This video goes through the Time- and State-Dependent Resampling SSRN article1 and its accompanying Python code2.
Time- and State-Dependent Resampling is a new general class of time series resampling methods for high-dimensional investment market simulation.
The Fully Flexible Resampling method, first introduced in Chapter 3 of the Portfolio Construction and Risk Management book3, is an instance of the Time- and State-Dependent Resampling class. You can read more about this relation in this post4.
Watch the next video in this playlist here:
12. The Normal Distribution Myth
The normal return distribution assumption has been made on many occasions in academic finance theories such as CAPM, Black-Litterman, and mean-variance.
Time- and State-Dependent Resampling SSRN article: https://ssrn.com/abstract=5117589
Time- and State-Dependent Resampling Python code: https://github.com/fortitudo-tech/fortitudo.tech/blob/main/examples/11_TimeStateResampling.ipynb
Portfolio Construction and Risk Management Book: https://antonvorobets.substack.com/p/pcrm-book
Time- and State-Dependent Resampling post: https://antonvorobets.substack.com/p/time-and-state-dependent-resampling
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