Client Success Story: Algorithmic Strategy Development

This is the story of a client who needed help developing an algorithmic trading strategy, starting with backtesting. The successful completion of this phase led to more projects, showcasing the client's trust in my skills and expertise.

The Problem Statement

The client sought a Python developer to build an algorithmic strategy for backtesting purposes, using data from the Fyers API. The goal was to create a backtesting system that would execute within Jupyter Notebook and handle part 1 of a larger 3-part project. The client also required pre-existing code for calling Fyers APIs to be integrated into the solution.

Job Description

The Solution

I created Python scripts for backtesting the algorithmic strategy. The solution was developed with a strong focus on flexibility and efficiency, resolving any bugs that emerged along the way. After successfully completing this project, I continued working with the client, developing more features like live tick updates, automatic order placement, and historical data fetching. These scripts were executed through APIs from both Fyers and Zerodha, making them robust, reliable, and scalable.

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