Research on Quantitative Trading Model——Taking Bitcoin and gold as examples

Abstract

With the rapid development of data science, quantitative trading models have become prevalent in financial markets. We calculate a series of indices based on the price data of gold and bitcoin from 2016 to 2021. On the basis of ARIMA model in time series algorithm, we build a prediction model that forecasts that very day's gold and bitcoin price relying solely on the past stream of daily prices to date. After completing the construction of the prediction model, we establish the quantitative trading model. We use AHP method to get buying scores of gold and bitcoin, which are the criteria for buying and selling. We then draw up some numbers and compare them with buying scores to decide whether to buy or sell and the number of shares bought and sold each day. After this, we use dynamic programming to find the theoretical maximum profit. Comparing this with the result of our quantitative trading model, we conclude that our model has significant superiority. Generally, the trading model established in this paper has good sensitivity to adapt to market changes and has strong risk resistance.