Research Article
Quantitative Portfolio of Gold and Bitcoin with Synthesized Prediction Models
@INPROCEEDINGS{10.4108/eai.9-12-2022.2327582, author={Xuan Wu and Zhinan Xie}, title={Quantitative Portfolio of Gold and Bitcoin with Synthesized Prediction Models}, proceedings={Proceedings of the 4th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2022, December 9-11, 2022, Chongqing, China}, publisher={EAI}, proceedings_a={MSIEID}, year={2023}, month={3}, keywords={time-series analysis; autoregressive prediction; statistical simulation}, doi={10.4108/eai.9-12-2022.2327582} }- Xuan Wu
Zhinan Xie
Year: 2023
Quantitative Portfolio of Gold and Bitcoin with Synthesized Prediction Models
MSIEID
EAI
DOI: 10.4108/eai.9-12-2022.2327582
Abstract
Quantitative portfolio of gold and bitcoin investment can be determined by synthesized quantitative model, with the help of various quantifying indicators. Previous prediction models labor to disperse risk of the investment portfolio as well as maximize the return. To handle it, this essay digs into a synthetic quantitative model of diversified regressive and prediction model, based on an enhanced ARIMA model, and this essay also integrates Analytic Hierarchy Process weight analysis and Monte Carlo model into it. In stage one, the daily value of the portfolio in a given time is predicted by enhanced ARIMA model, then the AHP method helps calculate the weight of the price rise and fall (%) of it, which leads to the establishment of two investment evaluation models on risk and income, respectively. In stage two, the judgment vector of whether to buy or sell was quantified through the ratio relationship. Eventually, the quantity of the two assets is determined by iterations, the accuracy and sensitivity of judgment of bitcoin and gold trading are quantified precisely, and decision-making is made with a slighter influence from inter-group conflicts.
