A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Portfolio managers are constantly adapting to the ever-evolving environment of the investing landscape. Shifting market trends, government regulation and macroeconomic factors can all affect the way ...

Ben Johnson: Hi. I’m Ben Johnson, director of global ETF research with Morningstar. Today I’m on the sidelines of Morningstar’s 30th annual Morningstar Investment Conference, and I’m joined by Kevin ...

At first glance, it might appear that machine learning models and asset managers, particularly those that employ quantitative strategies, are a natural fit. But the reality is that many managers are ...

Quantum machine learning has been one of the most tantalizing promises in computational finance: the idea that qubits, ...

As investors enter bear market territory, alternative asset managers will need to differentiate themselves from competitors in ways they haven’t had to in years. Venture capital firm Georgian may ...

Abstract: One of the primary applications of machine learning methods is to uncover patterns from historical relationships and trends in the data. In unsupervised learning, we apply these methods and ...

Machine learning (ML) in asset management is an increasingly popular domain. Many studies and asset managers focus on forecasting returns with machine learning models to form investment portfolios ...

It’s estimated that more than 80% of financial advisers are using some form of model portfolios to handle their clients’ investments. In that overall category of outsourced investment management, the ...

Mehmet Caner, professor of economics, recently co-authored a study that illustrates the ability of machine learning to improve the Sharpe ratio which strengthens portfolio performance. Caner assisted ...