Forecasting Cryptocurrency Trends using Web Application

Forecasting Cryptocurrency Trends using Web Application

Bitcoin; Ethereum; Litecoin; Cryptocurrency; Machine Learning; Price Prediction.

Global currency values have been declining, stock markets have been having a bad run, and investors have been losing capital over the past two years due to growing geopolitical and economic concerns. As a result, interest in virtual currencies has increased. One of the most well-known digital currencies, cryptocurrency, has gained attention from investors hoping to get a piece of it and from businesses accepting it as payment because of its consistent performance over the past several years. The study proposes a system aimed at accurately predicting the prices of Bitcoin, Ethereum, and Litecoin by considering various parameters influencing their values. For the first phase of investigation, aim to understand and identify daily trends in the cryptocurrency market while gaining insight into optimal features surrounding cryptocurrency price. The data set consists of various features relating to the Bitcoin, Ethereum and Litecoin price and payment network over the course of five years, recorded daily. For the second phase of investigation, using the available information to predict the sign of the daily price change with highest possible accuracy. The overall goal of the project is to construct a machine learning model that can predict price trends with results superior to that of random selection.

[1] B. I. Hameed, “Blockchain and Cryptocurrencies Technology: a survey”, JOIV : International Journal on Informatics Visualization, vol. 3, no. 4, Nov. 2019.
[2] Bo-Jhang Ho et al ,”Bitcoin Price Prediction Using Machine Learning: An Empirical Study”, 2020.
[3] E. Pintelas, I. Livieris, S. Stavroyiannis, T. Kotsilieris, and P. Pintelas, “Investigating the Problem of Cryptocurrency Price Prediction: A Deep Learning Approach”, 2020.
[4] Kim, Y.B., Lee, J., Park, N., Choo, J., et al.: “When Bitcoin encounters information in an online forum: Using text mining to analyses user opinions and predict value fluctuation”, PLOS One 12, e0177630, May 2017.
[5] Sebastian Kuhlmey et al,”Bitcoin Price Prediction Using Machine Learning: An Approach to Sample Size and Feature Set Optimization”, 2019.
[6] T. Phaladisailoed and T. Numnonda, “Machine learning models comparison for bitcoin price prediction” 10th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 506–511, 2018.
[7] Y. K. Pardeshi and P. P. Kale, “Technical analysis indicators in stock market using machine learning: A comparative analysis”, 12th
[8] International conference on computing communication and Networking Technologies (ICCCNT)20201
[9] Y. Liu, Z. Li, R. Nekhili, and J. Sultan, “Forecasting cryptocurrency returns with machine learning,” Research in International Business and Finance, vol. 64, p. 101905, Jan. 2023.
[10] Yufei Li et al , “A Comparative Study of Bitcoin Price Prediction Using Machine Learning”, (2019).
[11] [Z. Ai and Z. Yao, “The Investment Value and the Current Regulation of Cryptocurrencies Market Under the Confusion,” Jan. 2021.