Data Scientists become Traders
We have something interesting for you.
The crypto market is so young that almost no one has enough data to analyse it deeply. It remains a field of pure experiment for so many. What we are trying to achieve is to bring data-driven approaches to analysing and forecasting crypto investments. And who are the closest people to the data? Data scientists. With their knowledge of data, are they able to apply it to trading activities and understand how the market works?
We challenged our in-house data scientists to become traders for six weeks. The challenge began on 17 January, when nine data scientists were each given starting capital of 0.1347 ETH (about 0.01199 BTC). They were asked to make trades using at least one of Cindicator’s indicators until midnight on 28 February.
The results are:
– 79 trades in six weeks. Average number of trades made was 8. The leader made 19 trades;
– 40 unique trading pairs were used, making it a diverse experiment;
– One participant’s activities were profitable — he ended up with a 4% gain in BTC after six weeks;
– The worst result was -34%. The average result was -20%.
The winner of this challenge was Sergey Arefiev: “I had a very vague understanding of what trading was, so it was very interesting for me to give it a try. The market was crashing down during the challenge, and that was a problem since the only goal was not to lose money. My strategy was to buy crypto and wait until it rose by 4–5%. I think if the market was on the rise, the challenge would have been more interesting for all of us.”
Ekaterina Belonogaya said that she now places a stronger emphasis on market behaviour when exploring signals: “For a person with no experience in trading Cindicator’s signals are a good start, as they save a lot of time in exploring the market (which is especially important for people with no specific education in that field).”
Alexander Osipenko tells us: “Because of the limited time frame of the challenge and a lack of any previous experience of trading, Сindicator’s signals were a very useful guiding tool for me, telling me which token I should pay attention to. After six weeks I can see that trading is very time consuming. You are not going to be successful if trading is a part time job. Overall, I made only three successful trades with profit of around 15%. For four more trades I am still waiting for the price to go up because I believe in their teams and technologies. I will definitely continue to trade on the crypto market.”
Eugene Koltsov’s impressions are: “I’ve learned a good lesson, namely that traders must be very attentive and patient. No careless decisions. Also, my strategy is long-term, so no matter if it doesn’t fit within the challenge period — my old orders will soon bring me my profit.”
Alexander Frolov thought that the challenge was really useful for him: “The human brain doesn’t work well with a lot of data but it’s capable of long-term learning that is not achievable for machine-learning algorithms. Therefore, we are good at finding patterns or conducting analysis on a small amount of data. On the contrary, AI can work well with a large amount of data, finding hidden patterns. Symbiosis of the two approaches can provide interesting results.”
Nodari Kolmakhidze, Cindicator’s Chief Investment Officer, comments on the results:
“It’s absolutely normal that the majority of results are negative. Here is why:
- It was the first trading experience for most of them (some traders can’t achieve stable profits for decades);
- The entire market has been consistently bearish since January, so it’s pretty hard to make money in these circumstances;
- They did it as a hobby, not a full-time job. It’s quite hard to be profitable without spending all the time you have available.”
Most of the participants said that the challenge was useful for them in understanding markets more deeply. Some of them started to learn more about trading, becoming really interested in the whole process. The challenge was also useful for Cindicator as a whole, and for CND token holders since the data scientists now have real trading experience.
We recently invited Cindicator Bot users (Trader and Expert level) to participate in another private trading challenge. The main goal of this challenge is to better understand how effectively traders are applying our indicators.
The challenge will run for several weeks, with rewards including both financial and non-financial incentives. We will share the results with you when it’s over. We will continue to experiment with challenges, creating more opportunities for our community to learn more about the market, and especially the crypto market where a lot of testing and fine-tuning is still required.