NSE Options Algo with Backtest

@gowthamsarathy

vanakkam bro Hello, I'll develop a modular algorithmic trading system that separates strategy logic, broker integration, risk management, backtesting, and reporting into independent components. This approach allows your proprietary NSE options strategy to remain fully parameterized, making it easy to modify filters, lot sizes, strikes, instruments, and timeframes through configuration without changing the core trading engine. The platform will integrate with Angel One SmartAPI, Upstox, or Delta Exchange APIs for automated execution, order management, and live monitoring while providing comprehensive backtesting with equity curves, drawdown, win rate, and trade analytics. Since I actively trade myself, I understand the importance of execution speed, position synchronization, and reliability in live trading environments, which helps shape the overall system design. The final delivery will include well-documented Python source code, configurable strategy settings, VPS/local deployment, paper-trading validation, comprehensive backtest reports, and a hand-off session covering deployment, monitoring, and future strategy updates. Relevant Work: https://www.freelancer.in/portfolio-items/11493278-algorithmic-trading-bot-for-mt5 https://www.freelancer.in/portfolio-items/11493462-nyse-and-nasdaq-algo-trading-platform https://www.freelancer.in/portfolio-items/11493491-mt4-mt5-trade-copier Kind regards, Gowtham

@onkarkulkarni8

Hello, I checked your "NSE Options Algo with Backtest" project and it looks like understanding the existing workflow will be important before making any changes. I've worked on similar PHP projects involving c programming, python, software architecture, c++ programming, financial analysis, restful api, data visualization, data analysis, financial modeling, backtesting and prefer delivering work in small milestones so everything stays easy to review and adjust if needed. If you can share a few more details about the current setup and expected outcome, I'll suggest the best approach and provide an accurate timeline. ⭐ 5.0/5 from a recent client: "Project was delivered before Time with Best professional Knowledge One could ever held. Thanks for the support" Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@ashinnd84

Hello Sir/Madam, we are a team of senior AI ML Full Stack Web and Mobile App Developers. Please, send me a message to discuss the work and finish in no time. Thanks Ashish Kumar.

@vishal1145

Your Angel One integration will fail in production if the WebSocket feed drops during volatile market hours and your bot does not reconnect automatically. That means missed exits and unhedged positions sitting overnight. Quick questions - are you planning to run multiple strategies in parallel that share the same margin pool, and do you need real-time Greeks calculation or just delta-neutral rebalancing triggers? Here is the architectural approach: - ANGEL ONE SMARTAPI: Build fault-tolerant WebSocket handler with exponential backoff reconnection, order state machine tracking pending/filled/rejected transitions, and position reconciliation on every reconnect to prevent duplicate orders. - BACKTESTING MODULE: Implement vectorized backtesting engine in Python using pandas for tick-level NSE options data, generate PDF reports with Sharpe ratio, max drawdown, win rate, and equity curve visualizations using matplotlib. - PARAMETERIZED CONFIG: Design JSON-based strategy config separating entry filters, strike selection logic, lot sizing rules, and risk parameters so you modify thresholds without redeploying code or restarting the process. I've built 4 algo-trading systems for NSE derivatives that processed 12K+ orders daily without manual intervention. Let's schedule a 20-minute technical call to review your rule logic and finalize the state-machine design before we write a single line of code.

@NEHABHAT92

I appreciate your consideration, and I believe my skill set could be invaluable for your options trading project. In a world where milliseconds can make or break a trade, my 9+ years of experience in web and mobile development means that not only am I proficient in Python, but, also closely understand the values of efficiency and reliability that are crucial to your project. This proficiency extends to websockets which are essential to your data requirements. In past projects, I have leveraged back-testing frameworks like pandas, Zipline, and Backtrader to ensure the accuracy of historical price data; delivering comprehensive reports on key metrics like equity curve, draw-down, win-rate et cetera - factors critical for successful implementation of any trading algorithm. These skills and more can help me hit your required target off 95% accuracy while matching your trades. Moreover, by dedicating myself fully to this project, I guarantee you a thorough comprehension of your proprietary rules and the development of a highly-customizable system as per your needs. I also understand the essence of a swift hand-off given dynamic cryptocurrency ecosystems like BTC I'd proactively bridge any knowledge gap you might anticipate during deployment ensuring you feel fully comfortable running and updating the final product.

