Learn, build,
share, repeat.
We constantly learn more about investing, build disciplined strategies to capture the best of what we've learned, and share our broad findings with other curious investors.
PHILOSOPHY and PROCESS
FOLLOW OUR RESEARCH
O’Shaughnessy Quarterly Investor Letter Q4 2018By Patrick W. O’Shaughnessy, Chief Executive Officer and Portfolio Manager
In this quarter’s letter, we address the most common questions that we field at OSAM by discussing:
I. 2018 performance
II. Whether the market looks attractive as of January 2019
III. Factor performance during 2018 (which started fine and ended very badly)
IV. Our vision for the long-term future of OSAM.
ML & Investing Part 1: From Linear Regression to Ensembles of Decision StumpsBy Kevin Zatloukal, Ph. D
The idea of applying machine learning to finance and investing has become a popular topic of discussion recently, and for good reason. As its use becomes widespread, machine learning (ML) has the potential to change almost every part of society, both by automating routine activities and by improving performance in difficult activities. In all likelihood, investing will be no exception.
Alpha within FactorsBy Jesse Livermore+, Chris Meredith, CFA, and Patrick O’Shaughnessy, CFA
In Factors from Scratch, we showed that value investing works through a re-rating process. The process begins when the market develops an expectation that the earnings of certain companies will decline or grow at depressed rates into the future. The market then prices those companies at a discount relative to their current earnings, turning them into "value stocks." Over the short-term, the market usually ends up being right in its expectations: value stocks usually do go on to experience declines or slowdowns in their earnings, particularly in comparison with the rest of the market. But over the long-term, they usually recover and return to normal growth. When the market prices value stocks, it tends to underestimate the likelihood and extent of their eventual recoveries.
O’Shaughnessy Quarterly Investor Letter Q4 2018By Patrick W. O’Shaughnessy, Chief Executive Officer and Portfolio Manager
In this quarter’s letter, we address the most common questions that we field at OSAM by discussing:
I. 2018 performance
II. Whether the market looks attractive as of January 2019
III. Factor performance during 2018 (which started fine and ended very badly)
IV. Our vision for the long-term future of OSAM.
ML & Investing Part 1: From Linear Regression to Ensembles of Decision StumpsBy Kevin Zatloukal, Ph. D
The idea of applying machine learning to finance and investing has become a popular topic of discussion recently, and for good reason. As its use becomes widespread, machine learning (ML) has the potential to change almost every part of society, both by automating routine activities and by improving performance in difficult activities. In all likelihood, investing will be no exception.
Alpha within FactorsBy Jesse Livermore+, Chris Meredith, CFA, and Patrick O’Shaughnessy, CFA
In Factors from Scratch, we showed that value investing works through a re-rating process. The process begins when the market develops an expectation that the earnings of certain companies will decline or grow at depressed rates into the future. The market then prices those companies at a discount relative to their current earnings, turning them into "value stocks." Over the short-term, the market usually ends up being right in its expectations: value stocks usually do go on to experience declines or slowdowns in their earnings, particularly in comparison with the rest of the market. But over the long-term, they usually recover and return to normal growth. When the market prices value stocks, it tends to underestimate the likelihood and extent of their eventual recoveries.
Our Team - Consistency, Creativity, and Alignment
Investment success requires constant exploration, disciplined implementation, and skin in the game. We have built a team dedicated to applying our style of investing for the long term, whose interests are aligned with our clients and fellow OSAM colleagues.
Link: https://www.osam.com/
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