No more free lunch:The increasing popularity of machine learning and financial market efficiency  

作　　者：Jian Feng Xin Liu 

机构地区：[1]Faculty of Business and Economics,The University of Hong Kong,Hong Kong SAR,China [2]School of Finance,Renmin University of China,Beijing,China

出　　处：《Economic and Political Studies》2024年第1期34-57,共24页经济与政治研究（英文版）

基　　金：supported by the Key Programme of National Natural Science Foundation of China(NSFC)[Grant No.72233003].

摘　　要：In this paper,we show that the increasing popularity of machine learning improves market efficiency.By analysing the performance of a set of popular machine learning-based investment strategies,we find that profits from these strategies experience significant declines since the wide adoption of machine learning techniques,especially for profits based on the more preferred method of neural networks.These declines mainly come from long legs.Using the‘machine learning’Google search index as a proxy for machine learning-based trading intensity,we find that returns from the neural networks-based long–short and long-only strategies are weaker following high levels of machine learning intensity,while no relation is found between machine learning intensity and the short-only neural networks-based strategy.

关 键 词：Machine learning market efficiency MISPRICING neural networks arbitraging activities 

分 类 号：F832.5[经济管理—金融学] TP181[自动化与计算机技术—控制理论与控制工程]