Automating Financial Analytics with Python

In this project, I developed a tool designed to analyze various stock factors, thereby assisting a wealth management firm in making informed trading decisions. The primary objective was to establish a reliable system for evaluating stock performance based on multiple financial indicators.

"Lucinda is an outstanding talent, and I cannot recommend her enough. She was able to help us scale a project that needed her level of talent. She is smart, asks great questions and notices things that we had missed. She found a computing error in our model and politely pointed out the flaw, fixed it and moved on. Her programing skills produced an end-product that is elegant, easy for us to use and scalable. She is extremely well organized with written work plans, regular updates and turnaround times were always fast. We spent time up front giving her context for the project and that made our communications flow, and her insights were always welcomed. Highest recommendation without reservation."

My responsibilities included data acquisition, processing and analysis, script automation, and tool development. To begin with, I connected to multiple financial APIs to retrieve up-to-date stock data. Ensuring the continuous availability of the latest information was crucial, so I automated the data collection process.

Utilizing Python and Pandas, I processed and analyzed the stock data with a focus on key stock factors such as Bollinger Bands (BBW), Force Index (FI), moving averages and other relevant indicators. I implemented scripts to calculate and visualize these factors, facilitating easy interpretation for the wealth manager.

A significant part of the project involved developing automated scripts to perform regular data updates and analyses without requiring manual intervention. This automation ensured that the client received timely insights through scheduled reporting, thus enhancing decision-making efficiency.

Additionally, I created a user-friendly interface for the wealth manager to interact with the analysis results. I provided detailed documentation and support to ensure effective use of the tool, enabling the wealth manager to fully leverage the insights generated.

The tool significantly enhanced the client's ability to analyse stock performance, leading to more informed trading decisions. The automation of data retrieval and analysis not only saved time but also improved the accuracy and reliability of the insights provided.

By leveraging Python and Pandas, I streamlined complex financial data analysis processes and delivered a practical solution tailored to the needs of wealth management. This project demonstrated my ability to integrate data science and financial analysis to create impactful tools for investment professionals.