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@PHDTHESIS{Thalhammer:972304,
      author       = {Thalhammer, Marco Simon},
      othercontributors = {Lontzek, Thomas Siegmund and Wilms, Ole},
      title        = {{A}sset pricing with climate risks and heterogeneous
                      beliefs},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2023-10094},
      pages        = {1 Online-Ressource : Illustrationen, Diagramme},
      year         = {2023},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University; Dissertation, Rheinisch-Westfälische Technische
                      Hochschule Aachen, 2023},
      abstract     = {This thesis analyzes how climate risks are priced on
                      financial markets. We show that climate tipping thresholds,
                      disagreement about climate risks, and preferences that price
                      in long-run risks are crucial to an understanding of the
                      impact of climate change on asset prices. Our model
                      simultaneously explains several findings that have been
                      established in the empirical literature on climate finance:
                      (i) news about climate change can be hedged in financial
                      markets, (ii) the share of green investors has significantly
                      increased over the past decade, (iii) investors require a
                      positive, although small, climate risk premium for holding
                      “brown” assets, and (iv) “green” stocks outperformed
                      “brown” stocks in the period 2011–2021. The model can
                      also explain why investments in mitigating climate change
                      have been small in the past. Finally, the model predicts a
                      strong, non-linear increase in the marginal gain from
                      carbon-reducing investments as well as in the carbon premium
                      if global temperatures continue to rise.This thesis also
                      presents an adapted numerical solution approach based on
                      projection methods and Gauss-Hermite quadrature to solve
                      long-run risk asset-pricing models with disasters and
                      heterogeneous agents, where closed-form solutions are
                      unavailable. We demonstrate an effective approach for
                      handling nonlinearities, such as a tipping threshold. The
                      proposed approach demonstrates sufficient accuracy in
                      solving the equilibrium conditions, making it
                      computationally efficient even for models involving multiple
                      states and agents.},
      cin          = {811110},
      ddc          = {330},
      cid          = {$I:(DE-82)811110_20140620$},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2023-10094},
      url          = {https://publications.rwth-aachen.de/record/972304},
}