Machine learning is an increasingly important and controversial topic in quantitative finance.
A lively debate persists as to whether machine learning techniques can be practical …

This paper demonstrates that portfolio optimization techniques represented by Markowitz
mean-variance and Hierarchical Risk Parity (HRP) optimizers increase the risk-adjusted …

This paper provides a summary of the current literature related to applying machine learning
algorithms in the field of finance with a focus on three main areas: asset pricing, bankruptcy …

Alpha factors are built to perform well over time, on average. There are instances when they
do not, and knowing these instances ex ante can be a significant source of added value for …

Abstract Machine Learning algorithms have been widely used and proven effective in
financial markets. In this paper, we introduced a Machine Learning model set trained on the …

We present a real-time, cross-asset, positions-based relative sentiment indicator to predict
the US equity market. Derived from the Commitments of Traders report, the indicator …

This paper uses European data only and provides evidence that 3 out of 4 investment styles,
as measured by 11 style proxies in total, exist in large and liquid European data panels …

O estudo analisa a possibilidade de integração de estratégias de investimento baseadas
critérios fundamentalistas de valor, qualidade e suas combinações, considerando também a …

It was early 2015 and executives in iShares' Factor Strategies Group were considering the
launch of a new class of exchange-traded funds (ETFs) called smart beta funds. Specifically …

为了验证中国股市是否存在小盘股和大盘股择时投资并具预测价值, 通过选取2005 年3
月至2013 年7 月巨潮小盘指数和巨潮大盘指数月度数据和周数据, 采用logit 分类选择模型 …