Disclosures: qplum LLC is a registered investment adviser. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and are never guaranteed. Be sure to first consult with a qualified financial adviser and/or tax professional before implementing any strategy discussed herein. Past performance is not indicative of future performance.... continued from STAC New York keynote
where we covered
Narv Narvekar
HMC
David Swensen
Yale
Warren Buffett
Berkshire
Ken Griffin
Citadel
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It turns out that allocating to investment strategies is very similar to recommender systems
Visualization of matrix factorization based collaborative filtering
"Unsupervised learning had a catalytic effect in reviving interest in deep learning, but has since been overshadowed by the successes of purely supervised learning. Although we have not focused on it in this Review, we expect unsupervised learning to become far more important in the longer term." - Geoffrey Hinton et. al., Nature, Deep Learning
- Investment strategies that learn by themselves (article)
Disclosures: qplum LLC is a registered investment adviser. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and are never guaranteed. Be sure to first consult with a qualified financial adviser and/or tax professional before implementing any strategy discussed herein. Past performance is not indicative of future performance.
It is not always just about higher returns.
Utility function is not uniformly distributed.
Utility function is not the same.
Most pension funds have a nominal target yield.
Not meeting the target yield is a big deal compared to outperformance
III. Capacity:
Investments that have scale and capacity to get in and to get out
IV. Should work with illiquid assets:
Illiquid investments are a part of everyone's portfolio.
One cannot look at liquid investments without considering the illiquid assets that are a part of the portfolio already.
“By choosing to place asset allocation at the center of the investment process, investors ground the decision-making framework on the stable foundation of long-term policy actions.
Focus on asset allocation relegates market timing and security selection decisions to the background, reducing the degree to which investment results depend on mercurial, unreliable factors.
Selecting the asset classes for a portfolio constitutes a critically important set of decisions, contributing in large measure to a portfolio’s success or failure. Identifying appropriate asset classes requires focus on functional characteristics, considering potential to deliver returns and to mitigate portfolio risk. Commitment to an equity bias enhances returns, while pursuit of diversification reduces risks. Thoughtful, deliberate focus on asset allocation dominates the agenda of long-term investors.”
– David Swensen
(a) Target constant risk in the portfolio.
(b) Optimize portfolio for the specified utility function.
(c) Constrain any studies to a specified, systematic risk management threshold.
"security analysis may begin--modestly, but hopefully--to refer to itself as a scientific discipline "
Imagining investing with "trustworthy tool" and not experts.
- Benjamin Graham
By Gaurav Chakravorty
Gaurav Chakravorty, co-founder and Chief Investment Officer at qplum, will discuss how Deep Learning can be used in global tactical asset allocation. We will show how this investment strategy compares to a traditional institutional investing benchmark as well as qplum's US investor index. We believe that Deep Learning will provide a huge contribution to asset management in its utility for core tactical asset allocation rather than indirectly predicting returns.
