大数据下的ETF资产量化配置及实证研究

Quantitative Allocation and Empirical Research of ETF Assets under Big Data

本文旨在深入探讨大数据下的ETF资产量化配置,通过获取深交所72家行业基金数据,综合运用三因子模型、熵权法以及奇异谱分析等多种量化模型方法,全面评估各行业ETF的风险和收益状况,在此基础上通过程序量化方法配置ETF资金组合策略,以达到最优的投资效果。同时,通过构造综合ETF指数进行奇异谱分析,用于跟踪股票市场的波动趋势方法,为投资者提供了量化的市场参考。本文的创新点和实用性在于为投资者提供一种新的全过程量化的ETF投资组合模式,从而更好地在管理投资风险下实现资产保值增值目标。

The paper on ETF Investment Strategies Based on Global Big Data Analysis.This department has analyzed 72 financial information data through cross-sectional data analysis,utilizing the Three Kingdoms sub-index.This enables a comparison of the effects of investment strategies under geometric mean and arithmetic mean conditions,strongly recommending the maintenance of the proportion and specifications of the LV ETF index to achieve the most effective market performance.During this period,through quantitative analysis of the selected Three Kingdoms sub-index ETF,designed to track the trends of the black market,we provide investors with the most valuable dynamic analysis.The department suggests that strategies designed to maximize investment returns,using this index,can be developed by comparing performances under different metrics,thereby better meeting the needs and expectations of investors and regulators.