How Is Deep Learning Used in Cryptocurrency Trading?

The cryptocurrency trading and investment trends have been touching the sky for quite some time now. Its growth and market capitalization have been soaring high for many months. It welcomes the interest of people to make investments in digital currency.

What’s enjoying major popularity with cryptocurrency is machine learning. But, to one’s surprise, its use is attached to predicting the market conditions and stock prices.

However, it offers a restrictive use if anyone wants to use this trend for predicting the violations of cryptocurrencies. Some reasons behind it are stated as follows:

• Technological progressions
• Security, theft, and data misuse issues
• Political and other types of governmental factors

A higher degree of volatility enhances the chances of adding the profits. However, the only concern is intelligent investments backed by strong and well-researched studies.

But, the question arises that if not machine learning, what’s the thing that predicts the cryptocurrency prices and influences its trading.

Well, the answer to it is deep learning.

The question is related to this new term and what exactly it has with cryptocurrency dealings?

Scroll on to know!

Deep Learning In Cryptocurrency – A Brief


It is a type of machine learning training model. As the name suggests, it digs deep into the human brain and tries to understand the brain’s ability to set decisions. And, when it comes to cryptocurrency trading, investments are fruitful only if monitored decisions support them.

The concept of deep learning targets the algorithms in a broader sense that solves problems. It is an advanced level of machine learning and employs neural networks to give rise to problem-solving skills. As far as a neural network is concerned, it is related to solutions for different tasks with different degrees of task complexity.

Such a neural network owes its training to a large amount of data. The functioning is similar to how a blockchain releases the data every time a transaction is initiated from the buyer’s account.

Using The Deep Learning Concepts For Cryptocurrency Trading


The concept of deep learning has an important role to play while entering into the cryptocurrency trading world through an

The use of deep learning while trading in cryptocurrencies can be understood in 4 ways. They are as follows:

Procuring Real-Time Data


Procuring real-time trends and data is important while studying cryptocurrency dealings from scratch. The forecast is incomplete without fulfilling the data requirements like the following:

• Price and volume of the chosen dataset of a particular period. In usual cases, it is one year.
• Open, high, increased, low, and decreased values that are a part of the dataset related to one year

The data procured to move forward with the cryptocurrency dealings has 5 important features. These features have been discussed as follows:

• Closing or last price stands for the price or amount of various cryptocurrencies at which the market closes by the end of a day.
• Opening price refers to the price at which different types of cryptocurrencies open for dealings within a day.
• The higher price is the maximum price for cryptocurrency dealings within a single day.
• Lower price stands for the least price at which cryptocurrencies are dealt with within 24 hours.
• Volume refers to the currency quantum set to be traded within one day.

Data Training And Tests


Deep learning algorithms note the details of the dealers and choose the valid exchange rate stored in the data frames consisting of other real-time data. It is because the algorithms consider these as string objects to cater to the complexity of the dealings.

Next comes the process of normalization into the picture. Normalization is an important step while employing deep learning to extract the cryptocurrency price for everyday dealings. The main aim of employing this machine learning concept is to bring the possible value change in different numeric columns of the table.

The value changes help keep all the values consistent and related to a common scale. It eliminates the risk of any distorting difference that may arise due to the values of different ranges and further adds convenience while predicting the cryptocurrency pricing.

Price Predictions Through Neural Network


The LSTM neural network of deep learning functions in a manner that employs the special gates for extracting relevant information related to the digital currency pricing, followed by its decisions of whether to trade in them or not. The information is extracted through both the previous and current layers of use. After passing through different gates, the activation functions get to a place that is further moved forward with the help of the LSTM cells.

Deep learning has the biggest advantage in patterns of these LSTM cells that help the people interested in crypto dealings remember the patterns. It helps them reduce the loss risk and places them in a better position to enjoy profits through dealing in digital currencies. Also, LSTM remembers important information on behalf of the user, so the chances of entering wrong information are less. It lets go of the information that is of no use.

Result Visualization


Evaluation is important before taking the final step. MAE, which stands for mean absolute error, is one of the best ways of visualizing the predicted cryptocurrency values as it goes well with the understanding of both the experienced and new digital market investors. MAE is a readily explained model and can be preferred by different crypto dealers. It does not consider the directions and is good for measuring the highlighted degree of error while predicting the everyday price or dealing amounted related to cryptocurrencies.

Another method that can be adopted is RMSE. However, it is not solely responsible for describing the average errors. It is a complex method, and the non-technical audience and new market investors might have difficulty understanding the RMSE process.


In all, deep learning is home to one of the most reliable neural networks that help analyze the trading followed by the price prediction of digital currencies. Deep learning is one of the best ways to reduce the risks of these transactions and helps the user get their hands on real data for a better experience and profitability of dealing in such currencies.

Marina Livaja
Marina Livaja

My name is Marina Livaja. I am a lawyer by profession, currently working as an editor for the website In my free time, I enjoy sports, and on weekends, I indulge in long walks in the national park located near my home.