The goal of this paper is to ascertain with what accuracy the direction of Bitcoin price in USD can be predicted. The price data is sourced from the Bitcoin Price Index. The task is achieved with varying degrees of success through the implementation of a Bayesian optimized recurrent neural network (RNN) and a Long Short Term Memory (LSTM) network.
In this project, we attempt to predict the Bitcoin price accurately taking into
consideration various parameters that affect the Bitcoin value. For the first
phase of our investigation, we aim to understand and identify daily trends in
the Bitcoin market while gaining insight into optimal features surrounding
Bitcoin price. Our data set consists of various features relating to the
Bitcoin price and payment network over the course of five years, recorded
daily. For the second phase of our investigation, using the available
information, we will predict the sign of the daily price change with highest
possible accuracy.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
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