We were inspired by the democratization of stocks and cryptocurrencies in the wake of the popularization of platforms like Robinhood and CoinBase to bring Forex into the hands of the people. Additionally, we want to create a world where the average person can extract the same amount of actionable insights out of earnings calls as the industry members who spend all their time spewing murky financial jargon.
MichMoney is a web application that has two main features: an earnings call transcript sentiment analyzer, and an intuitive visualizer of global Forex prices. It supports modern, cryptographically-secure authentication protocols and practices to ensure users and their data are safe and secure.
We built MichMoney using a modern tech stack including Python, Flask, React, and frontend languages and frameworks such as TailwindCSS and HTML. On the frontend, we employed React to create an interactive user interface, providing a responsive and dynamic experience. Additionally, we used several React components for visualizing global Forex prices as well as our earnings call sentiment heat map, offering an intuitive and user-friendly display of financial data. For the backend, we relied on a Flask web server to handle server-side logic, along with popular Python libraries like Plotly and Pandas. In terms of authentication and security, MichMoney boasts its own secure authentication process, allowing for seamless user logins, logouts, and signups. Natural Language Processing (NLP) techniques were utilized for the earnings call transcript sentiment analyzer. We leveraged NLP libraries such as NLTK (Natural Language Toolkit) to analyze and derive sentiment from the transcripts.
Throughout the development of MichMoney, we faced various challenges that pushed us to expand our technical skills and problem-solving capabilities. One significant challenge was the integration of financial data into the React components we used. We had to aggregate data from several different sources via several different methods, including web scraping and various APIs. Another hurdle we encountered was the lack of uniformity across devices. The virtual environment and version requirements of all the different technologies was a problem throughout the hackathon.
We are incredibly proud of our ability to effectively create a dual-feature hackathon project within the time limit in such a manner that leaves us impressed at our own work, and equally as shocked at our lack of sleep. We are also very proud of how clean and sleek our frontend is. We are very pleased with our newfound sense of confidence in our skills.
Our team acquired valuable insights and knowledge throughout the development of MichMoney. While we aren't new in the realm markets and financial analysis, delving so deeply into Forex provided us a deeper appreciation for the intricacies of it, as well as how it differs from other financial instruments. We significantly increased our proficiency with React during this project. Additionally, the collaborative nature of the project taught us effective teamwork, communication, and project management skills.
As we move forward, MichMoney has ambitious plans for continuous growth and innovation. We plan to integrate the next iterations of this project into our prospective FinTech startup: WolvWealth. User feedback will be a priority, allowing us to collect valuable insights and further enhance the user experience based on specific needs. We aim to expand the coverage of Forex data, exploring possibilities for integration with additional financial markets to provide users with a more comprehensive view of global financial landscapes. MichMoney is committed to democratizing financial insights, and our future endeavors are geared towards making these insights even more accessible and valuable to a broad audience.