AI Options Trading Algorithm

@mohjib092

I typically implement systems like this using Python, FastAPI, pandas, scikit-learn/TensorFlow, and a modular microservice architecture to keep strategies configurable and scalable. I can also deploy and optimize the system on your VPS to meet the ≤250ms execution latency requirement. I’d be happy to discuss architecture details, milestones, and timeline toward paper trading validation and live deployment. Best regards.

@Shrutibimpl

Hello, I will build a comprehensive AI trading platform that integrates real-time market data, news feeds, and sentiment analysis to drive your options strategies. I will implement a custom engine to calculate technical indicators like Wave Trend and VWAP, allowing the system to automatically identify and execute calls, puts, and multi-leg spreads via your broker API. The platform will include a dedicated risk management module to handle position sizing, margin checks, and volatility shocks before orders are sent. I will also develop an interactive dashboard for you to monitor P&L, open positions, and model confidence in real time. 1) Which specific broker API are you planning to use for execution? 2) Do you have a preferred source for the social media and news data feeds? 3) Should the dashboard be a web-based interface or a desktop application? Thanks, Bharat

@prashanpatel557

Hello, I can design and build your AI-driven options trading platform with modular architecture, real-time analytics, and automated execution. Proposed architecture: 1. Data Layer Streaming market data + historical time-series ingestion. Integrate technical indicators (WaveTrend, VWAP, volatility metrics). Efficient pipeline using Python, pandas, and asyncio. 2. AI / Strategy Engine ML models (scikit-learn or TensorFlow) for signal prediction and strategy selection. Module capable of identifying optimal structures such as: • Calls / Puts (buy or sell) • Vertical spreads • Straddles / Strangles • AI-selected multi-leg strategies. Model confidence scoring and trade ranking. 3. Risk & Portfolio Management Position sizing based on volatility and margin availability. Max-loss cutoffs, exposure limits, and volatility shock protection. Pre-trade validation before order execution. 4. Execution Engine Broker API integration (IBKR / Zerodha / Tradier). Smart order staging and position monitoring. Latency-optimized pipeline for fast execution. 5. Dashboard & Backtesting Real-time dashboard showing positions, PnL, model confidence, and risk metrics. Backtesting engine with historical replay and strategy evaluation. Deliverables: • Full source code and deployable system • Strategy configuration module • Backtesting framework • Documentation and deployment guide Ready to discuss data sources, broker choice, and milestone timeline.

@prabhathk5

Thanks for sharing the details. I’ve reviewed your requirement and would be glad to discuss it further. I’m Prabhath, an experienced MQL4/MQL5, Pine Script, Python, and C++ developer specializing in automated trading systems and institutional-grade algorithmic solutions. I develop Expert Advisors, indicators, dashboards, data tools, and custom trading utilities for MT4/MT5, TradingView, and standalone platforms. Along with MQL5 systems, I also build fully automated trading software in Python and C++ for Indian stock markets and global exchanges (US, EU, and others). These solutions can be tailored for stocks, indices, futures, forex, and crypto based on project needs. As an active trader, I work with ICT, SMT, market structure, liquidity models, order blocks, FVGs, VWAP, and volume-based logic, ensuring each strategy follows the client’s trading methodology. My expertise includes institutional-grade EA and indicator development, ICT/SMT-based trading systems, Pine Script automation, Python and C++ systems for Indian and global markets, backtesting, paper trading and live trade integration, strategy optimization, and low-latency execution. I also fix, optimize, and enhance existing trading systems to make them stable and production-ready. Where permitted, I can share demos or walkthroughs of previously completed projects while respecting client confidentiality. Thank you for your time and consideration.

@ahmedtahash

I am certain that I can build a modular AI trading system combining real-time market data, options strategy intelligence, and automated execution. The solution will use Python with high-performance data pipelines, predictive modeling, and broker API integration. Risk controls, latency optimization for VPS deployment, and a backtesting engine will validate performance metrics including Sharpe ratio and drawdown limits. A clean dashboard will track P&L, confidence scores, and open positions with clear documentation for maintenance. Quick question: which broker API and options market data source will the bot primarily trade and analyze from (e.g., IBKR, Tradier, or others)? Regards, Ahmad Al-Ashery.

