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Performance analysis of bitcoin forecasting using deep learning techniques

Nrusingha Tripathy · Sarbeswara Hota · Debahuti Mishra

26 citations0/0 files storedIndonesian Journal of Electrical Engineering and Computer Science

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Stock Market Forecasting Methods Blockchain Technology Applications and Security Forecasting Techniques and Applications

Abstract

The most popular cryptocurrency used worldwide is bitcoin. Many everyday folks and investors are now investing in bitcoin. However, it becomes quite difficult to evaluate or foresee the price of bitcoin. The price of bitcoin is extremely difficult to forecast due to its swings. By this point, machine learning has developed a number of models to examine the price behaviour of bitcoin using time series data. The digital money, a different type of payment developed utilising encryption methods, is difficult to forecast. By utilising encryption technology, cryptocurrencies may act as both a medium of exchange and a virtual accounting system. To estimate the values of a future time sequence, this work introduces a deep learning-based technique for time series forecasting that treats the current data as time series and extracts the key traits of the past. To overcome the shortcomings of conventional production forecasting, three algorithms-auto-regressive integrated moving averages (ARIMA), long-short-term memory (LSTM) network, and FB-prophet-were investigated and contrasted. We compared the models using historical bitcoin data of past eight years, from 2012 to 2020. The “FB-prophet” model, which is significant, catches variation that might draw attention and avert possible problems.

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References

1977Time Series Analysis: Forecasting and Control 2019Chapter 12: What does the Anthropocene hold for citizenship?2017Deep learning with long short-term memory networks for financial market predictions 2014Stock Price Prediction Using the ARIMA Model 2018A novel cryptocurrency price trend forecasting model based on LightGBM 2020Stochastic Neural Networks for Cryptocurrency Price Prediction 2021Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models 2019Sentiment-Based Prediction of Alternative Cryptocurrency Price Fluctuations Using Gradient Boosting Tree Model

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