Tendency monitoring and nearest-time estimation of rapid changing data: Cryptocurrency example

Abstract

It is a very tiring process for people to watch the multiple parallel instant price changes in stock exchanges that are rapidly changing like the crypto money market. As a solution to this, a computer software that can make quick and objective decisions by constant observation can take the place of a person. In this study, an original decision algorithm that evaluates the instantaneous values of price change indicators and obtains relatively high earnings in a short period of time is examined. The Python programming language and Mathlib library have been used to construct this algorithm and to visualize the data, Moving Average Convergence Divergence (MACD) and Bollinger Bands have been used as a basic indicator. The result is an algorithm that requires less processing power and can operate continuously even on ARM-based mini-computers.