This service is exclusively for HYPE Community members and it is a subscription-based service. Please note that this service will stay in a BETA phase until the end of 2019. If you wish to subscribe as a BETA tester for free, please contact BTlead or Leon on Telegram. Telegram Messenger is a requirement to use this service as all signals are sent via a channel on the app.
Artificial Intelligence with machine-learning capabilities at work.
Artificial Intelligence revolution is upon us. Self-driving cars are fact, chess programs that beat an average professional have been known for a long time. Stock market trading, being unregulated in terms of traders’ methods, will reward those on the cutting edge of research. Best hedge funds may be still be run by humans but if their method is really better, AI will figure it out as well. Besides, most traders do not compete with the best. Just like in the tale where two men are trying to escape from the bear, they need to out run one another, not the bear. Because stock market has so much randomness, it will take traders longer to notice that their opponent is using a superior method.
Another important argument in favour of AI is that most traders specialize in one trading style, be it trend following, mean reverting, fundamental analysis and so on. That is because learning one style is difficult enough, mastering all of them is impossible. When traders start using AI, they suddenly can reach to methods that were not available for them before. By utilizing AI, traders can trade free from their believes, misguided opinions and personal limitations. (Wojtow, Genotick)
SIGNAL 1 (BTC/USD, ETH/USD, ETH/BTC) [25 Machine-Learning AGENT SIGNALS]
1 daily signal provided
Combination of 25 AI/ML signals, evaluating and analysing the BTC/USD, ETH/USD, ETH/BTC markets every 4 hours. In a typical day, it produces 150 signals and all those signals are combined to find a pattern – BUY, SELL or HOLD. Subscribed users will receive 1 daily signal which is a combination/average of the 150 signals of the following day.
Initially, we were only interested in launching SIGNAL 1 (25 AI agents with machine learning capabilities). However, upon testing it for months, we came to a conclusion that it was simply not as effective and intelligent enough particularly during a volatile bull/bear run. Wojtow, the founder of Genotick highlights this issue with Machine-Learning AI bots used to predict stock market data.
One of the main issue with Machine Learning is over-learning. This is due to the fact that in traditional AI algorithms data is fed to a Neural Network multiple times. If the Neural Network can “see” the data more than once, it can learn to react to changes that are not market inefficiencies but just noise. This can be reduced by selecting how much learning is allowed before checking network’s prediction on out-of-sample data. However, this isn’t perfect as amount of learning on in-sample-data is also data dependent and in the end is just another parameter that must be adjusted.
This does not mean the AI agents are ineffective and useless. It definitely helps traders find a pattern and draws day-to-day market movements more clearly as opposed to not having it in the first place. Therefore, we will keep SIGNAL 1 and provide SIGNAL 2 on top of it to further improve accuracy of the predictions.
SIGNAL 2 (BTC/USD, ETH/USD) [GENOTICK + TWEET SENTIMENTS]
More than 1 daily signals provided
SIGNAL 2 is a combination of the Genotick open-source AI bot + Stacked Learner Tweet Sentiment module. Genotick is a well known open-source AI bot which has performed well for traditional stock markets and commodity markets. However, it has performed relatively weakly and rather conservatively when it comes to cryptocurrencies, due to its immense volatility. To improve this, we have added the Tweets-for-Price-Prediction neural network module which is a script for scraping twitter data for predicting stock prices.
We overcame the problem of machine-learning AIs specially designing the algorithm to be Walk-Forward only. That is, similarly to actual trading in real life, our software trades and learns as it goes along. There is no separate learning and trading modes. Also, to better simulate real life, we forced the algorithm to trade on the market’s next price, instead of its last. This is to simulate a real life delay between analysis and placing a trade.
At the beginning Genotick creates initial systems by randomly choosing instructions, changing their arguments and grouping them into lists. Each system has one list of instructions than can be up to 1024 long. Interestingly, once a system is created it never changes. This allows us to trust the system – its output will always be the same on the same data. All systems are saved in a population which is adjusted (or “learns”) over time with genetic algorithm, one day at a time.
Our algorithm assumes that there are multiple systems, each a little bit different. We then take all their predictions to calculate one cumulative prediction that would be used by a user to put a trade on. Genotick calculates profit yield by these predictions and reports it to the user at the end. The final result is what a user would get in real life when executing every day and opening a trade at next market open. (Wojtow, Genotick)
Genotick Neural Network + Twitter Module
This ensemble learning model combines the predictions of both the market data learner and twitter data learner. Those two learners are used as the base models to train the meta model, a simple multilayer perceptron.
Above Testings Showed a Result of 75% accuracy
From the chart, this network seems to have less of a bias towards a single prediction and might be more suited for practical application. However, the accuracy is not always guaranteed and it is a well-known fact that accuracy of these bots drastically decrease with real-time data, particularly when the markets are highly volatile.
The AI-powered Trading Signals should therefore, only be used to serve as a supportive indication added on to your proven trading strategies. You should not solely rely on the signals provided by these bots to make financial decisions and your own due diligence is essential when it comes to trading cryptocurrencies.
MORE READS ON GENOTICK AI
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