The Mystery of Predicting Crypto Prices

Ever thought about how experts try to foresee the future prices of cryptocurrencies like Bitcoin and Ethereum? They use various methods to make these predictions, focusing on how these digital currencies behave compared to traditional money. Scientists and analysts look at past data, such as opening, low, and high prices, market capitalization, and trading volumes. They employ statistical techniques and machine learning algorithms to analyze this information. Two main models are often tested: a simple linear regression (SLR), which only considers closing prices, and a multiple linear regression (MLR), which includes other price and quantity data. The results are then compared using measures like Mean Absolute Percentage Error (MAPE) and relative Root Mean Square Error (relative RMSE). Interestingly, the ARIMA model showed the highest accuracy in predictions. Close behind were the Multivariable Linear Regression and Long Short-Term Memory (LSTM) models. These findings highlight how complex it is to predict cryptocurrency prices accurately.