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Autoencodeurs Appliqués À La Construction De Portefeuilles Mean-Reverting (Autoencoders Applied to define Mean-Reverting Portfolios)

https://doi.org/10.2139/ssrn.2952833
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/0304-4076(94)90055-8openalex-extracted
Comparison of Box—Tiao and Johansen canonical estimators of cointegrating vectors in VEC(1) models
inferredcites →https://doi.org/10.1080/14697680903124632openalex-extracted
Statistical Arbitrage in the U.S. Equities Market
inferredcites →https://doi.org/10.1080/14697688.2010.481634openalex-extracted
Identifying small mean-reverting portfolios
inferredcites →https://doi.org/10.1145/1390156.1390294openalex-extracted
Extracting and composing robust features with denoising autoencoders
inferredcites →https://doi.org/10.1515/9783110976588.viiopenalex-extracted
Vorwort
inferredcites →https://doi.org/10.18653/v1/d13-1170openalex-extracted
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
inferredcites →https://doi.org/10.2139/ssrn.2595051openalex-extracted
inferredcites →https://doi.org/10.1016/b978-1-78548-008-9.50002-2openalex-snapshot
Smart Beta: Managing Diversification of Minimum Variance Portfolios
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.