@prabhathk5

Hello, I have already developed a very similar automated trading system for the Indian market using broker APIs. The project included: * Fully automated rule-based execution through broker APIs (entry, exit, SL, TP, and risk management) * Configurable strategy parameters without modifying the core code * Historical backtesting with detailed performance metrics (equity curve, drawdown, win rate, P&L, etc.) * Live paper trading and real-time order execution * VPS deployment and post-deployment support I have experience working with **Angel One SmartAPI, Upstox, Zerodha Kite Connect, MT5, and TradingView integrations**, along with Python-based trading systems using WebSocket and REST APIs. Your requirements are well within my expertise. I can build a clean, modular, and well-documented solution that supports: * Automated NSE options trading * Easy-to-edit configuration for instruments, lot size, strikes, and timeframes * Comprehensive backtesting and analytics * Live paper trading before production * VPS deployment and complete source code with documentation I'd be happy to discuss your proprietary trading rules under NDA if required. Once I understand the strategy logic, I can provide an accurate timeline and development plan. Please take a look at my Freelancer profile for similar trading automation projects and client reviews. I look forward to working with you. Best regards, Prabhath Python | Algorithmic Trading | Broker API | Trading Automation Developer

@Algokage

Hello, I hope you're doing well. I am an experienced algorithmic trading developer with over 6 years of expertise in building and deploying automated trading systems, including NSE options strategies integrated with platforms like Angel One and Upstox. I’ve successfully delivered rule-based systems with parameterized controls, back-testing modules, and live deployment setups, ensuring seamless execution and easy customization. For this project, I’ll start by coding the strategy to automate order placement, modification, and squaring off on Angel One, using Python for its compatibility with REST/WebSocket APIs. I’ll build a robust back-testing module that generates key metrics like equity curve and draw-down in a clear PDF report. A simple config file will allow you to adjust instruments, strikes, and timeframes without altering the core code. Once the system is ready, I’ll assist with live deployment on a VPS or local machine and provide a hand-off session to ensure you’re comfortable managing the bot. I deliver clean, well-documented code and have prior experience with NSE options and Angel One. If you’d like, I can share a brief demo or screenshots of past performance analytics to showcase my work with back-testing frameworks like pandas and Backtrader. Let’s discuss this further to ensure we align on your requirements. Thanks, Adegoke M.

@FreeLancers360

Hello, I just finished reading your brief for "NSE Options Algo with Backtest", and I'm genuinely excited about the chance to work on it. What stood out to me is how clearly you’ve described what you want — and clarity like that is where we deliver our very best work. From your brief I can see this involves analytics, dashboard — all areas we handle in-house. We specialise in C Programming, Python, Software Architecture, C++ Programming, which lines up directly with what you need. How we'd approach it: - Define the exact fields, sources and output format - Build the collection / processing pipeline - Validate accuracy and clean the data - Deliver in your preferred format with a short summary I also noted you don’t need touching the core code — that’s clear, and I’ll keep the work clean and strictly on-brief. Expect smooth progress updates throughout, full respect for your specifications, and zero surprises along the way. If it helps, I can share a couple of relevant samples and a short plan before you decide. Looking forward to it! Best regards, FreeLancers360 Let’s connect in chat and get started — message me anytime and I’ll reply right away!

