Explainable artificial intelligence for crypto asset allocation

被引：38

作者：

Babaei, Golnoosh ^{[1
]}

Giudici, Paolo ^{[2
]}

Raffinetti, Emanuela ^{[2
]}

机构：

[1] Univ Pavia, Via San Felice 5, I-27100 Pavia, Italy

[2] Univ Pavia, Dept Econ & Management, Via San Felice 5, I-27100 Pavia, Italy

来源：

FINANCE RESEARCH LETTERS | 2022年 / 47卷

关键词：

Machine learning; Shapley values; Robo-advisory;

D O I：

10.1016/j.frl.2022.102941

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

Many investors have been attracted by Crypto assets in the last few years. However, despite the possibility of gaining high returns, investors bear high risks in crypto markets. To help investors and make the markets more reliable, Robot advisory services are rapidly expanding in the field of crypto asset allocation. Robot advisors not only reduce costs but also improve the quality of the service by involving investors and make the market more transparent. However, the reason behind the given solutions is not clear and users face a black-box model that is complex. The aim of this paper is to improve trustworthiness of robot advisors, to facilitate their adoption. For this purpose, we apply Shapley values to the predictions generated by a machine learning model based on the results of a dynamic Markowitz portfolio optimization model and provide explanations for what is behind the selected portfolio weights.

引用

页数：7

共 25 条

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