Using Machine Learning to Predict Options Returns
Option Return Predictability with Machine Learning and Big Data Bali, Beckmeyer, Moerke, WeigertA version of this paper can be found hereWant to read our summaries of [...]
Option Return Predictability with Machine Learning and Big Data Bali, Beckmeyer, Moerke, WeigertA version of this paper can be found hereWant to read our summaries of [...]
Financial Media, Price Discovery, and Merger Arbitrage Buehlmaier and ZechnerReview of Finance, forthcomingA version of this paper can be found hereWant to read our summaries of [...]
Part 1: The End of Accounting This is the first part of a series of guest posts by Kai Wu, the CIO & Founder of [...]
Responsible Investing: The ESG Efficient Frontier Pedersen, Fitzgibbons, and PomorskiJournal of Financial Economics, 2020A version of this paper can be found hereWant to read our summaries [...]
CFO Gender and Financial Statement Irregularities V.K.Gupta, S. Mortal, B. Chakrabarty, X. Guo, D. B. TurbanAcademy of Management Journal, 2019A version of this paper can [...]
Zero-Revelation RegTech: Detecting Risk through Linguistic Analysis of Corporate Emails and News S.R. Das, S. Kim, B. KothariJournal of Financial Data Science, Spring 2019A version [...]
How news and its context drive risk and returns around the world Charles Calomiris and Harry MamayskyJournal of Financial Economics, August 2019A version of this [...]
We at ENJINE are big believers in the potential of machine learning (or as some call, “artificial intelligence”) to transform asset management. However, it’s fair [...]
Predicting Bond Returns: 70 Years of International Evidence Guido Baltussen, Martin Martens, Olaf PenningaWorking PaperA version of this paper can be found hereWant to read our [...]
When More or Less is Less: Managers' Clichès J. Klevak, J. Livnat, and K. SuslavaJournal of Financial Data Science, Summer 2019A version of this paper [...]
Quantitative factor portfolios generally use historical company fundamental data in portfolio construction. The key assumption behind this approach is that past fundamentals proxy for elements [...]
This blog talks about reinforcement learning for trading applications. Once one of my pups found half a roast chicken in the corner of a parking [...]
Shiller's CAPE ratio is a popular and useful metric for measuring whether stock prices are overvalued or undervalued relative to earnings. Recently, Vanguard analysts Haifeng [...]
Researchers love novel datasets--it gives them a new set of information to conduct studies and test theories. That brings us to this paper, titled "Core [...]
You can watch the video via this link: https://www.youtube.com/embed/tVwwZ1-bThI This week Ryan and I discuss two editorials on machine learning and its impact and [...]
In the last post in our machine learning series, we showed how nonlinear regression algos might improve regression forecasting relative to plain vanilla linear regression (i.e., [...]
A Backtesting Protocol in the Era of Machine Learning Rob Arnott, Campbell Harvey, and Harry MarkowitzWorking paperA version of this paper can be found hereWant to [...]
Recently, Wes pointed me to this interesting paper by David Rapach, Jack Strauss, Jun Tu and Guofu Zhou: "Dynamic Return Dependencies Across Industries: A Machine [...]
If you are out to describe the truth, leave elegance to the tailor. — Albert Einstein Machine learning is everywhere now, from self-driving cars to [...]
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