Bitcoin’s value has increased exponentially in the last 2-3 years. With a consistent rise in price, the coin has drawn more investors than ever and has achieved exponential growth in its market capitalization. The static supply, anonymity, and resistance to cyber-frauds make Bitcoin a valuable investment.
On the flip side, market volatility makes Bitcoin a high-risk asset. Wouldn’t it be better if we could know the swings in prices beforehand? There is one field of study that can help: Machine Learning. This article will explore how machine learning can be leveraged to track future prices.
Bitcoin and Machine Learning
Launched in 2009, Bitcoin is now the most popular variant of cryptocurrency. The coin enables a decentralized, trustless peer-to-peer payment network. Bitcoin transactions are secured by cryptographic keys and are stored in blocks in an open distributed ledger, known as the blockchain, upon verification from network nodes or the network of miners.
How individuals use Bitcoin and traditional currencies to transact is similar—the difference is the absence of a central authority in a Bitcoin transaction. Apart from its volatile nature, Bitcoin does not correlate with other assets, so investors use it for hedging against inflation.
Machine learning is a powerful data mining technique that uses computer algorithms to predict an outcome with the utmost accuracy. It uses historical data to analyze patterns and then applies them to preset data rules to generate a possible outcome. The large amount of data analyzed could be anything from texts to images or any form of media and has two main components: observations (instances) and variables (attributes).
Many businesses and researchers apply machine learning to understand consumer behavior or analyze trends.
How Can We Predict the Price of Bitcoin Using Machine Learning?
Machine learning utilizes time-series prediction models, including autoregressive integrated moving average (ARIMA), support vector regression, and deep learning techniques to predict prices.
The downside of the ARIMA is that it relies on linear assumptions more than variables, and hence is ineffective in predicting prices accurately. Support vector regression uses regression analysis to analyze smaller datasets, but it is not useful for analyzing complex, large, and noisy datasets. That leaves us with the non-linear deep learning method that can extract meaningful data from massive datasets and make accurate forecasts.
By implementing deep learning techniques—long short-term memory (LSTM) and recurrent neural network (RNN)—predicting prices can be possible. Both LSTM and RNN are designed to handle long-term dependencies and are equally plausible in classifying, processing, and making time series model predictions. RNN often fails to learn on training data due to vanishing gradient problems.
Predicting Prices
To predict the Bitcoin price, you need to retrieve the historical Bitcoin price data from a reliable source. Next, build LSTM and RNN models in Python using the API wrapper Keras. You can also use the Adam optimizer for optimization of loss function or mean absolute error.
Now apply RNN and LSTM models on a GPU instead of a CPU for better predictive analysis. The price prediction calculation is classifying the Bitcoin price by daily price changes and future hourly price changes.
- Remove all null/zero.
- Check data stationarity.
- Perform data seasonality.
- Match the observations.
- Divide the dataset as train data and test data.
- Analyze the dataset on a temporal scale.
- Design multiple LSTM layers.
- Train data with Adam optimizer for optimization of the loss function.
- Stop training data.
- Make the price forecast for Bitcoin.
- Inverse the temporal scale for real-time predictions.
Machine learning is a handy prediction tool, and one can forecast trends in Bitcoin prices using its different models. Because of its ability to analyze patterns in the data better than ARIMA, LSTM is an ideal time-series model for making predictions. With that said, machine learning is found to be approximately 70% accurate in Bitcoin price prediction. Therefore, your decision about Bitcoin investment should not be based solely on the outcomes generated by the machine learning models. However, Day by day, automation and technology take place everywhere as we’ve seen about the future price prediction. In the same way, You can also automate your Bitcoin trading with the help of Bitcoin robot platforms. There are many Bitcoin robots available in the market. But you need to choose an authentic platform like the Bitcoin lifestyle. You can check authentic Bitcoin Lifestyle Review to get more details on this trusted Bitcoin robot.