@alluankit01

Hi, I can build your NSE options trading algo with Python, Angel One SmartAPI/Upstox support, parameterized strategy rules, backtesting, paper trading, reporting, and deployment guidance. The best solution is to first review your entry, exit, strike selection, lot size, timeframe, stop-loss, target, trailing stop, and risk rules. I’ll then code the strategy in a clean modular structure with a config file so you can change instruments, strikes, filters, and lot sizes without editing core code. I’m comfortable with Python, Angel One SmartAPI, REST/WebSocket APIs, options trading logic, backtesting, pandas, Backtrader-style workflows, VPS deployment, order placement, modify/square-off logic, and performance reporting. Deliverables include: * Python trading bot * Angel One/Upstox API integration * Configurable strategy parameters * Entry/exit/risk logic * Backtesting module * Equity curve and drawdown report * Win-rate and trade metrics * Paper-trading test support * Clean commented source code * VPS/local deployment guide * Handover session No profit is guaranteed, but I’ll build a clear, testable, and risk-controlled system that follows your rules accurately. Best regards Ankit

@geethasekar1995

Hello, I am from chennai. i am already developed scanner and autotrade, developed indicator, stratergy I have over 8 years of experience in .NET development and have hands-on experience building algorithmic trading applications for the Indian stock market. I have worked with broker APIs, including Angel One SmartAPI, Upstox, and market data integration, developing solutions for automated trading, live market feeds, order execution, and risk management. I can build a configurable rule-based trading system that automates your options strategy without requiring code changes for parameter updates. The solution will support live order placement, modification, square-off, stop-loss, target management, position sizing, and comprehensive risk controls. I can also develop a backtesting engine using historical market data to generate detailed performance reports, including equity curves, drawdown, win rate, profit/loss, and trade analytics. The application will include a configuration panel for instruments, strikes, lot sizes, expiry selection, and trading timeframes. The code will be modular, well documented, and designed for future strategy enhancements. I will also assist with deployment on a VPS or local machine, paper trading validation, and provide complete source code with a handover session. I would be happy to discuss your strategy and help build a reliable, production-ready automated trading platform. Thank you for your consideration.

@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 17) Binance Bitcoin tradingview strategy python bot 18) Fyers Tradingview python bot 19) Dhan Python order manager I can deliver any project in Trading. Readymade setups for Python available

@kanwaljeetk56

Hi, I have expertise writing strategies to backtest and to implement the algo trading. I have developed more than 500 commercial strategies and can show you live demo of backtest result with fully Algo trading.

@thiagofoz87

Your project requires two things to work reliably together: deterministic strategy execution and accurate historical simulation. The main risk in algo-trading systems is divergence between backtest behavior and live execution, so I would structure the solution around a shared execution engine used by both the backtester and the live trading module to keep rule interpretation consistent. I can build the system in Python using a modular architecture with: - strategy/risk engine separated from broker integration - Angel One SmartAPI integration (REST + WebSocket) - configurable parameters for strikes, lot size, filters and timeframe through config files or lightweight UI - backtesting pipeline with equity curve, drawdown, win rate and trade logs - paper-trading/live execution mode with detailed logging and fail-safe handling For the analytics/reporting layer, I can generate either PDF summaries or a lightweight dashboard depending on your preference. Historical replay accuracy, order lifecycle tracking and reproducibility will be priorities so the strategy behavior remains transparent and easy to validate against your manual trades. Deployment can be done on VPS or local machine with environment setup, monitoring guidance and a short handoff session included. Once you share the exact trading rules, I can estimate implementation phases more precisely and define the final validation checklist for backtest parity and live execution behavior.

@neerajkanti2703

Hi, I can build your NSE options trading system as a modular, fully automated Python application with support for Angel One (SmartAPI), Upstox, and Delta Exchange (BTC options/futures). The architecture will be parameter-driven, allowing you to modify lot sizes, filters, strikes, expiry selection, and risk parameters through a configuration file without changing the core strategy code. **Relevant Experience** * Developed multiple automated trading systems using **Python**, **Angel One SmartAPI**, **Upstox API**, **Delta Exchange API**, **TradingView (tvDatafeed)**. * Built rule-based and indicator-based strategies with automated order execution, position management, stop-loss, trailing stop, and risk controls. * Created custom backtesting engines with **pandas**, including detailed performance analytics such as equity curve, drawdown, win rate, profit factor, expectancy, and trade-by-trade reports. I will deliver a well-structured solution that includes automated execution, a comprehensive backtesting framework, configurable strategy parameters, deployment assistance, and a complete handover session. My priority is to ensure the live system closely matches the backtest logic so you can confidently transition from manual to automated trading. I look forward to discussing your strategy rules and turning them into a reliable production-ready trading system.

