Academic Journal of Computing & Information Science, 2022, 5(8); doi: 10.25236/AJCIS.2022.050813.
Nana Xiao, An Pan, Jingwen Lu, Yunru Zhang
School of Information, Xi'an University of Finance and Economics, Xi'an, Shaanxi, 710100, China
This study focuses on trading strategies for maximizing the value of assets, when traders buy, sell and hold bitcoin and gold daily. We have built a price forecasting model using Multiple Linear Regression (MLR) theory, and an executable trading model to provide daily trading orders. First, a 5-year data of daily prices were checked and few of missing values in gold price were filled with the value of the day before. Second, the MLR model was adopted using today's price, today's 5-day moving average (MA5) and today's 20-day moving average (MA20) to forecast prices in future days. The first 8% of the data was used as training set, and the goodness of fit is up to 99.64% on the remaining data. Third, we determined the overall trading strategy, the buying/selling point judgment strategy and the combination trading strategy for bitcoin and gold, based on the forecasting model. Finally, a trading model was built to solve daily trading orders (sell, buy or hold on) and the corresponding values for the three currencies (cash, bitcoin and gold), for a 5-year trading period. We have calculated that the value of assets increased from the initial $1,000 to $38.34 million, after 5 years of investment.
Multiple Linear Regression, Price Forecasting, Trading Strategies, Daily Trading Orders
Nana Xiao, An Pan, Jingwen Lu, Yunru Zhang. Research on the Trading Strategies for Maximizing the Value of Assets in Quantitative Trading. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 8: 90-94. https://doi.org/10.25236/AJCIS.2022.050813.
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