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Factor mimicking portfolios for climate risk
De Nard, Gianluca; Engle, Robert F.; Kelly, Bryan T. - 2024 - This version: March 2024
We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices … climate risk hedge portfolios. The new mimicking portfolio approach is much more efficient than traditional sorting or maximum … delivering markedly higher and statistically significant alphas and betas with the climate risk indices. …
Persistent link: https://www.econbiz.de/10014531337
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Factor mimicking portfolios for climate risk
De Nard, Gianluca; Engle, Robert F.; Kelly, Bryan T. - 2023 - This version: March 2023
We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices … climate risk hedge portfolios. The new mimicking portfolio approach is much more efficient than traditional sorting or maximum … delivering markedly higher and statistically significant alphas and betas with the climate risk indices. …
Persistent link: https://www.econbiz.de/10014232089
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Hedging macroeconomic and financial uncertainty and volatility
Dew-Becker, Ian; Giglio, Stefano; Kelly, Bryan T. - 2019
Persistent link: https://www.econbiz.de/10012124936
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Hedging macroeconomic and financial uncertainty and volatility
Dew-Becker, Ian; Giglio, Stefano; Kelly, Bryan T. - 2020
Persistent link: https://www.econbiz.de/10012300973
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Hedging climate change news
Engle, Robert F.; Giglio, Stefano; Kelly, Bryan T.; … - 2019
Persistent link: https://www.econbiz.de/10012015507
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Hedging climate change news
Engle, Robert F.; Giglio, Stefano; Lee, Heebum; Kelly, … - 2019 - This version: May 7, 2019
We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news … change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk … approaches to managing climate risk. …
Persistent link: https://www.econbiz.de/10012024377
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Complexity in factor pricing models
Didisheim, Antoine; Ke, Barry; Kelly, Bryan T.; … - 2024
We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance---in terms of SDF Sharpe ratio and test asset pricing errors---is improving in model parameterization (or "complexity''). Our empirical findings verify the...
Persistent link: https://www.econbiz.de/10014472608
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The virtue of complexity in machine learning portfolios
Kelly, Bryan T.; Malamud, Semyon; Zhou, Kangying - 2021
Contrary to conventional wisdom in nance, return prediction R2 and optimal portfolio Sharpe ratio generally increase with model parameterization, even when minimal regularization is used. We theoretically characterize the behavior of return prediction models in the high complexity regime, i.e....
Persistent link: https://www.econbiz.de/10012800453
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Principal portfolios
Kelly, Bryan T.; Malamud, Semyon; Pedersen, Lasse Heje - 2020 - This version: June 8, 2020
We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...
Persistent link: https://www.econbiz.de/10012271188
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Universal portfolio shrinkage
Kelly, Bryan T.; Malamud, Semyon; Pourmohammadi, Mohammad; … - 2023
Persistent link: https://www.econbiz.de/10014483260