The math and computational skills required to fully understand Artificial Intelligence in the cryptocurrency market are incomprehensible for the mathematically challenged!
Fortunately, most of us just want to know how it can help us and how user-friendly it is.
So, we’ll look at why AI is such a game-changer and how it might improve investment and trading in cryptos.
There seem to be three areas of development:
Crypto market predictions
Crypto market sentiment analysis
Automated crypto trading strategies
Let’s start by looking at what we’ve been doing before the advent of AI.
Do Your Own Research (DYOR)
One of the features of the crypto market is its unpredictability and extreme volatility. This is exciting for the risk-tolerant but a no-go for the more cautious.
The typical, if somewhat naïve, advice to potential market participants has been to DYOR – do your own research. This has meant undertaking fundamental and technical analyses of cryptocurrencies.
A simple fundamental analysis includes the qualitative aspects of a coin or token, such as the underlying technology, the core team, and the market opportunity.
You might study the whitepaper, follow community inputs, check Github for progress on code development, look for listing on exchanges, and track price and market activity.
It’s laborious but theoretically possible.
Technical analysis is much more complicated.
Technical Analysis (TA)
Technical analysis relies on quantitative data and market sentiment.
Unfortunately, there is no single infallible indicator. Instead, you apply several indicators and then look for overall trends. All of them involve some sort of mathematical calculation applied to historical data.
Relative Strength Indicator (RSI)
Moving Average (MA)
Moving Average Convergence Divergence (MACD)
Bollinger Bands (BB)
The purpose is to find trends and patterns. You want to spot overbought or oversold positions, trend reversals and support and resistance levels.
Keeping track of all of this for one cryptocurrency is tricky. But doing it for all the cryptos out there is practically impossible.
This is where AI, Machine Learning (ML) and Natural Language Processing (NLP) come to the rescue.
AI for Crypto Market Predictions
There is just too much data and noise for manual systems to handle. More sophisticated methods are needed.
AI and Blockchain for Crypto Predictions
The power of AI is its ability to deal with large data sets and identify trends and patterns that are often too complex or subtle for people to observe.
And AI is even more powerful when paired with blockchain. Blockchain records are secure and can be used with confidence to analyze historical and real-time data.
Analytics applied to this data can rapidly identify and make sense of patterns, including behavior patterns, and use them to predict moves in the market.
Neural Networks for Predictive Analytics
Neural networks are a series of algorithms that work to recognize the relationships between large amounts of data.
They can integrate different and seemingly unrelated features and detect patterns in multiple dimensions.
For example, the data in crypto forecasting might include
Price and trading volume
On-chain variables such as
the number of active and inactive addresses, or
the total number of tokens available on the market to date, or
the length of time that tokens have been held in individual accounts
Blockchain-related data, such as
volume of transactions
speed of mining
size and direction of whale activity
A few of the many machine learning algorithms that can be applied include:
Classification and Regression Trees
K-Nearest Neighbors (KNN)
Learning Vector Quantization (LVQ)
Support Vector Machines (SVM)
The names alone are enough to make our eyes cross!
But they do tell us that AI and ML are not simple techniques. They give us a sense of their superiority over our human attempts at analysis of complex crypto markets.
Using AI To Identify Crypto Market Sentiment
Market sentiment is the overall attitude of investors towards the cryptocurrency market or individual currencies.
Sentiment can be described as
Bullish or bearish
Positive or negative
Greed or fear
In general, market sentiment is bullish when prices are rising and bearish when they are going down. In the same way, a positive sentiment predicts prices rising, and a negative one expects a fall. Reading market sentiment is an integral part of identifying overvalued or undervalued stocks.
Market sentiment has a remarkable impact on the price movements of crypto, although it often has nothing to do with the asset’s fundamental value. The recent surge in Dogecoin following positive comments from Elon Musk is a case in point.
NLP To Read Market Sentiment
Natural Language Processing (NLP) has revolutionized the analysis of market sentiment. Traders may still use technical indicators such as the Volatility Index (VIX) or Bullish Percent Index (BPI). But they now also have an analysis of news and social media.
AI systems gather data at scale, and NLP can identify the sentiment in news channels, blogs, articles, community forums, social posts, message boards, and comments.
It can quickly be analyzed in terms of
Polarity: positive, negative, or neutral
Aspect: the emotion attached to specific cryptocurrencies
Importantly, unusual behaviors that indicate manipulations in the market will also be detected.
An excellent example of how different sources of data are integrated is the Greed and Fear Indicator for bitcoin.
Artificial Intelligence for Cryptocurrency Trading Strategies
Automated trading strategies are beneficial for high-frequency trading.
Bots For High Frequency Trading
Bots are applications of AI. They have Inbuilt machine-learning algorithms that can, for example, recognize and analyze chart and candlestick patterns or trend reversal points that the trader may miss.
The result for traders is that computers can analyze the market and execute large numbers of orders within fractions of a second.
Some bots are pre-programmed to execute specific trading strategies. The more advanced ones allow investors to customize the settings to run any number of trading strategies.
Which Trading Strategies Are Best Served By Bots?
The utility of bots can easily be envisioned for traders applying a volatility-based strategy.
Bots For Volatility-Based Strategy (VBS)
Traders sometimes deliberately choose the most volatile cryptos or include technical volatility indicators in their overall strategy.
They may use moving averages representing minimal time periods. For example, this might be ten periods of 30 seconds to quickly spot when the price moves outside of support or resistance levels.
Or they will look for movement in the asset price within each candlestick rather than looking at trends over multiple candlesticks.
And they may set stop-loss or take-profit orders on movements of fractions of cents.
Trends need to be monitored on a minute-by-minute basis. A bot is more efficient at doing this than a person.
Some traders trade on low volatility.
They act as market makers, with both buy and sell orders set throughout the day. They buy lower and sell higher all day. Bots allow them to make thousands of these small trades per day.
Bots For Arbitrage
Traders using bots can avoid slippage and execute transactions across multiple exchanges to extract profit. Some bots are programmed to include the exchange fees as part of the trading decision.
A Cautionary Word About Bots
Bots Instantaneously and automatically execute according to the set parameters.
However, not all bots are equal.
Some bots have imbedded unsuccessful or outdated strategies
Some have low-quality software and bugs in the system
Some are frauds promising hyper profits.
Some of the characteristics of better bots include
Flexibility for traders to decide on their trading strategies
Backtesting and paper trading capability
Security of your trading
No bot can guarantee profits. However, the more the trader can monitor, adjust, and maintain the bot, the more likely trading success will be.
Artificial Intelligence In The Cryptocurrency Market Changes The Game
Artificial intelligence in the cryptocurrency market means that traders and investors have relevant predictions based on data from multiple sources.
Natural language processing (NLP) applied to news and social media gives a more accurate measurement of market sentiment.
And bots driven by AI algorithms revolutionize high-frequency trading.
Traders and investors should DYOR to find the best AI-driven tools to help analyze crypto opportunities.