OPTimal

It is easy to make good decisions when there are no bad options. Through OPTimal, you can learn financial algorithms without a headache.

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Inspiration

Financial tools are often bogged down by difficult terminologies causing fear in regular traders. We allow users to learn and ultimately trade with conviction and clarity. The idea began with a brief chat with Al (Head of Tech @ Marshall Wace). As he reiterated, there are no perfect algorithms or fortune tellers that can perfectly time the market. However, one can perform optimally by knowing, and having the financial tools in their arsenal. Hence, our mission is to provide our community and users more financial tools allowing them to perform optimally in diverse market conditions.

What it does

OPTimal is a platform that provides our users the information necessary to maximize their financial options. By providing information on seemingly complex trading techniques such as option trading, our program allows users to effectively respond to the unpredictable market by providing them with insight and tools necessary to outperform the market.

How we built it

We the backbone (version 1) of our learning platform on Python with the use of Streamlit framework, as well as several Python libraries. The vision for the next version is implemented via Figma design tool.

Challenges we ran into

The most difficult aspect of the project was simplification. That is, we wanted to simplify the financial terminologies, visuals, and even our virtual platform because our purpose is to be user-friendly. However, financial terms are not easily explainable. Hence, we incorporated visuals and easily maneuverable tool bars so that our users can easily observe the price changes caused by changes in different variables and financial phenomena.

Accomplishments that we're proud of

  • Learning how to use software tools, such as Streamlit.
  • Getting acquainted with financial models.

What we learned

The most important lesson we learned from this project is collaboration. We had difficulty coming up with an optimal team situation. However, by quickly adapting to the adversaries and collaborating on the tasks that we are unaware of as a group, we were actually able to finish more of the project than expected by collaborating on difficult tasks rather than alienating a team mate to a certain task.

What's next for OPTimal

  1. In addition to our current model, an AI that can keep track of volatility levels of the option, specifically, one that can buy (if volatility is low) and sell(if volatility is high) is the chosen stock would optimize revenue.
  2. Partnerships with Udemy/ other educational institutions.
  3. Add real-world examples.
  4. 3D modeling/interface improvements.
  5. Add more information about trading.

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