@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

@Hemantt841

You’re looking to build a fully automated AI-driven options trading platform that handles complex strategies like multi-leg spreads and straddles, while integrating real-time market data, sentiment analysis, and risk management. The system must also execute trades via broker APIs with low latency and offer a configurable strategy module alongside a back-tester for performance validation. With over 15 years of experience and more than 200 projects completed, I specialize in Python development, API integration, and AI-driven predictive analytics, making me well-suited to deliver your algorithmic trading bot. My background includes building robust automation systems that combine data science and machine learning to operate reliably in live market environments. I propose architecting the solution using Python with libraries such as pandas, TensorFlow, and scikit-learn for data processing and modeling, integrated with broker APIs like IBKR for execution. The workflow will ensure data cleansing, predictive modeling, risk checks, and order placement within your 250 ms latency target. I estimate initial milestones—data integration and model prototyping—within 3 weeks, followed by back-testing and deployment phases. Let’s discuss how I can tailor this system to your specific strategies and timeline.

@PyMLExpert1

I am thrilled to introduce myself, Zainab, as a seasoned Python and Machine Learning Expert who focuses on architecting and deploying end-to-end AI solutions. I believe my strong command over sophisticated algorithms, extensive work with large-scale datasets and my depth expertise in delivering predictive analytics will make a progressive contribution to your AI-driven options trading platform project. My proficiencies in tools like pandas, scikit-learn, TensorFlow matched with hands-on experience in designing and implementing complex architectures aligns perfectly with your project requirements. Addressing your needs for real-time market analysis, my acquired skills fuse essential data sources such as live feeds, historical time-series data, news insights, social media sentiments and technical indicators with precision. Automation is the key; I ensure automated trade execution through a broker API while effectively using order staging, smart routing and maintaining position monitoring for efficient risk management. My main objectives are to develop a fully operational trading bot that allows for toggling various options strategies through a configurable strategy module (buying/selling, spreads and more) supported by an effective risk management layer with editable limits and alerting. Additionally, I envisage developing a powerful back-tester which replays historical data to establish crucial edge and drawdown parameters.

@rahulb617

hi , i have made bots for binance,fyers,shoonya for my clinets i can help u build with ai implementation and all your requirements

@niketu88

Hi, What you’re describing is essentially a quant options trading platform, not just a trading bot. To build it properly, the system should be modular and phased. Architecture I propose: 1. Data Layer - Live options chain + historical data ingestion - News & sentiment feed processing 2. Strategy Engine - Technical indicators (VWAP, Wave Trend, volatility metrics) - AI model (XG Boost/LSTM) predicting directional bias & volatility regime - Strategy selector (buy/sell, spreads, straddles, strangles) 3. Risk Engine - Position sizing - Margin checks - Max loss / volatility shock controls 4. Execution Layer - Broker API integration (IBKR/Tradier/Zerodha) - Order lifecycle management 5. Research & Dashboard - Backtesting framework - Real-time PnL & risk metrics dashboard Because of the system complexity, I recommend building Phase 1 (data + strategy + execution) first. Let’s discuss broker choice and options data source before defining milestones.

@bhartimalu

Hello, I can develop your options trading algorithm with strategy logic implementation, real-time market data processing, entry/exit conditions, and proper risk management (SL/TP, position sizing). I have experience working with algorithmic trading systems and Python-based financial analysis, ensuring reliable execution and structured outputs. Please share the strategy details and broker/API you plan to use so I can confirm timeline and cost. Ready to start immediately. Regards, Bharti M

@michaelh314

I've built autonomous stock trading systems with AI/ML pipelines, including a production WolfOW trading bot. This project aligns perfectly with my expertise in: • Python, TensorFlow, scikit-learn for predictive models • IBKR and Tradier API integration for automated execution • Options strategies (spreads, straddles, delta-neutral) • Risk management systems with position sizing and max-loss cutoffs • Backtesting engines with Sharpe ratio optimization I can deliver Phase 1 with a working paper-trading bot in 7 days. Let's discuss your preferred broker API and specific strategy requirements.

