AI Trading Bot & Guide

@ducthodg

As an experienced MQL developer and trading algorithm expert with a proficiency in multiple programming languages including C++, C, Java, VBA, MQL4, MQL5, Pine Script and Python, I believe I am the right freelancer for your AI Trading Bot & Guide project. With a solid 10+ years of experience in writing Expert Advisors and Indicators in MQL for various trading platforms such as MT4 and MT5, I have a deep understanding of designing and implementing sophisticated trading systems. Lastly, my engineering background as an Industrial Engineer strengthens my ability to architect high-quality systems with robust back-testing capabilities. Besides delivering on the mentioned technical aspects of the project effectively and efficiently within your timeline, I will provide a professional-grade standard of clean, well-commented source code that comes with comprehensive installation scripts. Coupled with thorough documentations and a easy-to-understand video walkthrough, you can trust that training your bot too will be smooth sailing. I look forward to discussing further project details with you

@vishal1145

Your biggest risk is building a system that trades live before you've validated the reinforcement-learning loop won't amplify losses during market volatility. I've seen two startups lose $40K in a week because their RL agent optimized for short-term gains without downside protection. Before we architect this, I need clarity on two things: What's your acceptable drawdown threshold during the self-improvement phase, and are you planning to run this on cloud infrastructure or dedicated servers? Latency matters when you're hitting Binance WebSocket feeds at 100 updates per second. Here's the architectural approach: - PYTHON + PYTORCH: Build a modular RL agent using Proximal Policy Optimization with risk-adjusted reward functions, not raw PnL. I'll add circuit breakers that halt trading if drawdown exceeds your threshold. - API INTEGRATION: Design an exchange abstraction layer so adding Kraken or Interactive Brokers only requires implementing four methods—authenticate, fetch_ticker, place_order, cancel_order. I've done this for three crypto platforms already. - NLP + GPT-4: Integrate a conversational layer that translates model outputs into plain English. Instead of "Sharpe ratio dropped 0.3," it'll say "I'm seeing choppy markets, so I reduced position size by half." - BACKTESTING FRAMEWORK: Use Backtrader with custom metrics to simulate slippage, fees, and API rate limits. Your acceptance test of one trading day won't catch edge cases, so I'll include 90-day historical runs. - SELF-IMPROVEMENT PIPELINE: Set up nightly retraining jobs that compare live performance against backtest predictions. If accuracy drops below 60%, the system flags it for manual review before deploying new weights. I've built two algo-trading systems that processed $2M in daily volume without a single failed order. One used sentiment analysis on crypto Twitter; the other ran statistical arbitrage on forex pairs. I don't take on projects where risk management is an afterthought. Let's schedule a 20-minute call to walk through failure scenarios—what happens if Binance goes down mid-trade, or your model starts overfitting to noise? Timeline depends on your answers, but expect 8-10 weeks for production-ready code with proper testing.

@ashinnd84

Hello there, we are a team of developers and we can build your AI trading application. Please, send me a message to discuss the work. Thanks Ashish Kumar.

@KarthikTechCon

Hi, I’m Karthik with 15+ years of experience in Python, AI/ML systems, real-time data platforms, and API-driven trading application development. Your project needs more than just a bot—it needs a modular trading platform with live/paper trading, explainable AI decisions, and a conversational layer users can actually trust. I can help architect and build this using Python, PyTorch/TensorFlow, exchange API adapters, backtesting, and an NLP layer such as OpenAI GPT for friendly user interaction. My approach would include: • Multi-exchange connector layer for Binance, Coinbase, and Kraken • Trading engine with paper/live modes and risk controls • ML pipeline for signal generation, evaluation, and retraining • Conversational dashboard/chat widget to explain positions, risk, and trade logic in plain language • Backtesting and performance logging for transparent review • Clean source code, install scripts, quick-start guide, and walkthrough video I would design it with reusable broker adapters so new exchanges can be added with minimal code changes. The self-improving pipeline would track model drift, accuracy, and trading outcomes, then trigger controlled retraining with reviewable metrics. I have strong experience in AI integrations, analytics dashboards, automation workflows, and production-grade Python systems built for maintainability and scale. Warm Regards, Karthik

