Last Updated on February 11, 2021 by admin
This post will introduce you to Crypto-ML’s Matic crypto trading strategy, providing insight into how it works and what you can expect.
Crypto-ML Trade Strategies
With Release 7 of Crypto-ML’s machine learning crypto trading system, we introduced the ability to intelligently switch between multiple trading strategies. This allows our platform to rapidly adapt to different market conditions.
As of this writing, our platform will switch between three strategies:
- ML: our original, core trading system that trades directly off of our neural network price predictions. This is ideal for traditional, stable markets.
- Manipulation: an offshoot of ML, this strategy identifies market manipulation by measuring variance in our neural network predictions from actual movement. This is ideal for volatile markets.
- Matic: the topic of this post. It is a separate system derived from deep learning.
Learn more about Crypto-ML Trading Strategies.
Matic can best be described as an adaptive rules-based engine for trading. It takes inputs from technical analysis indicators, evaluates them, then issues a BUY or SELL signal.
What makes Matic unique is how the rules are determined.
Whereas our other two strategies are dependent on Neural Network price change predictions, Matic applies machine learning in an entirely different manner.
Deep Learning to Develop Crypto Trading Rules
Crypto-ML feeds large quantities of technical data into deep learning algorithms that find patterns in the data. These data sets are typically around 500 GB in size. Each given set consists of technical indicators deconstructed down to their individual components.
This is a huge amount of information that is ideal for a machine to analyze.
As humans, we can now ask questions such as:
- What does the market look like before upswings?
- What does the market look like before price drops?
Based on the findings, rules can be put in place to open and close trades as those patterns emerge in the market.
Once the core rules are determined, Crypto-ML applies machine learning optimization algorithms to tune parameters and maximize the potential outcome.
This approach to trading is exciting for three reasons:
- Unlike with our neural networks, we (humans) can understand the exact criteria used to make trade decisions. There is no layer of abstraction.
- Nearly all findings from deep learning are unorthodox. Machines don’t rely on textbooks and videos to learn technical analysis. Instead, they learn from the data itself. As a result, they use indicators differently than you typically expect.
- The processing is extremely fast. This reduces trade slippage when compared to methods that rely on a prediction pipeline.
Since Matic is computerized, it will consider hundreds of variables before determining whether or not to open a trade. Let’s look at one such rule derived from Relative Strength Index (RSI).
Human traders may learn to consider opening a trade when RSI is below 30. This indicates an oversold condition.
Matic, on the other hand, gets to learn RSI from the ground-up. Our system will completely deconstruct RSI. During the learning phase, we may find that bullish conditions usually happen when the RS line is between 45 and 50 while also dropping by 5% per bar. It may also determine this matters on 4-hour bars, but not on 1-minute bars.
Taking this a step further, it might find this is only true when certain unorthodox conditions exist with other deconstructed indicators.
As you can see, this level of detail and intricacy would otherwise overwhelm human analysts.
Matic seeks to capture quick moves in the market, therefore trades will typically be opened and closed within hours. However, some trades may be open for several days.
As of this writing, Matic has issued 14 trades to Crypto-ML customers at a 100% win rate. The average trade so far is +2.35%.
As with our other systems, the machines have determined it is best to capture profit quickly. There are two reasons for this:
- The longer a trade is open, the greater the chance of something going wrong.
- By rolling trade gains into the next trade, you can compound your results.
Another expectation to set is you may experience drawdowns in trades. If conditions are still bullish (despite the drawdown), Matic will consider the drop as a temporary move. By doing so, it can avoid being whipsawed out.
As a trader, you will see three key benefits from Matic:
1. Matic seeks to issue very high probability trades. Its goal is to rapidly compound your trading funds.
2. As noted, since Matic doesn’t rely on neural networks for buy and sell decisions, it can execute trades extremely quickly, reducing trade slippage.
3. Matic is can effectively navigate bull, bear, and sideways markets.
The key downside to Matic is that if rule conditions are not met, it will not issue a trade.
This means there may be extended periods of time without a trade.
With our intelligent strategy switching, Crypto-ML can mitigate this.
Matic adds tremendous strength to Crypto-ML’s already robust suite of machine learning-enabled trading systems.
Crypto-ML provides machine learning for crypto traders and investors. Gain crystal-clear signals and deep market insights. Add predictive capabilities to your toolbox. Learn more and join for free.