KNN Virtual Currency Price Prediction Model Based on Price Trend Characteristics

Abstract

Bitcoin presents a new monetary concept and has received a lot of interest from various parties, which in turn has created a new form of investment in virtual currencies. The prices of virtual currencies tend to change quickly and fluctuate greatly, causing many investors to rush into the market in a frenzy, ignoring the riskiness behind it. The price prediction of virtual currencies can not only provide reference for investors’ investment, but also reveal its financial laws to a certain extent, improve the risk warning mechanism, and enhance its stability and safety. In this paper, we propose an improved KNN algorithm for virtual currency price prediction. The new model restructures the data and converts the original single-point price data into the trend characteristics of the price. The experimental results show that the improved KNN model has better prediction effect compared with the traditional KNN model as well as the logistic regression model.