Applied quantamental investment management using the Fully General Investment Framework (FGIF) from the Portfolio Construction and Risk Management book.
| Platform |  | Pricing | Freemium | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 123 | Founded | 2 years ago | Last Issue | 4 days ago |
| Active | |||||
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antonvorobets.substack.comLatest Issues
Conditional Maximum Loss vs Variance Backtest
This article presents a Python case studying comparing the performance of Conditional Maximum Loss (CML) and variance-optimized portfolios.
Analyzing and optimizing tail risk is receiving accelerating attention to the point that even the a...
Latest Scientific Investment Research
Screenshot of the Science tab of the Quantamental Investing publication.
As some of you might remember, I stopped updating my SSRN page due to an unfair treatment of the Conditional Maximum Loss Portfolio Optimization article. I experience...
CVaR vs CML Portfolio Optimization
This article sheds some light on when we should expect big differences between CVaR and CML portfolio optimization.
The recently introduced Conditional Maximum Loss (CML) investment risk measure is a natural generalization of Conditional V...
Future Technologies and Case Studies
Overview of the Conditional Maximum Loss (CML) formula in the Fully General Investment Framework (FGIF).
There are two fundamental issues with old investment technology:
- It is dangerously oversimplifying with mean-variance analysis....
Investment Data Imputation with Variational Autoencoders
This article illustrates how we can perform missing investment data imputation using variational autoencoders (VAEs).
A situation where you are missing some investment data can occur for several reasons. For example, you might trade in glo...
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Authors
The writers behind this newsletter.
I am Founder & CEO of Fortitudo Technologies; an investment technology company offering novel software solutions to the investment management industry. I share content about cutting-edge risk and analysis methods for sophisticated investors.
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