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4. Time Series Variational Autoencoders

This video presents time series variational autoencoders (VAEs) and explores how they can be used for investment simulation and missing data imputation.

Section 3.2.2 in the Portfolio Construction and Risk Management book gives a brief introduction to generative machine learning methods for investment market simulation, including variational autoencoders (VAEs), which can also be used to impute missing data.

This video presents the VAE examples of the Investment Simulation module, including multi-asset simulation as well as holiday, long-term, and alternatives missing data imputation.

The attached PDF provides a written summary of the perspectives and case studies.

Variational Autoencoders For Investment Time Series
1.12MB ∙ PDF file
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See also this video presenting stationary transformations and the Fully Flexible Resampling method.

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