Research and Case Study of Quantitative Investment Trading Strategy Model in Bitcoin and Gold

Da Rao

doi:10.47297/taposatWSP2633-456937.20220303

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Research and Case Study of Quantitative Investment Trading Strategy Model in Bitcoin and Gold

Volume 3, Issue 3

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Research and Case Study of Quantitative Investment Trading Strategy Model in Bitcoin and Gold
Research and Case Study of Quantitative Investment Trading Strategy Model in Bitcoin and Gold
Sichuan University,Sichuan,Chengdu,P.R.China
Vol. 3, Issue 3, Pages: 201-210(2022)
Published： 2022 ，
DOI：10.47297/taposatWSP2633-456937.20220303
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DA RAO. (2022). Research and Case Study of Quantitative Investment Trading Strategy Model in Bitcoin and Gold. Theory and Practice of Science and Technology, 3(3), 201-210..
DOI：

DA RAO. (2022). Research and Case Study of Quantitative Investment Trading Strategy Model in Bitcoin and Gold. Theory and Practice of Science and Technology, 3(3), 201-210.. DOI： 10.47297/taposatWSP2633-456937.20220303.

摘要

Abstract

This paper mainly studies the most effective investment plan for bitcoin and gold

to maximize total return and minimize investment risk. Before each trading day

this paper forecasts the trading price of the day through grey forecasting and time series based on short-term data(5-15 days) prior to the trading day. According to the forecast price to judge the rise and fall of the day

this paper researches quantitative investment trading strategy

with the help of indicators such as maximum rise and maximum fall

so as to ensure low investment risk and high return. Finally

the model is applied into bitcoin and gold transactions. The case study is also performed to verify the influence of variable parameters in the model.

关键词

Keywords

Quantitative investmentTrading strategyGrey predictionTime seriesLevel of sensitivity

references

Zirui Li. Research on quantitative investment trading strategy [d]. Tianjin University. (2013).[2] Peter L. Bernstein. A brief history of gold [M]. Shanghai University of Finance and Economics. (2013.8).[3] Jue Wang. Research on the construction and application of grey prediction model based on data characteristics. Jiangnan University. (2021).[4] Xiongwei He. Hai Lin. Empirical analysis of bitcoin time series prediction based on LSTM [J]. (36):40-46. (2020).[5] Lubitz, S. A. et al. Association between familial atrial fibrillation and risk of new-onset atrial fibrillation. JAMA 304, 2263–2269 (2010).

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