Bitcoin-Usd Trading Using SVM to Detect the Current Day’s Trend in the Market

Abstract

Cryptocurrency trade is now a popular type of investment. Cryptocurrency market has been treated similar to foreign exchange and stock market. The Characteristics of Bitcoin have made Bitcoin keep rising In the last few years. Bitcoin exchange rate to American Dollar (USD) is $3990 USD on November 2018, with daily pice fluctuations could reach 4.55%2. It is important to able to predict value to ensure profitable investment. However, because of its volatility, there’s a need for a prediction tool for investors to help them consider investment decisions for cryptocurrency trade. Nowadays, computing based tools are commonly used in stock and foreign exchange market predictions. There has been much research about SVM prediction on stocks and foreign exchange as case studies but none on cryptocurrency. Therefore, this research studied method to predict the market value of one of the most used cryptocurrency, Bitcoin. The preditct methods will be used on this research is regime prediction to develop model to predict the close value of Bitcoin and use Support vector classifier algorithm to predict the current day’s trend at the opening of the market

Enhancement Support Vector Regression Using Black Widow Optimization for Predicting Foreign Exchange Rate

“…Predictive model for time series problems can be made using several methods such as Long Short Term Memory (LSTM), Support Vector Machine (SVM), Least Square Method, Support Vector Regression (SVR), and others [3]- [6]. One method that has a good performance in predicting foreign exchange rates is SVR.…”