before committing to full implementation. I'm also familiar with NinjaTrader's execution environment and ATM framework. Code I deliver is production-standard: structured logging, explicit edge-case handling, clean separation of signal and execution layers, and documented at a level where the system is maintainable after handoff. - What I Work On: - Strategy Research & Backtesting: QuantConnect/LEAN, Backtrader, Zipline, VectorBT, QuantLib, Python - Execution Systems: IB TWS/ibapi, Tradovate API, NinjaTrader, REST/WebSocket broker integrations, FIX Protocol - Retail Platform Development: MQL4/MQL5 (MetaTrader 4/5), Pine Script (TradingView), NinjaScript (NinjaTrader 8), EasyLanguage (TradeStation), ThinkScript (Thinkorswim), cAlgo/C# (cTrader), AFL (AmiBroker) - Broker APIs: Interactive Brokers, Alpaca, TD Ameritrade, Tradovate, Oanda, Databento - Crypto Platforms & APIs: Binance, Bybit, OKX, Kraken, Coinbase Advanced Trade, Bitfinex, Deribit (options/derivatives), KuCoin, Gate io, Freqtrade, Hummingbot, 3Commas, Pionex, Gunbot, ccxt (unified exchange library) - Statistical Testing: Walk-forward testing, parameter sweep analysis, Monte Carlo simulation, bootstrap inference - Full-Stack Delivery: Data ingestion → signal research → backtesting → live deployment

I am on vacation. Please reach out to: Rajendra Kumar Sharma upwork/freelancers/~0172aacf3c6b74448a/ Looking to optimize your trading strategies? I develop high-performance, automated trading systems using NinjaTrader, TradeStation, CTrader, Quantconnect, Python, MetaTrader, Pine Script, and more. My work has helped high-profile clients achieve superior execution and profitability. I have worked with 🌟High Profile Clients/Organizations🌟 and have professional experience working at an Algo trading desk. ✔ Proven Expertise – 10+ years of experience in Quantitative Trading, Algo Development, and AI-driven trading systems. ✔ High Client Satisfaction – 100% positive reviews and repeat clients on Upwork. ✔ Cutting-Edge Strategies – I develop advanced trading algorithms using Python, Pine Script, and C++. ✔ Rapid Response & Support – I ensure fast, clear communication and ongoing support. ✔ Results-Driven Approach – My trading models have consistently delivered high Sharpe ratios & live market success. ✅ Algorithmic Trading (Pine Script, MQL4/MQL5, NinjaTrader, TradeStation, cTrader) ✅ AI/ML for Trading (XGBoost, Decision Trees, TensorFlow, Keras) ✅ Backtesting & Optimization (Backtrader, QuantConnect, Lean) ✅ High-Frequency Trading (HFT) & Market-Making Bots ✅ API Development & Integration (RESTful APIs for brokers & exchanges) Developed a Python-based trading bot with 40% ROI in live market testing. Created an ML-driven options strategy with a Sharpe ratio of 2.5+. 💬 Need a custom algorithmic trading solution? Let’s chat about how I can boost your trading performance. Click the "Hire Now" button to get started! Finder : Tradestation, TS, AgenaTrader, AT, Backtesting Python, Lean, Quantopian, Quantconnect, QuantConnect, Pinescript, PineScript, Pine Script, Quant, Quant Connect, Interactive Brokers, IB, TWS, Trader, Metatrader, Meta trader, Metatrader4, Meta trader 4, MT4, Metatrader5, Meta trader 5, MT5, Ninja Trader, NinjaTrader, Ninjatrader7, Ninja Trader 7, NT7, Ninjatrader8, Ninja Trader 8, NT8, EA, Expert Advisor, Indicator, ForEx programmer, code an Indicator, code an EA, MQL4 Programmer, MQL 4 Programmer, MQL4, MQL 4, MQL5 Programmer, MQL 5 Programmer, MQL5, MQL 5, TradingView, Trading View, cTrader, cAlgo, cBot, PineScript, PineScript

I engineer institutional-grade algorithmic trading systems that combine quantitative finance, deep learning, and real-time market intelligence. 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

