Applied Research On Multi-factor Model In Digital Money Market

Since the day of its invention,bitcoin has gained a lot of attention from researchers,investors and national leaders because it is decentralized and generated by computer network nodes instead of centralized issuance by the government.At the same time,with the continuous development of bitcoin application scenarios,it has gradually created an emerging investment market and brought tens of billions of global capital transactions every day.As a typical representative of virtual digital currency,bitcoin is rapidly entering the vision of investors around the world.As of January 2019,the daily transaction volume of one of the largest digital currency trading platforms in the world has reached 3 billion yuan.Compared with the traditional market,the bitcoin market is characterized by a 24-hour trading system,"t+0" trading rules,natural advantages of the same variety of markets,and high volatility.It has attracted a large number of developers and investors who adopt quantitative trading methods,especially those who make quantitative trading for stocks,futures,stock indexes and other targets in traditional trading markets,and they hope to gain a share in emerging markets.Based on the characteristics of the digital currency trading market,this paper studies the current situation and trading risks of the bitcoin market.At the same time,I learned the quantitative trading model of the relevant traditional financial market,independently established the future earnings prediction model,and measured and summarized the quantitative investment strategy with a high rate of return.The research method adopted in this paper is to construct a multi-factor digital currency selection model by using actual data screening factors and to jointly reduce the selected factors to the digital currency return rate,and eliminate the factors that are not significant in the joint regression.The main result of this paper is that this paper tested more than forty different types of stock market common factors in the digital currency market,and selected 16 factors to construct trading strategies through single factor regression and multi-factor regression.As can be seen from the trading strategy income,the 16 factors are effective in the digital currency market,and the best performance is the BOP and ROC factors.The paper concludes that the multi-factor strategy adopted is effective.From the perspective of the trading strategy simulation income,we can learn from the multi-factor stock selection model in the stock market to establish a multi-factor model suitable for the digital money market,and establish a digital-based model.A multi-factor digital currency model of the money market.