Quantitative asset allocation system and method based on macroscopic factors, medium and equipment

Abstract

The invention provides a quantitative asset allocation system and method based on macroscopic factors, a medium and equipment. The quantitative asset allocation method based on the macroscopic factor comprises the following steps: acquiring asset allocation reference information; and making an asset allocation decision by using an economy-currency double-clock model to obtain an asset allocation result conforming to the asset allocation reference information. According to the method, a rational and reasonable asset allocation scheme can be effectively given, and adverse effects caused by severe fluctuation of the market can be avoided to a certain extent.

Description

technical field [0001] The present invention relates to the technical field of internet finance, in particular to a quantitative asset allocation system, method, medium and equipment based on macro factors. Background technique [0002] Traditional asset allocation models, such as Mean Variance Optimization, B-L model and Risk Parity, etc., although supported by rigorous mathematical derivation, often lack practical capabilities, which are mainly reflected in two aspects. [0003] First, the results of asset allocation are too theoretical, and the corresponding parameters are too sensitive. The asset / product allocation weights calculated by the mean-variance model are often greater than 1 or less than 0, which lacks practical allocation significance. And the mean-variance model is too sensitive to parameters (expected rate of return, volatility, covariance matrix, etc.), resulting in a small difference between the expected and the actual, which will lead to a significant ch...

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Problems solved by technology

Asset / product allocation weights calculated by the mean-variance model are often greater than 1 or less than 0, which lacks practical allocation significance

And the mean-variance model is too sensitive to parameters (expected rate of return, volatility, covariance matrix, etc.), resulting in a small difference between the expected and the actual, which will lead to a significant change in the configuration results of the model

The risk parity model has made some improvements to the problem of parameter sensitivity, but the estimation error of the future volatility (or other risk definitions) of all assets will still have a large deviation in the configuration conclusion of the model

[0004] Second, the traditional asset allocation model only guides the allocation based on the historical risk-return characteristics of the asset, without considering the attributes and characteristics of the asset itself, and does not take into account a large number of external variables that affect asset prices

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