Algorithmic Trading Developer specializing in building end-to-end trading systems, backtesting and optimization frameworks, and predictive machine learning models for financial markets. With over 3 years of experience collaborating with HNIs, hedge funds, and retail traders, I help clients automate, validate, and deploy profitable trading strategies across cryptocurrency, forex, and stock markets. My expertise spans technical analysis, quantitative research, and ML-driven strategies, along with developing custom screeners, dashboards, Python-based trading bots, low-latency execution systems, and robust Risk Management (RMS) infrastructure. I also provide statistical validation of trading strategies to ensure they are backed by data rather than assumptions. Whether you're implementing an idea from a research paper, translating a technical trading concept into code, or building a production-ready algorithmic trading system, I can help you develop, test, optimize, and deploy it with a scalable and reliable architecture. Programming Languages - Python - C++ - SQL Python Frameworks - Pandas - Numpy - Sci-kit - TensorFlow - Seaborn - Matplotlib - Streamlit - Plotly-dash Backtesting Frameworks - Backtrader - VectorBT - Backtesting-py - Custom backtesting engine Platform & Tools - Linux - Windows - Git - Github - Docker Databases - PostgreSQL (Timescale-db) - SQLite - Redis - Parquet/DuckDB ML for Financial Markets - Time-Series modeling - Classification & Regression - XGBoost, LightBoost Broker/Exchanges (not limited to) - Interactive Broker - Thinkorswim - Robinhood - Tradier - Alpaca - Charles Schwab - Binance - Coinbase - Bybit - OKX - Kraken - Crypto Read-only proficiency - Pine Script (Tradingview) - C# - MQL5 (Metatrader) - ThinkScript (Thinkorswim) Important Note - I do not sell pre-made bots or strategies. - Every system is custom-built based on your unique requirements and trading logic. If you're looking for a reliable algorithmic trading developer to turn your trading ideas into robust, production-ready systems feel free to send a 'message' or 'invite' me to your project.

Quant Scientist with over 5 years of experience in financial modeling, algorithmic trading, and machine learning. I specialize in building and deploying data-driven systems for forecasting, strategy development, and risk management — with deep expertise in time-series modeling and Python-based tooling. Currently, I work at a Global Macro Hedge Fund where I design and implement systematic strategies across asset classes, build portfolio optimization tools, and develop quantitative risk frameworks. Outside of work, I actively research and trade in equities and digital assets, with hands-on experience developing DeFi strategies (arbitrage, trend-following, yield optimization) since 2021. What I Can Help You With? - Development and backtesting of trading strategies (equities, crypto, futures) - Predictive modeling & machine learning (scikit-learn, TensorFlow) - Time-series analysis and signal engineering - Custom data pipelines: APIs, scraping, structured storage - Interactive dashboards and analytics (Dash, Plotly) Tech Stack - Languages & Libraries: Python, NumPy, Pandas, Scikit-learn, XGBoost, TensorFlow, Statsmodels, Git - Backtesting & Strategy Simulation: Backtrader, VectorBT, QuantConnect (LEAN) - Risk & Portfolio Analysis: Pyfolio, Riskfolio-Lib, Empyrical, cvxpy, Quantlib - Forecasting: Scikit-learn, XGBoost, TensorFlow, Darts, TSFresh - Data & Automation: REST APIs, Web Scraping (Selenium, BeautifulSoup), SQL, ArcticDB - Visualization & Dashboards: Plotly, Dash, Seaborn - API Integration: Interactive Brokers API (ib_insync), CCXT (CEXs), Web3.py, The Graph (on-chain data), 0x API - Infrastructure & Workflow (Optional): Docker, Airflow, AWS (EC2, S3), Git - Options: understanding of theory, including Greeks, implied volatility, and surface construction

Hello! I'm a Quantitative Trading Systems Developer with 10 years of experience in algorithmic trading, financial data science, and market behavior modeling. I specialize in building robust Pine Script strategies for TradingView, predictive models for market trend forecasting, and backtested trading logic for real-time execution. 🔹 Strategy Design & Pine Script Development 500+ PineScript strategies built with multi-timeframe logic (M15–D1) Focus on low drawdown, real-time signal quality, and adaptive take-profit/stop-loss logic Market regime filtering using ADX, RSI, Bollinger Bands, EMA, and price action filters 🔹 Predictive Modeling & Forecasting Systems Created trend forecasting models using TCN-LSTM + Attention, achieving 66–68% accuracy on out-of-sample BTC/USDT data Full data pipeline design: OHLCV ingestion, feature engineering, normalization, and deployment Real-time prediction delivery via Telegram or custom dashboards 🔹 Quantitative Analysis & Risk Modeling Built statistical models for volatility, regime shifts, and position sizing Applied walk-forward testing, recovery factor tracking, and out-of-sample validation Delivered models with performance in mind: not just backtested, but market-ready 💼 Tools & Stack: Python • Pine Script • TSLab • Backtrader • Pandas • NumPy • TA-Lib • MetaTrader 5 APIs • TensorFlow • PyTorch I'm also experienced in reinforcement learning and custom RL environments for trading, but these services are available only to institutional clients. Let's work together to build powerful and reliable trading systems that perform in real-world conditions. Message me if you'd like to discuss your project.