Tails, Black Swans and Optimal Portfolios

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Tails, Black Swans and Optimal Portfolios

Jan Rosenzweig discuss non-diversified optimal portfolios and Modern Portfolio Theory.

Tuesday 14 June 2022

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Podcast Description

QuantSpeak host, Dan Tudball, is joined by Jan Rosenzweig, Portfolio Manager at Pine Tree, to discuss why optimal portfolios are not diversified, his first encounter with Modern Portfolio Theory, and his career journey as a quant finance professional.

Topics & Timestamps

[00:00 - 01:18] Guest Welcome and Talk Preview

[01:18 - 06:15] Discussion: Modern Portfolio Theory, Sharpe Ratios, Diversification, Theory vs. Practice

[06:15 - 06:52] Reflection: Early Experience with Modern Portfolio Theory

[06:52 - 08:12] Transition from Theory to Practice: Realities on the Trading Desk

[08:12 - 09:27] Models as Frames of Reference: Options, Tail Risk, and Practical Hacks

[09:27 - 14:56] Tail Risk Management: Diversification, Hedging, Measures of Tail Risk, and Limitations

[14:56 - 15:25] Agent-Based Modeling & Behavioral Finance: Potential and Challenges

[15:25 - 16:29] Limitations of Behavioral & Agent-Based Models for Tail Risk

[16:29 - 18:41] High Order Moments: Why They Matter, Distribution Filtering, and Practical Limitations

[18:42 - 20:01] Estimating High Order Moments & Practical Allocation

[20:01 - 21:12] Moment Convergence, Drawdown, and Theoretical vs. Practical Issues

[21:12 - 23:02] Takeaways: Diversification as the Core Message

[23:02 - 24:54] Difficulties in Defining “Fixed Allocation” and Practical Rules of Thumb

[24:54 - 28:13] Tail Risk Funds: Market Cycles, Appropriateness, and Market Outlook

[28:13 - 34:33] Cross-Disciplinary Inspiration: Neuroscience and Portfolio Research

[34:33 - 38:22] Career Path, and Career Advice: Stay Open, Recognize and Use New Ideas

[38:22 - 40:23] Talk Takeaways: Recognizing the Limits of Modern Portfolio Theory, Seeing the Full Spectrum.

Disclaimer

Podcasts are for informational purposes only and provided “as is” without any representation or warranty from Fitch Learning of any kind. Comments or statements expressed by speakers may not be those of the Fitch Learning. Fitch Learning is not providing advice or recommendations. Fitch Learning, its directors, officers, or employees do not accept any liability for any loss arising from the use of information.