Bot creator spotlight: Laika
Bot creator spotlight: Laika
Where would the BOTS app be without our amazing bot creators? These superheroes are the minds and creators behind the bots in the BOTS app. But who are they, where are they from, what's their relationship with trading, and what's their philosophy?
Let’s find out, shall we?
Today, the spotlight is on the bot-creator team Laika: responsible for 16 (!) bots in the BOTS-app, and an additional 7 new bots going through their quarantine period.
The team behind Laika was already familiar with the BOTS app, and their enthusiasm made them decide to create a great number of bots for the app. “The BOTS app helped us to reach a wide range of investors that were willing to invest in our algorithms, in order to further professionalize our business.”
Even though there had always been an interest in financial markets, team Laika didn’t decide to expand until they created an algorithm to manage their own portfolios…
The first Laika algorithm was created
Steven Wisbrun, the man behind Laika, discovered his interest in programming and algorithms while studying his master degree in Quantitative Finance at Erasmus University. “We gained a lot of experience in programming and algorithms in general during our studies. The knowledge of algorithms and interest in financial markets resulted in writing theses about financial assets and some underlying stochastic relationships not visible on the surface, with exceptional academic supervision.”
“The crypto-market is relatively unestablished, leaving the opportunity to find certain anomalies and profit off of them.”
But it didn’t end there… “After developing these methods, we tried to exploit our findings by converting them to trading signals. This resulted (after a lot of backtesting, optimizing and setbacks) in our first actual trading algorithm, which we used to manage our own portfolio’s. The market is relatively unestablished, leaving the opportunity to find certain anomalies and profit off of them. Furthermore, due to the volatile nature of the underlying assets, it allows the algorithms to generate very large returns (if executed correctly). The results of these algorithms were quite successful, which is why we continued to not only develop different strategies but also searched for investors to grow the trading portfolio.”
Laika and the BOTS app
The BOTS app is a great platform for both users and bot creators. The community vibe is strong, and bot creators like Laika do all they can to connect with the users: “We try to keep close contact with our investors, to address any concerns they might have. We believe this not only increases the trust between bot creator and investor but improves upon the transparency that the algorithms might lack. We are grateful for the BOTS app for attracting such a large investor base, in a relatively short time!”
For the Laika-bots fans: no worries, team Laika will continue to provide the BOTS users with a variety of new bots: “We want to be part of this exciting journey and therefore we force ourselves to keep optimizing our provided algorithms. This makes the collaboration with BOTS very favourable! We plan to continue to improve our current algorithms, develop new strategies and grow our investor base!”
Advice to new bot creators
So what about Laika’s advice to new bot creators? “We believe it is very important to really understand why an algorithm makes a certain decision. It would be easy to simply throw a machine learning algorithm at some data, backtest it, and await what it will do trading live. Historical data is full of biases, so one must be very careful in interpreting these results. Incorrectly optimizing and backtesting on historical data can lead to substantially different results going forward.
“When not knowing exactly why an algorithm makes a decision, it can be very dangerous to use in live trading.”
“Furthermore, when not knowing exactly why a ‘black box’ algorithm makes a decision, it can be very dangerous to use it in live trading. Lastly, one should closely monitor the execution performance. As the trading portfolio grows, it gets harder to fill entire orders, so an algorithm should address these concerns and adapt accordingly.”