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v1.0.7 (#11)
* README update * mathbb fix attempt * poetry updates
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README.md

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@@ -29,13 +29,19 @@ Entropy Pooling is a powerful method for implementing subjective views and
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performing stress-tests for fully general Monte Carlo distributions. It was first
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introduced by [Meucci (2008)](https://ssrn.com/abstract=1213325) and refined
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with sequential algorithms by [Vorobets (2021)](https://ssrn.com/abstract=3936392).
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[You can loosely think about Entropy Pooling as a generalization of the Black-Litterman model](https://antonvorobets.substack.com/p/entropy-pooling-vs-black-litterman-abb608b810cd) without all the oversimplifying assumptions. Entropy Pooling operates directly on
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[the next generation market representation](https://youtu.be/4ESigySdGf8?si=yWYuP9te1K1RBU7j&t=46)
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defined by the simulation matrix $R\in \mathbb{R}^{S\times I}$ and associated joint
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scenario probability vector $p\in \mathbb{R}^{S}$.
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For a quick introduction to Entropy Pooling intuition, watch [this YouTube video](https://youtu.be/qk_5l4ICXfY).
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The original Entropy Pooling approach solves the minimum relative entropy problem
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$$q=\underset{x}{\text{argmin}}\lbrace x^{T}\left(\ln x-\ln p\right)\rbrace$$
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subject to the constraints
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subject to linear constraints on the posterior probabilities
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$$Gx\leq h \quad \text{and} \quad Ax=b.$$
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to a posterior probability vector $q$.
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A useful statistic when working with Entropy Pooling is the effective number of
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scenarios introduced by [Meucci (2012)](https://ssrn.com/abstract=1971808). For
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a causal Bayesian nets overlay on top of Entropy Pooling, see
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scenarios introduced by [Meucci (2012)](https://ssrn.com/abstract=1971808).
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For a causal Bayesian network overlay on top of Entropy Pooling, see
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[Vorobets (2023)](https://ssrn.com/abstract=4444291).
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Video walkthroughs
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Video walkthroughs of the two notebook examples are available [here](https://youtu.be/hDt103zEML8)
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and [here](https://youtu.be/DK1Pv5tuLgo). The videos give additional insights into
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Entropy Pooling theory and its sequential refinements. It is highly recommended
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to watch these two videos to quickly increase your understanding.
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to watch these videos to quickly increase your understanding.
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Portfolio Construction and Risk Management Book
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-----------------------------------------------

poetry.lock

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pyproject.toml

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[tool.poetry]
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name = "entropy-pooling"
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version = "1.0.6"
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version = "1.0.7"
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description = "Entropy Pooling in Python with a BSD 3-Clause license."
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authors = ["Fortitudo Technologies <software@fortitudo.tech>"]
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license = "BSD-3-Clause"

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