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microprediction authored Aug 22, 2024
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Expand Up @@ -6,6 +6,21 @@ In no particular order. The scope is robust diversified portfolios and things th

Or file an [issue](https://github.com/microprediction/precise/issues).

## Essays on Robust Portfolio Management [pdf](https://www.e-helvetica.nb.admin.ch/api/download/urn%3Anbn%3Ach%3Abel-1412461%3ADis4910.pdf/Dis4910.pdf)
Lukas Plachel

Chapter 1 addresses the problems of traditional mean-variance optimization originating from model- and estimation errors. In order to simultaneously tackle both
error sources, a joint method for covariance regularization and robust optimization
is proposed which exploits the inherent complementarity between the two concepts.
Chapter 2 introduces a covariance estimation approach which is based solely on
characteristic company information. In contrast to traditional, time series based estimation procedures which typically lead to extreme and unreliable estimates, the proposed method produces stable covariance matrices which can be used if no time series
data is available, or complementary to traditional methods. We derive characteristicsbased covariance matrices for a US stock universe and use them as shrinkage targets in
a minimum variance optimization example.
Chapter 3 bridges the gap between MPT and one of the most vivid fields of contemporary research: Artificial Intelligence. A model is introduced which uses a Neural
Network to learn the relation between portfolio weights and arbitrary measures of
portfolio success. Based on the resulting approximation function, a Genetic Algorithm is employed to derive a near-optimal allocation. Two portfolio selection examples for the commodity and the equity market illustrate the potential to successfully
implement a wide scope of traditional and exotic investment strategies.

## Robust Growth-Optimal Portfolios [pdf](https://core.ac.uk/download/pdf/76990543.pdf)
Napat Rujeerapaiboon

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