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In this project we had the challenge to turn something very complex such as the financial markets into a fun and engaging game.
STUDO is an investment simulator, necessary for those who are already investors or are just starting to get interested in the financial market. Using OpLab platform servers, STUDO creates a simulated market just 15 minutes behind B3 that allows the user to simulate stock and options trading. When the position turns profitable the user receives profit as "Sortes" and they in turn can be used to unlock different items and services in the store to help.
By removing risk in trading and allowing for the user to experience the financial markets directly we can help them learn how to proper behave in different situations while also rewarding them for their correct actions with our coins.
Margin and Limits
Since our game allowed the user to play with derivatives (options) we needed to calculate the user margin in a way that it didn't became overly complex but also was close to the actual stock market’s reality. In other words our challenge was: how much buying power should we give to the user based on how many derivatives they had sold and/or bought.
Our solution to this challenge was to create our own algorithm that, in general terms, evaluates every sold and bought position for the user and uses these positions to cancel each other in the correct proportion. This allowed our users to experience an even more realistic trade enviroment.
One of the main challenges of the development team was to create a reliable algorthim for ranking all users in an optmized way. We went trough a few different versions before ending up in the one we have today. The challenging parts were: performance (because we need to iterate through all our database of users to calculate their results), consistency (how do we keep things working in case some error happens) and profitability (how do we find the best way to calculate rentability for a porfolio between any given two dates).
After a lot of trial and error we learned that altough this ranking seemed simple at first, a deeper look showed us that were many hidden details in finding which was the best approach to calculate all the trades each user made during the period being evaluated.
From complex to fun
Studo was created to make something complex and difficult to understand at first glance, such as the financial market, into a fun and engaging experience. We wanted to help those who wanted to start investing but felt as it was too daunting and boring or were too afraid of losing money.
That's where gamification comes in, by using some key concepts like prizes, rankings and our own virtual currency we provided a layer of tools that are intended to keep the players engaged until they have a better grasp of the market’s inner workings and were ready to go out there and do it themselves for real this time.
The hardest part here was identifying the line between too “gamey” and too much of a formal investing platform. Because while we couldn't lose touch with reality we also had to spice things up a little bit. In order to help with that we added a few different illustrations in a very selective manner to add some visual playfullness to the app without turning it into a complete game. As well as some subtle ways of helping the players through powerups that can fix slight mistakes and provide a additional layer of safety.
The 'Greek's' Challenge
In order to properly evaluate option trading, users need a few parameters called greeks. They are used to evaluate how each option will respond to certain moves in the underlying asset. In order to bring this dynamic to the game we connected with Oplab's infraestructure.
Based on this partnership we use a polynomial-based strategy to estimate the theoric price and greeks for each option. This equation uses a set of metadata like option strike, expiration, underlying asset price and so on together with Oplab’s propietary technology.
The end result is a list of parameters that each user can use to improve their decision making during option trading.