@lawrencey4

I can build a Python architecture for your options bot with strategy modules, broker API execution, risk controls, and backtesting flow. I will structure delivery in milestones and provide clean documentation.

@simar2176

Hello, Greetings of the day !! I reviewed your requirement for building an AI-driven options trading platform capable of executing complex strategies automatically, and this aligns closely with my experience in Python-based trading systems, data pipelines, and AI/ML-driven analytics platforms. I am a Senior Python & AI Developer with 6+ years of experience, previously working with TCS and Infosys, and recently building algorithmic trading tools, real-time analytics systems, and automation platforms for international clients. For your platform, I would design a modular trading architecture that separates data ingestion, strategy intelligence, risk management, and execution. The data engine would collect real-time market data, historical options chains, news feeds, and sentiment signals. These inputs would feed into predictive models and signal generation modules using libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow. Technical indicators like VWAP, Wave Trend, volatility metrics, and momentum indicators can be integrated to improve signal quality. I’d be happy to discuss architecture, broker integration, and milestones to move from paper trading to a stable live trading system. Best regards, Mohit Sharma Senior Python & AI Engineer Algorithmic Trading | ML Systems | Quant Analytics | Automation ?

@arvindk126

Hello, I can help build your AI-driven options trading platform. I have 7+ years of trading experience and strong expertise in developing automated trading and AI-based financial systems. For this project, I would design a modular architecture that combines real-time market data, historical analysis, sentiment signals, and technical indicators (VWAP, Wave Trend, momentum models) to identify optimal options strategies including calls, puts, spreads, straddles, and strangles. The system will include: • Real-time data pipeline for quotes, news, and sentiment • AI prediction engine using Python (pandas, scikit-learn / TensorFlow) • Strategy selector that evaluates risk-reward for multi-leg option structures • Automated execution layer integrated with broker APIs (IBKR, Tradier, Zerodha) • Risk-management module with position sizing, margin checks, and auto-shutdown rules • Backtesting engine to validate strategies on historical SPX options data • Live dashboard showing positions, P&L, model confidence, and risk metrics

@bhuvans39

Hello, I have experience in Python, Machine Learning, API integration, and data analysis. I understand the requirements for building an automated trading system with real-time data processing, risk management, and strategy execution. I can design the system using Python with libraries like pandas, scikit-learn, and API integration for broker connectivity. I will ensure clean code, proper testing, and clear documentation. I am ready to start immediately and discuss the architecture and milestones.

@hassam945

As an AI and Machine Learning specialist, I’ve amassed a wealth of experience in constructing intelligent systems from start to finish, perfectly aligning with the demands of your AI Options Trading Algorithm project. Over the years, I've applied my skill set to domains such as Computer Vision and Natural Language Processing (NLP), allowing me to effortlessly fuse historical data, news feeds, sentiment analysis, and technical indicatorsthe exact mix your platform needs for real-time market analysis. My expertise in supervised, unsupervised, and reinforcement learning ensure intelligent algorithm selection, trade evaluation, and risk management to optimize results. A standout feature of my past projects is their sustainable architecture and optimized performance—precisely what you are looking for in a real-time trading system. These include systems as diverse as Diabetic Retinopathy detection using medical imaging to sentiment analysis using Transformers. Throughout these projects, I deployed clean code that delivered high diagnostic accuracy under stringent conditions. In addition to my engineering intuition, I value timely communication and consistent delivery which is what sets me apart from others who could tackle this project. Allow me to bring my unique blend of skill, experience and commitment to bear on your project; you'll hardly be disappointed!

@margit8

I am the best candidate for this project because i have a strong interests in technology, artificial