Investing is tedious and risky prospect and finding ways to minimize that risk is essential. An active portfolio that properly manages risks based on new available data is something the investors should be considering. In that spirit, we bring to you our iOS game simplifies this process by calculating your preference for risk in the vitural space and creating an optimal stock portfolio for you based on stocks you preselect in the real world.
Our app is a game that calculates your risk-taking behaviour through an endless scroller game. As you progress within the game, you have to make decisions faster in order to get a high score. We use this information to generate a greading system for how our player/investor handles risk and swift judgement. Then we change gears and look at it from a finance perspective. GrowthDriver makes use of several portfolio optimization strategies by constructing a covariance matrix for the rate of return on stocks in the portfolio, while accounting for financial metrics such as the annualized rate of return, risk (variance), and Sharpe ratio.
We used Python and Flask for the backend logic and concepts, and Swift for the frontend game developement using tools from SpriteKit and UIKit
It was definetely a challenge getting our game logic to work from a decision making/story telling perspective in consideration of a 2D enviornment, generating original artwork, and working with new Python libraries.
Pivoting from our original idea, all while getting our app to work still in the spirit of game theory.
Game Design/Decisions, planning game protocols, Google Cloud Platform, Machine Learning Concepts.
Taking on the biggest firms in the world.
DevPost project link can be found here: https://devpost.com/software/growthdriver