Build Intraday NSE Trading Algo

@mahads31

Building high-impact digital products that solve complex problems is what I excel at, and I'm thrilled at the prospect of taking your proprietary intraday strategies and transforming them into clean, production-ready Python code. My skills in C++ Programming and Python make me perfectly suited for this job where performance and reliability are paramount. Beyond just translation, I appreciate the need for a thoughtful and robust validation of your algorithm's compatibility with historical data. To this end, I specialize in creating meticulous back-test harnesses which ensure the parallel testing of strategies against live market feeds. My experience working with Python libraries like Pandas, NumPy, ta-lib, as well as broker SDKs such as Kite or FYERS further equip me for this project. I’ve also done previous intraday trading projects on NSE and can provide evidence of my successful ventures in this space upon our collaboration. Choose me for an efficient, reliable and auditable algorithmic strategy solution, Mahad Sheikh.

@vishal1145

Your biggest risk is order-slippage during NSE volatility windows — if your execution layer doesn't account for partial fills or tick delays above 50ms, your back-test will show profit while live trading bleeds capital. I've built similar systems for 2 prop desks where we shaved latency from 200ms to under 30ms by pre-validating orders before the broker API call. Quick questions - are you expecting sub-second tick processing, or is minute-bar resolution acceptable? And does your broker API support bracket orders natively, or do we need to manage stop-loss logic in-app? Here is the architectural approach: - ALGORITHMIC TRADING: Build a deterministic event-driven engine where strategy logic, order execution, and risk checks run in isolated modules so you can swap rules without rewriting the pipeline. - BACKTESTING: Create a tick-replay harness using Pandas that mirrors the live feed structure exactly, logs every decision with timestamps, and outputs performance metrics identical to production so there's zero discrepancy. - C++ PROGRAMMING: Wrap latency-critical sections in Cython or pybind11 if Python proves too slow during live tick ingestion, ensuring sub-100ms order placement without a full rewrite. I've deployed 4 NSE algo systems over the past 6 years, including one that handled 12K orders daily with zero manual intervention. Let's schedule a 20-minute call to walk through your strategy flow before I commit timelines.

@Algokage

Hello, I hope you're doing well. I am an experienced algorithmic trading developer with over 4 years of expertise in building and deploying intraday strategies on the National Stock Exchange. I've successfully translated proprietary strategies into production-ready Python code, integrating live market feeds, broker APIs, and back-testing frameworks. For your project, I'll use Pandas, NumPy, and ta-lib to implement your logic, handle edge cases, and ensure deterministic behavior. I'll also create a simple config file for parameter adjustments and provide detailed logging for every decision. I deliver clean, well-documented code and can share a GitHub link of a previous back-test I built. Message me to discuss timelines for the prototype, back-testing module, and final production version. Thanks, Adegoke M.

@ammarahmed20

My name is Ammar Ahmed Malik and I have spent the past 6+ years building intelligent systems that automate complex tasks, utilizing an array of technologies and languages with a prime focus on AI. Market analysis and trading are domains I'm well-versed in, and I've observed that your project aligns closely with my experience building AI-driven trading applications. My skillset extends to Python, C and C++, all crucial to effieciently crafting robust and reliable algorithms - just what you require for this project. I understand that translating your proprietary intraday strategies into clean, production-ready Python using live market feeds and targeted broker API integration is the main objective. You need a reliable code that can handle edge cases, minimize data lags, log every decision without fail and provide comprehensive back-testing capabilities. My wide-ranging experiences across healthcare, e-commerce, real estate, and SaaS including automation work using tools such as Kite or FYERS give me a unique perspective that I can bring to your NSE trading system. Regarding the timeline of the project, I assure you timely deliverables without compromising quality. With my first working prototype with hard-coded parameters, completed back-testing module with a detailed sample report, and eventually a fully production-ready version with fine-tuning options within the stipulated timeframe.

@shayankhan333

Hello, I will translate your intraday NSE strategies into production-ready Python, wire in live feeds, place orders via your broker API, and build a back-test harness that replays historical ticks alongside the live engine. I can start today. For the Kite or FYERS SDK, I will handle partial fills and data lags, log every decision, and expose parameters in a config file. Questions: 1) Which broker SDK, Kite or FYERS? 2) What tick history format do you have for back-testing? Looking forward to discussing further. Regards, Shayan.

@forsalee

Hi — I went through the full brief for “Build Intraday NSE Trading Algo”. My understanding is that the important part is: Your code should accept live market feeds, apply my logic in real time, and place orders automatically through the broker API I’ll provide. I’d first reproduce the requested behavior and isolate the smallest reliable implementation. Then I’d write the Python solution with clear validation/error handling rather than hiding failures. Before handover, I’d test the main scenario and provide clean source files plus concise run instructions. My work is focused on Python automation, debugging and practical scripts that are easy to run and maintain. Is there existing code to continue from, and what result will you use to consider the task complete? For the scope currently described, I’d quote ₹19500 INR and about 4 days.

@bhargav922002

Hello, I'm Bharghav, and I bring a decade of experience in matching job skills with specific project requirements, particularly in areas like C Programming, Python, Software Architecture, and C++ Programming. My background equips me to understand and efficiently translate trading strategies into robust software solutions. I've carefully reviewed your need for an intraday trading algorithm for the National Stock Exchange. My plan involves developing a clean and production-ready Python application that can seamlessly integrate live market feeds, implement your proprietary strategies, and automate order placements through your broker's API. I will ensure that edge cases are meticulously handled and that every decision is logged reliably. Additionally, I will create a back-testing module that will allow you to validate performance using historical data before going live. With familiarity in tools like Pandas, NumPy, and various broker SDKs, I am confident in delivering a solution that meets your requirements. Let's start a chat to delve deeper into your project and discuss the timelines for the prototype and final versions. Best regards, bhargav922002