@Shrutibimpl

You want an AI trading assistant. I will build your multi-asset trading engine that automates execution, learns from performance, and explains every move in plain English. 1) Which specific exchanges are the highest priority for the initial automated trading implementation? 2) Do you have a preferred infrastructure for the reinforcement learning pipeline to ensure 24/7 retraining without downtime? 3) Should the chatbot integrate with a specific messaging platform like Telegram or Discord for user convenience? We will build a smart partner that doesn't just trade on cold data but actually talks to you. You will get a friendly assistant that watches the crypto, forex, and stock markets around the clock, placing trades automatically while keeping a log of exactly why it made each decision. If you are curious about a position, just ask, and the bot will break down the risk or the logic in simple terms, making the complex world of algorithmic trading feel clear and approachable. It learns from its own wins and losses, constantly sharpening its strategy to stay effective in changing market conditions. I will develop the engine using Python, leveraging PyTorch for the reinforcement learning models and an NLP layer powered by an LLM to translate decision logs into conversational insights. Thanks, Bharat

@UzeeTech

As an experienced Full-Stack Developer with 7+ years of using Python, reinforcing your project with an AI trading system isn't just another technical challenge, it's a perfect alignment of my expertise and your requirements. Building on Tensorflow and PyTorch for modelling, I would construct a powerful, performant backend that integrates seamlessly with the APIs of Binance, Coinbase, Kraken and other platforms you may require in the future. Additionally, I'll incorporate an NLP layer like OpenAI GPT to ensure smooth conversational interactions. Your project's emphasis on self-improvement resonates well with my AI and machine learning proficiencies. By incorporating reinforcement learning techniques, I can ensure that your trading bot will not only learn from its mistakes but also continually evaluate and adapt its performance to maximize accuracy. I'll deliver a pipeline which includes performance metrics on both your training regime and live sessions for easy analysis of the bot’s actions. Last but not least, I'm committed to delivering well-documented, clean code that is not only easily maintainable by future developers but comprehensible for you. My clients consistently highlight consistent communication with топ-notch updates - expect no less from me. Let's take this journey together so we can build something that doesn’t just work, but outperforms expectations.

@MqlcoderHub

Hi — this is a serious build, and it needs the right architecture from day one. I can design and develop a modular AI trading system with execution + conversational layer that’s actually stable in real-world conditions. Quick questions: • Do you want to start with paper trading first only, or partial live deployment? • Any preferred timeframe (scalping vs swing) for initial model training?

@prashanpatel557

Hello, I can build your AI trading bot with a conversational interface, focused on practical performance, not overhyped ML. Approach: • Python-based engine (Flask/FastAPI) • Broker APIs: Binance / Coinbase / Kraken (modular adapters) • Real-time pipeline: data → signal → execution AI Layer (Practical): • Hybrid system: rule-based + ML • Avoid heavy RL initially (unstable for trading) • Continuous evaluation + retraining pipeline Conversational Module: • GPT-based assistant (explains trades, risk, decisions) • Example: “Why trade?” → returns logic + indicators used • Integrated into web dashboard Core Features: • Live + paper trading modes • Risk control (SL, sizing, drawdown limits) • Trade logs + performance metrics Self-Improvement: • Daily performance tracking • Auto retraining trigger (if accuracy drops) • Insight logs for review Deliverables: • Full system (engine + AI + chat + dashboard) • Clean code + setup guide • Demo (multi-exchange paper trading) Timeline: 22–28 days Budget: ₹55,000 – ₹75,000 I have experience building AI + trading automation systems, ensuring realistic and scalable solutions. Question: Do you prefer starting with crypto only (faster testing) before adding stocks & forex?

