ARMA model-based asset evaluation method, apparatus and device, and storage medium

Abstract

The embodiment of the invention discloses an asset assessment method, device and equipment based on an ARMA model, and a storage medium, which are applied to the field of artificial intelligence, and the method comprises the steps: obtaining sample asset assessment data of a plurality of sample assets, and determining the stability degree of each sample asset assessment data, taking the sample assets of which the stability degree of the sample asset evaluation data is greater than a stability degree threshold value as training sample assets; training an ARMA model of multiple groups of parameters based on the sample asset evaluation data of the training sample assets, and determining an asset evaluation model based on the ARMA model of multiple groups of parameters; obtaining asset data of at least two types of target assets; and generating target asset evaluation data of the target assets based on the asset data of the at least two target assets, inputting the target asset evaluation data of the target assets into an asset evaluation model, and determining replaceable resource evaluation information corresponding to the target assets. According to the embodiment of the invention, the efficiency and accuracy of asset assessment can be improved.

Description

technical field [0001] The present application relates to the field of artificial intelligence, and in particular to an asset evaluation method, device, equipment and storage medium based on an ARMA model. Background technique [0002] At present, the income method, as an important asset evaluation method, is widely cited in the field of asset evaluation. Its basic principle is to estimate the future net income of the target asset as the value of the asset (such as land, buildings, etc.). The variables that affect the results of the income method include: the future income of the asset and the income period of the asset. Among them, the income period of the asset can be determined by the remaining period of the land use right and the remaining economic life of the building, but there are many factors that affect the future income of the asset , it is difficult to predict. In the existing technology, the future income of an asset is usually estimated based on a fixed growth ...

AI Technical Summary

Problems solved by technology

The calculation process of this method is relatively simple, but for real estate such as real estate, the resource value that can be replaced by assets (for example, long-term rent or mortgage loans) usually increases exponentially, and the future income error calculated by fixing the growth rate of replaceable resources Larger, the accuracy of asset evaluation results is low

In addition, the growth rate of replaceable resources is usually determined based on the experience of asset appraisers, which is greatly affected by subjective factors, the accuracy of asset appraisal results is low, the efficiency of asset appraisal is low, and the applicability is poor

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