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the-kelly-criterion's Introduction

The Kelly Criterion

This is the accompanying Jupyter Notebook for this blog post.

When investing, we spend plenty of time thinking about which securities should we buy but we rarely wonder how much money should we allocate in each asset.

Although it does not seem like an important aspect, it is crucial when defining a strategy, up to the point that it can determine the whole performance of your portfolio.

In this sense, the Kelly criterion helps us selecting the optimal proportion such that we can maximize our expected returns.

There have been many papers and books written about the Kelly criteria and its characteristics. In this notebook we will see an introduction for the Kelly criterion in continuous time and it's uses for the stock market. This notebook's aim is to serve as a starting point to understand and apply the Kelly criterion in the stock market. Personally, I find the Kelly Criterion fascinating for it's simplicity, elegance and utility.

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the-kelly-criterion's Issues

Treat tail risks

If you assume normality, then the "optimal" strategy vastly underestimates the tail risk, which is why it wants to leverage like a crazy person.

I believe part of the problem is the use of variance. Variance can't capture fat tails.

Use a distribution that better captures the tails. Examples:

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