Narrow search
Showing 1 - 10 of 224,326
Cover Image
Automated machine learning and asset pricing
Healy, Jerome V.; Gregoriou, Andros; Hudson, Robert - In: Risks : open access journal 12 (2024) 9, pp. 1-12
We evaluate whether machine learning methods can better model excess portfolio returns compared to the standard regression-based strategies generally used in the finance and econometric literature. We examine 17 benchmark factor model specifications based on Expected Utility Theory and theory...
Persistent link: https://www.econbiz.de/10015066381
Cover Image
Empirical Asset Pricing via Ensemble Gaussian Process Regression
Filipović, Damir; Pasricha, Puneet - 2022
We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...
Persistent link: https://www.econbiz.de/10014236083
Cover Image
Clustering-based sector investing
Bagnara, Matteo; Goodarzi, Milad - 2023
multiple operations, we employ a clustering approach on 69 firm characteristics and allocate companies to novel economic … investment set compared to standard classification schemes for portfolio optimization and for trading strategies based on within … to quantify feature importance for clustering methods, finding that size drives differences across classical industries …
Persistent link: https://www.econbiz.de/10014321226
Cover Image
Financial Machine Learning
Kelly, Bryan T.; Xiu, Dacheng - National Bureau of Economic Research - 2023
We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...
Persistent link: https://www.econbiz.de/10014322889
Cover Image
Empirical Asset Pricing via Machine Learning : The Global Edition
Cakici, Nusret; Zaremba, Adam - 2022
We examine the cross-section of international equity risk premia with machine learning methods. We identify, classify, and calculate 88 market characteristics and use them to forecast country returns with various machine learning techniques. While all algorithms produce substantial economic...
Persistent link: https://www.econbiz.de/10013306087
Cover Image
A bibliometric analysis of machine learning econometrics in asset pricing
Zapata, Hector O.; Mukhopadhyay, Supratik - In: Journal of risk and financial management : JRFM 15 (2022) 11, pp. 1-17
Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...
Persistent link: https://www.econbiz.de/10013475217
Cover Image
How Much Can Machines Learn Finance From Chinese Text Data?
Fan, Jianqing; Xue, Lirong; Zhou, Yang - 2021
power with an annualized return of 116% with a simple investment strategy and the portfolios based on our model …
Persistent link: https://www.econbiz.de/10013243543
Cover Image
Asset Pricing and Machine Learning : A Critical Review of Empirical Findings
Bagnara, Matteo - 2021
The latest development in empirical Asset Pricing is the employment of Machine Learning methods to address the problem of the factor zoo. These techniques offer great flexibility and prediction accuracy but require special care as they strongly depart from traditional Econometrics. I review and...
Persistent link: https://www.econbiz.de/10013321948
Cover Image
Financial Machine Learning
Kelly, Bryan T.; Xiu, Dacheng - 2023
We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...
Persistent link: https://www.econbiz.de/10014349505
Cover Image
What Does the Volatility Risk Premium Say About Liquidity Provision and Demand for Hedging Tail Risk?
Fan, Jianqing - 2016
This paper provides a data-driven analysis of the volatility risk premium, using tools from high-frequency finance and Big Data analytics. We argue that the volatility risk premium, loosely defined as the difference between realized and implied volatility, can best be understood when viewed as a...
Persistent link: https://www.econbiz.de/10013007611