@Fahadghouri7

Hi there, I’m ready to work on your project “End-to-End AI Trading System with Conversational Interface.” I’m a professional systems architect and founder specializing in high-performance AI infrastructure and "Zero-Trust" secure backends. I focus on building robust trading engines that bridge the gap between complex quantitative models and intuitive human interaction. My Architectural Approach: Modular Trading Engine: I’ll use Python with an adapter pattern for Binance, Coinbase, and Kraken. This makes the system broker-agnostic and easy to scale. AI & Self-Improvement: I’ll implement a Reinforcement Learning (PPO) agent using PyTorch for analysis. An automated pipeline will monitor the Sharpe Ratio and trigger retraining cycles if accuracy drops, ensuring the system evolves with the market. Conversational NLP: I’ll leverage OpenAI’s GPT-4o with a RAG (Retrieval-Augmented Generation) layer. When asked “Why this position?”, the bot queries its own trade logs to translate technical signals (RSI, volume) into friendly, jargon-light explanations. Timeline: I estimate a 2 to 4 week delivery: Weeks 1-2 for API & Backtesting; Weeks 3-4 for RAG & Chat, Self-improvement loops, Paper Trading, and final hand-off. Clear communication and technical transparency are my priorities. I’ll provide a Docker-ready repo with a video walkthrough. View my portfolio here: ✨ https://www.freelancer.com/u/fahadghouri7 Thank you, Fahad

@pinkeegupta

Hello I will be able to help you. I bring 9+ years of combined experience in Python development, Data Science, Data Analytics, and Business Intelligence, helping clients turn raw data into meaningful insights and actionable dashboards. My Core Expertise Includes: Node js , React Js, Mongo , Blockchain, crypto currency Python Development: Pandas, NumPy, Scikit-learn, FastAPI, Flask, Django Data Science & Machine Learning: Data cleaning, EDA, predictive modeling, AI/ML solutions Data Analytics: Statistical analysis, reporting, automation, data mining Power BI: Interactive dashboards, DAX, Power Query, data modeling, KPI reporting Databases & Big Data: SQL, NoSQL, SparkML AI & Frameworks: TensorFlow, PyTorch, Cursor, Calude, gemini, nano, chatgpt. I focus on clean code, clear insights, performance optimization, and business-oriented outcomes. I ensure timely delivery and transparent communication throughout the project lifecycle. Let’s connect to discuss your requirements in detail and define the best approach for your project. Looking forward to working with you. Regards, Anju Logical Soft Tech Pvt Ltd, Indore(M.P)

@abdf2010

Hello, I am interested in your project, AI Trading Bot & Guide. I've successfully completed projects involving C Programming, Python, Software Architecture before. Happy to discuss the details whenever works for you.

@Algokage

Hello, I can deliver an end-to-end AI trading system that operates across stocks, cryptocurrencies, and forex, with a conversational interface and self-improvement capabilities. My approach involves using Python, TensorFlow, and OpenAI GPT for the NLP layer, ensuring seamless integration with exchange APIs like Binance and Coinbase. The system will include live and paper trading modes, a robust back-testing framework, and automated model updates. With 5+ years of experience, I’ll ensure clean, well-commented code and provide a quick-start guide. Send a message to discuss further or see samples of similar projects. Thanks, Adegoke. M

@loxtic

Hi, how are you doing? I have solid hands-on experience building end-to-end trading systems with Python, ML models in TensorFlow/PyTorch, and NLP chat components, plus integration with major exchanges. I’d approach this by a modular stack: a live/paper trading engine compatible with Binance, Coinbase, and Kraken, a conversational layer using a lightweight NLP model for casual dialogue and clear explanations, and a self-improvement loop that retrains on new data and logs insights. Deliverables would include a clean, well-commented codebase, installation scripts, a quick-start guide, and a short video walkthrough. I can demo a working prototype on two exchanges and handle the automated model-update cycle after a trading day. If you’re interested, I’ll outline a concrete architecture and timeline.

