Stock Backtesting Web App Dev
Budget: ₹37,500 – ₹75,000 INR
Project Overview:
Looking for a skilled freelancer to assist in developing a web-based backtesting software specifically designed for the Indian stock market. The software will allow users to backtest trading strategies using historical market data, with the flexibility to test across various asset classes, timeframes, and strategies. The platform will be integrated with a Backtrader API, a powerful Python library designed for backtesting, live trading, and data analysis.
Core Requirements:
Web Development Expertise:
Frontend: Proficiency in modern web technologies like React.js, Vue.js, or Angular for a responsive and user-friendly interface.
Backend: Experience with Python and frameworks like Django or Flask for the server-side development, handling API requests, and ensuring smooth communication between the frontend and backend.
Backtesting & Trading Knowledge:
In-depth knowledge of Backtrader API to implement trading strategies, integrate market data feeds, and execute strategy backtests.
Understanding of key financial and trading concepts, including moving averages, technical indicators, entry/exit conditions, risk management, and multi-timeframe analysis.
Experience in algorithmic trading and financial data analysis.
Database Management:
Proficiency in SQL/NoSQL databases for storing historical market data and backtesting results.
Experience in data pipeline creation to import, clean, and store historical data from sources like NSE and BSE.
Cloud Integration:
Familiarity with AWS, Google Cloud, or Azure for deploying the web-based app with scalability, security, and high availability in mind.
Experience with serverless architectures, microservices, or Docker/Kubernetes for containerized deployments.
APIs & Data Integration:
Experience in integrating market data APIs (such as from NSE/BSE or any third-party financial data providers) into the backtesting engine.
Working knowledge of RESTful APIs and WebSockets for real-time data streaming.
User Authentication & Management:
Implement secure user authentication using OAuth2, JWT tokens, or similar protocols.
Develop user roles for different levels of access (e.g., admin, traders, viewers).
Performance Optimization:
Proficiency in optimizing backtesting engines to handle large data sets efficiently.
Experience in running multi-threaded or distributed backtesting to ensure scalability and faster results.
Desirable Skills:
Experience with financial libraries like Pandas, NumPy, and TA-Lib for strategy development.
Knowledge of cloud-based logging and monitoring tools (e.g., Prometheus, Grafana).
Prior experience building trading platforms or financial software would be highly advantageous.
Looking for a skilled freelancer to assist in developing a web-based backtesting software specifically designed for the Indian stock market. The software will allow users to backtest trading strategies using historical market data, with the flexibility to test across various asset classes, timeframes, and strategies. The platform will be integrated with a Backtrader API, a powerful Python library designed for backtesting, live trading, and data analysis.
Core Requirements:
Web Development Expertise:
Frontend: Proficiency in modern web technologies like React.js, Vue.js, or Angular for a responsive and user-friendly interface.
Backend: Experience with Python and frameworks like Django or Flask for the server-side development, handling API requests, and ensuring smooth communication between the frontend and backend.
Backtesting & Trading Knowledge:
In-depth knowledge of Backtrader API to implement trading strategies, integrate market data feeds, and execute strategy backtests.
Understanding of key financial and trading concepts, including moving averages, technical indicators, entry/exit conditions, risk management, and multi-timeframe analysis.
Experience in algorithmic trading and financial data analysis.
Database Management:
Proficiency in SQL/NoSQL databases for storing historical market data and backtesting results.
Experience in data pipeline creation to import, clean, and store historical data from sources like NSE and BSE.
Cloud Integration:
Familiarity with AWS, Google Cloud, or Azure for deploying the web-based app with scalability, security, and high availability in mind.
Experience with serverless architectures, microservices, or Docker/Kubernetes for containerized deployments.
APIs & Data Integration:
Experience in integrating market data APIs (such as from NSE/BSE or any third-party financial data providers) into the backtesting engine.
Working knowledge of RESTful APIs and WebSockets for real-time data streaming.
User Authentication & Management:
Implement secure user authentication using OAuth2, JWT tokens, or similar protocols.
Develop user roles for different levels of access (e.g., admin, traders, viewers).
Performance Optimization:
Proficiency in optimizing backtesting engines to handle large data sets efficiently.
Experience in running multi-threaded or distributed backtesting to ensure scalability and faster results.
Desirable Skills:
Experience with financial libraries like Pandas, NumPy, and TA-Lib for strategy development.
Knowledge of cloud-based logging and monitoring tools (e.g., Prometheus, Grafana).
Prior experience building trading platforms or financial software would be highly advantageous.