Financial Media, Price Discovery, and Merger Arbitrage

By |August 16th, 2021|Event Driven Investing, Research Insights, Basilico and Johnsen, Academic Research Insight, Machine Learning|

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 academic finance papers? Check out our Academic Research Insight category What are [...]

An Economic Framework for ESG Investing

By |March 22nd, 2021|ESG, Research Insights, Basilico and Johnsen, Academic Research Insight, Investment Advisor Education, Machine Learning|

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 of academic finance papers? Check out our Academic Research Insight category What [...]

Battle of the Sexes, Who’s Better at Fudging the Numbers?

By |January 19th, 2021|Research Insights, Women in Finance Know Stuff, Basilico and Johnsen, Academic Research Insight, Investment Advisor Education, Machine Learning|

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 be found hereWant to read our summaries of academic finance papers? [...]

Can A Computer Read Employee Emails and Detect Fraud?

By |October 19th, 2020|Research Insights, Basilico and Johnsen, Academic Research Insight, Investment Advisor Education, Machine Learning|

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 of this paper can be found hereWant to read our summaries [...]

News and its Impact on Risk and Returns Around the World

By |October 12th, 2020|Research Insights, Machine Learning, Macroeconomics Research|

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 paper can be found here.Want to read our summaries of academic [...]

How To Design Machine Learning Models – A Market Timing Example

By |September 24th, 2020|Research Insights, Factor Investing, Guest Posts, Machine Learning, Tactical Asset Allocation Research|

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 to say that machine learning hasn’t received mass adoption in [...]

Predicting Bond Returns? Focus on GDP Growth and Inflation Indicators

By |September 8th, 2020|Research Insights, Basilico and Johnsen, Academic Research Insight, Machine Learning, Fixed Income|

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 summaries of academic finance papers? Check out our Academic Research Insight category [...]

Fascinating Research Alert: Earning Calls, Clichès, and Negative Abnormal Returns

By |August 17th, 2020|Research Insights, Basilico and Johnsen, Academic Research Insight, Machine Learning|

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 can be found hereWant to read our summaries of academic finance [...]

Machine Learning and Investing: Forecasting Fundamentals w/ Ensembles

By |May 13th, 2020|Research Insights, Guest Posts, Academic Research Insight, Machine Learning|

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 of risk and/or systematic mispricing. However, what if we could [...]

Forecasting US Equity Market Returns with Machine Learning

By |January 7th, 2020|Research Insights, Machine Learning, Tactical Asset Allocation Research|

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 Wang, Harshdeep Singh Ahluwalia, Roger A. Aliaga-Díaz, and Joseph H. [...]

Alpha Architect Weekly Recap: Editorials on Machine Learning

By |December 21st, 2018|Research Insights, Machine Learning, Weekly Research Recap Videos|

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 use within Research. The first paper is an Editorial by [...]

Machine Learning Classification Methods and Factor Investing

By |December 21st, 2018|Research Insights, Machine Learning, Momentum Investing Research|

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., when underlying reality is nonlinear with complex interactions). In this [...]

A Protocol to Prevent “Quants Gone Wild”

By |December 17th, 2018|Academic Research Insight, Machine Learning|

A Backtesting Protocol in the Era of Machine Learning Rob Arnott, Campbell Harvey, and Harry Markowitz Working paper A version of this paper can be found here Want to read our summaries of academic finance papers? [...]

Machine Learning for Financial Market Prediction — Time Series Prediction With Sklearn and Keras

By |June 5th, 2018|Research Insights, Machine Learning|

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 Learning Approach." The paper presents a strategy that forecasts industry [...]

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