@Bilu7111

As a part-time trader, I have built Python-based trading bots, tested them successfully, and used them in real scenarios. I also find your idea of extending these bots with AI (OpenAI) and a RAG-based system very promising. It would allow the system to answer user queries intelligently while staying aligned with real-time market conditions. We can also store historical risks and market behavior to improve context-aware responses over time. I estimate around one month to design and implement the full system, including architecture design, back testing, integration of OpenAI and databases, deployment, and final testing on a live environment. I believe this can be a strong solution for traders who currently rely heavily on manual analysis. If you think I’m a good fit, I’d be happy to discuss the architecture in detail and get started. Thank you for your time. Kind regards, Bilal Kazmi

@Core100

Hi there, We will build a unified AI trading system for stocks, cryptocurrencies, and forex. It ingests real-time data via CCXT & broker APIs (Binance, Coinbase, Kraken), analyzes with PyTorch models + PPO reinforcement learning, and auto-executes trades in paper/live modes. A casual, friendly conversational interface (LangChain + Streamlit dashboard) explains decisions in plain language. The bot self-improves by retraining on performance drops and logs insights. Deliverables: Full Python code, backtesting, installation scripts, quick-start guide. Meets all acceptance criteria. Kindly contact via private message so that i can send you detailed proposal. Looking forward to hearing back from you. With Regards, Raghav, BLW TECH

@Sahyadri96

Completed projects till now 1) Python + DhanAPI +Excel + VBA option scalping strategy 2) Python 21 EMA and 9 EMA crossover strategy on DhanAPI 3) Google sheet + FyersAPI trading 4) Google sheet + Algomojo + Upstox 5) Tradetron Banknifty option scalping strategy 6) Excel 2600 NSE 10 years data 7) Copytrading using python 8) Tradetron Supertrend + MACD Crossover Strategy 9) Dhan option chain with Greeks in Google spreadsheet via Google Appscript 10) Backtesting of Nifty options for wait and trade strategy 11) Trigger orders for Dhan Nifty options 12) Shoonya API:- Wait and trade strategy 13) Tradetron: RSI + ADX + EMA strategy 14) Python Moving avarage channel trading Algo 15) Kotak Neo: Turtle scalping strategy for options 16) Fyers Filtered option chain in Excel I can deliver any project in Trading. Readymade setups for Python available

@shailender18

With my vast experience in MEAN and MERN stack development, I am fully equipped to deliver your AI Trading Bot with all the features you've outlined: from creating a solid architecture to leveraging APIs such as those of Binance, Coinbase, and Kraken. I understand the value of yours system being scalable and future-proof, allowing additional brokers to be integrated with minimal code changes. Talking about the core technologies required for this project, Python, TensorFlow/PyTorch for modeling, NLP layer for the chat component, and a strong back-testing framework; they are right up my alley. Being well-versed in Python along with an extensive knowledge in utilizing Tensorflow/PyTorch, designing an NLP driven system won't be challenging for me. In conclusion, armed with a comprehensive set of tools including Python, TensorFlow/PyTorch, NLP frameworks like OpenAI GPT and Rasa, as well as deep knowledge in MEAN/MERN stack development, working with me would ensure not just an impressive trading bot but also a reliable long-term partnership where we can continously grow and refine this system together.

@dushyant317

I can design a scalable trading engine with live/paper modes, self-improving pipelines, and a user-friendly chat interface—happy to share similar projects and outline a clear architecture and timeline.

@WiredAI

Dear Client, I can build your end-to-end AI trading system with real-time trading across stocks, crypto, and forex, combined with a friendly AI chat layer that explains every decision in simple language. With 6+ years in Python, ML (PyTorch/TensorFlow), and exchange integrations (Binance, Coinbase, Kraken), I’ll design a modular system for data ingestion, ML-based trading, execution, and conversational insights. ? You’ll get: Multi-exchange trading engine (live + paper) ML strategy + backtesting system GPT-based chat for trade explanations & risk Q&A Self-improving retraining pipeline Clean, scalable codebase + setup guide Timeline: 2 weeks for MVP. Let’s connect and finalize the architecture. Best regards, wiredAI Ventures