Morgenstern & Price

Bitcoin is currently the leading global provider of cryptocurrency which has recently received a lot of attention from the public. In while facilitating services and product deals. The factors that affect the Bitcoin price and the patterns behind its fluctuations can be predicted by using various mach This prediction may give better insights about the bitcoin price to the people who are investing in the bitcoin. Accurate prediction of the future trend in the closed price of the day for a given Machine Learning models can be used to predict the closed price for a given cryptocurrency Keywords: prediction bitcoin price calibration In today's era, the planet is digitalizing. there's a Cryptocurrency is digital cash that's very fashionable. The cryptocurrency may be a money primarily managed or exchanged on computer systems. Cryptocurrencies use blockchai are highly secure and transparent. So, cryptocurrencies can become a replacement sort of taking advantage of the longer term. There are more than 900 cryptocurrencies currently available to take a position online and this number is consistently growing. of those cryptocurrencies, undoubtedly the foremost popular has been Bitcoin and it had been also the primary cryptocurrency within the market. People can make use of bitcoin rather than cash. A. Literature Survey This section overlooks similar existing solutions and examines the algorithms used and drawbacks. Enhancing Bitcoin Price Fluctuation Using Attentive LSTM and Embedding network [1] study used traditional machine learning including Random Forest, XGBoost, S machine learning methods cannot capture the time dependency of time series. Recently, deep learning methods such as Recurrent Neural Networks (RNN) can handle the issue of time depend out long-term dependencies foremost commonly used variants of RNN can solve the vanishing gradient problem. long-term dependencies due to ARIMA [2] analyses neural network autoregression (NNA Bitcoin price forecast results, considering two different training and test samples. I better than ARIMA, while ARIMA outperforms NNAR in the second training