AlgoTech
AlgoTech
AlgoTech is a fintech startup in the algorithmic trading space. Our long term goal is to democratize investing tools for people that lack financial literacy. Our co-founding team comes from a low income background, and it was not until recently that we became financially literate. While modern investing tools like Robinhood allow easy access to financial markets, they do not provide the tool necessary to make informed investing and trading decisions. We’re taking the next leap forward by building a no code platform for algorithmic trading, where the end user will be able to design their own portfolio consisting of various cutting edge machine learning models without having to write a single line of code.
While this is a lofty long term goal, in the short term, we are focusing on concept proving. Essentially, we cannot provide a product for our customer if the product has not been built yet. Therefore, in the short term, we are focusing on building both the backend framework for building machine learning models along with the strategies themselves.
The Weissman Foundry Fellowship was a fantastic opportunity for our team. While we encountered many hardships, such as 3 of our original 5 co-founders resigning, we still achieved a substantial amount of our goals. First, we built a backtesting framework to test any given strategy’s performance against any given trading strategy. Shown below is the code for a sample strategy that we created to run the backtest on.
In addition, we created Spark clusters on our data set so we can more efficiently injest the data when running machine learning training jobs. We also built out a random forest framework for developing and training our machine learning models.
Without the Fellowship, we wouldn’t have been able to do any of this. The grant money from the Fellowship is what allowed us to purchase the US equities OHLC dataset that we ran the backtests on and created the Spark clusters with. Coming up with the money upfront to purchase this dataset was one of the largest obstacles with our project, but with the grant from the Foundry, our project was catapulted forwarded. This rapid growth in our project allowed us to continue reaching milestones even after the Fall 2021 Fellowship ended. Specifically, we landed a partnership with financial data provider AlgoSeek by being accepted into their academic incubator program. They will be providing us access to two extremely sophisticated historical datasets, which will allow us to build much more complex and accurate machine learning models.
A big thank you to the Weissman Foundry for accepting us into the Fall 2021 cohort. After working on the project for 5 months in stealth, it was amazing to have a community that supported the visions and goals of AlgoTech. We received so much helpful feedback and support from the community, and we are very appreciative to have taken part in this great opportunity!
**This post was created in conjunction with the Foundry Fellowship program. AlgoTech received a grant that enabled this project to move forward. If you’d like to learn more about the program, or have an idea for a grant for yourself, please visit our info-page here.