Penny Stock Trading Bot Development
Budget: $50 – $0 USD
I'm seeking a skilled AI & algorithmic trading expert to create a penny stock trading bot. The bot's primary function will be automated trading, utilizing a trend following strategy.
Key Requirements:
- The bot must integrate seamlessly with Interactive Brokers and TD Ameritrade.
- Proficiency in AI and algorithmic trading development is crucial.
- Experience with penny stock trading is a plus.
- Knowledge and practical application of trend following strategies in algorithmic trading.
We are looking for an experienced AI & Algorithmic Trading Developer to build an AI-driven penny stock trading bot that can identify breakouts, predict momentum shifts, and execute trades automatically. The bot should use machine learning, real-time data scanning, and automated trade execution to detect penny stocks hitting a 25% spike and ride them to 50-100% gains.
The ideal candidate should have expertise in AI/ML models for stock market predictions, financial data analysis, and API-based trading automation.
Key Responsibilities:
✅ Develop an AI model to detect penny stock breakouts before they hit a 25% gain.
✅ Integrate real-time stock data from APIs (Alpaca, Polygon.io, IEX Cloud) to scan for volume, momentum, and price surges.
✅ Implement NLP-based sentiment analysis using Reddit, Twitter, StockTwits to detect high-impact trends.
✅ Use deep learning models (LSTM, Reinforcement Learning) to predict stock price movements.
✅ Automate trade execution using Interactive Brokers (IBKR API), QuantConnect, or TradeStation API.
✅ Develop risk management protocols (stop-loss, trailing stop, position sizing, exit strategies).
✅ Optimize bot performance by continuously refining models and backtesting strategies.
Required Skills & Expertise:
? AI & Machine Learning for Stock Prediction:
Strong experience with LSTM, Reinforcement Learning (Deep Q-Learning, PPO, A3C).
Expertise in NLP (Sentiment Analysis, BERT, Transformer Models) for tracking Reddit, Twitter, StockTwits trends.
Experience in Anomaly Detection (Autoencoders, Isolation Forests) to filter real breakouts vs. fake pumps.
? Real-Time Market Data Integration:
Experience with Alpaca, Polygon.io, IEX Cloud for live stock price & volume tracking.
Knowledge of Unusual Whales, FlowAlgo APIs for options flow analysis.
Ability to scrape & process news data for catalyst detection.
? Algorithmic Trading & API Integration:
Hands-on experience with IBKR API, QuantConnect, TradeStation API for trade automation.
Experience using Backtrader, Zipline, or QuantConnect for backtesting strategies.
Strong understanding of VWAP, EMA, RSI, MACD-based trading signals.
?️ Cloud Deployment & Automation:
Ability to deploy AI models to AWS Lambda, Google Cloud Functions, or Azure.
Experience with PostgreSQL, MongoDB, Firebase for trade data storage & logging.
Proficiency in Flask/FastAPI, Docker, Kubernetes for building scalable systems.
? Preferred Experience:
✔ Previous experience building AI-powered trading bots (penny stocks preferred).
✔ Strong knowledge of low-float stocks, pre-market gappers, and high-volume runners.
✔ Understanding of high-frequency trading (HFT), market microstructure, and order book analysis.
✔ Ability to optimize execution speed (low-latency API calls, efficient order routing).
? Deliverables:
1️⃣ AI-Powered Penny Stock Scanner
Real-time tracking of momentum stocks, volume surges, and breakouts.
AI model to predict stocks likely to surge before they hit 25% gains.
Sentiment analysis from Reddit, Twitter, StockTwits.
2️⃣ Automated Trading Execution System
Trade execution via IBKR API, QuantConnect, or TradeStation.
Configurable buy/sell signals, stop-loss, and risk management strategies.
3️⃣ Backtesting & Optimization Dashboard
Historical data analysis to improve accuracy of AI predictions.
Performance tracking (win rate, risk-adjusted returns, Sharpe ratio, drawdowns).
Key Requirements:
- The bot must integrate seamlessly with Interactive Brokers and TD Ameritrade.
- Proficiency in AI and algorithmic trading development is crucial.
- Experience with penny stock trading is a plus.
- Knowledge and practical application of trend following strategies in algorithmic trading.
We are looking for an experienced AI & Algorithmic Trading Developer to build an AI-driven penny stock trading bot that can identify breakouts, predict momentum shifts, and execute trades automatically. The bot should use machine learning, real-time data scanning, and automated trade execution to detect penny stocks hitting a 25% spike and ride them to 50-100% gains.
The ideal candidate should have expertise in AI/ML models for stock market predictions, financial data analysis, and API-based trading automation.
Key Responsibilities:
✅ Develop an AI model to detect penny stock breakouts before they hit a 25% gain.
✅ Integrate real-time stock data from APIs (Alpaca, Polygon.io, IEX Cloud) to scan for volume, momentum, and price surges.
✅ Implement NLP-based sentiment analysis using Reddit, Twitter, StockTwits to detect high-impact trends.
✅ Use deep learning models (LSTM, Reinforcement Learning) to predict stock price movements.
✅ Automate trade execution using Interactive Brokers (IBKR API), QuantConnect, or TradeStation API.
✅ Develop risk management protocols (stop-loss, trailing stop, position sizing, exit strategies).
✅ Optimize bot performance by continuously refining models and backtesting strategies.
Required Skills & Expertise:
? AI & Machine Learning for Stock Prediction:
Strong experience with LSTM, Reinforcement Learning (Deep Q-Learning, PPO, A3C).
Expertise in NLP (Sentiment Analysis, BERT, Transformer Models) for tracking Reddit, Twitter, StockTwits trends.
Experience in Anomaly Detection (Autoencoders, Isolation Forests) to filter real breakouts vs. fake pumps.
? Real-Time Market Data Integration:
Experience with Alpaca, Polygon.io, IEX Cloud for live stock price & volume tracking.
Knowledge of Unusual Whales, FlowAlgo APIs for options flow analysis.
Ability to scrape & process news data for catalyst detection.
? Algorithmic Trading & API Integration:
Hands-on experience with IBKR API, QuantConnect, TradeStation API for trade automation.
Experience using Backtrader, Zipline, or QuantConnect for backtesting strategies.
Strong understanding of VWAP, EMA, RSI, MACD-based trading signals.
?️ Cloud Deployment & Automation:
Ability to deploy AI models to AWS Lambda, Google Cloud Functions, or Azure.
Experience with PostgreSQL, MongoDB, Firebase for trade data storage & logging.
Proficiency in Flask/FastAPI, Docker, Kubernetes for building scalable systems.
? Preferred Experience:
✔ Previous experience building AI-powered trading bots (penny stocks preferred).
✔ Strong knowledge of low-float stocks, pre-market gappers, and high-volume runners.
✔ Understanding of high-frequency trading (HFT), market microstructure, and order book analysis.
✔ Ability to optimize execution speed (low-latency API calls, efficient order routing).
? Deliverables:
1️⃣ AI-Powered Penny Stock Scanner
Real-time tracking of momentum stocks, volume surges, and breakouts.
AI model to predict stocks likely to surge before they hit 25% gains.
Sentiment analysis from Reddit, Twitter, StockTwits.
2️⃣ Automated Trading Execution System
Trade execution via IBKR API, QuantConnect, or TradeStation.
Configurable buy/sell signals, stop-loss, and risk management strategies.
3️⃣ Backtesting & Optimization Dashboard
Historical data analysis to improve accuracy of AI predictions.
Performance tracking (win rate, risk-adjusted returns, Sharpe ratio, drawdowns).