@Gurpreetsing343

As an established software development company, GSINFOTECHH OPC Pvt. Ltd. has the technical know-how and expertise to deliver precisely the kind of trading bot you're seeking—a rule-based approach on your proprietary options trading rules for NSE. We are well-versed in Python programming and have worked with major APIs, including WebSocket & REST, for seamless integration as required by Angel One’s platform. We also have an excellent understanding of platforms such as upstox and deltas exchange for btc. Additionally, we have a strong foundation in algorithmic trading and backtesting, utilizing frameworks such as pandas, Zipline, Backtrader to generate comprehensive reports that capture key metrics like equity curve, draw-downs, and win-rates just as you've outlined in your project objectives. Our rigorous testing methods will ensure that orders fire correctly and positions close as per your intentions both in paper-trading session and live deployment. Moreover, partnering with us means having access to various skills under one roof—the flexibility to use C++, if need be—and leveraging our experience developing similar solutions for clients who find it hard to operate actively owing to time-consuming manual processes. We can create a user-friendly configuration file or create a simple UI allowing easy switch-up between instruments, strikes, and timeframes without requiring manual code edits. Collaboration is key; let's build something amazing together!

@Chirag3147

Hi, I have experience developing automated trading systems in Python with broker API integrations, including Angel One SmartAPI, Upstox, and real-time WebSocket feeds. I can convert your rule-based NSE options strategy into a configurable trading bot with automated order execution, risk management, backtesting, performance analytics, and paper/live trading support. The solution will include a clean configuration interface, well-documented code, detailed reports, and deployment assistance on a VPS or local machine. I focus on reliable, maintainable, and production-ready trading systems and am ready to start immediately.

@morne01

INTRO I've recently helped a client automate their trading strategies, achieving remarkable results in the process. I will help you create a fully automated options-trading system tailored for the National Stock Exchange. MIDDLE I understand you need a clean and professional solution that can execute trades seamlessly while providing a comprehensive back-testing module. With expertise in Python and experience working with REST/WebSocket APIs, I can deliver a well-commented source code along with a user-friendly configuration setup. We have 75+ 5-star reviews on similar projects and rank in the top 1 % among 75 million users. OUTRO I look forward to helping you achieve your trading goals. Regards, MORNE.

@nikitau26

Понял задачу: нужен rule-based движок, где ваша логика входа/выхода живет в конфиге, а не в коде, чтобы вы сами могли крутить фильтры и лоты без моего участия. Backtest сделаю отдельным модулем на исторических данных: equity curve, drawdown, win-rate, все в PDF-отчете после каждого прогона (или простой Streamlit-dashboard, если удобнее смотреть интерактивно, скажите что предпочтительнее). Для реальной торговли возьму Angel One SmartAPI (REST + WebSocket под котировки и статусы ордеров), но сделаю отдельный адаптер под биржу/платформу, чтобы потом добавить Upstox или Delta Exchange для BTC без переписывания ядра стратегии. Этапы: 1. Core-движок стратегии + параметризуемый конфиг (инструмент, страйк, лот, таймфрейм) 2. Backtest-модуль с отчетом по метрикам 3. Исполнение через Angel One (постановка/модификация/закрытие ордеров) 4. Деплой на VPS + короткая сессия хендовера Срок 6 дней, 30000 INR за пункты 1-4 на Angel One. Delta Exchange под BTC добавлю отдельным этапом после проверки основной части, если понадобится, отдельно оценю. Вопросы: исторические данные для бэктеста уже есть у вас или собирать самому? PDF-отчет раз в прогон устроит или нужен живой dashboard? VPS для деплоя уже есть или тоже на мне?