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Title:

Principal Component Models with Stochastic Mean-Reverting levels. Pricing and Covariance surface improvements

Document type:
Zeitschriftenaufsatz
Author(s):
Bi, M.; Escobar, M.; Goetz, B.; Zagst, R.
Non-TUM Co-author(s):
ja
Cooperation:
international
Abstract:
In this work, we create a family of simple stochastic covariance models, which showcase stochastic mean-reverting levels as an additional level of stochastic behavior beyond well-known stochastic volatility and correlation. The one-dimensional version of our model is inspired by Heston (1993), while the multidimensional model generalizes the principal component stochastic volatility model in Escobar and Olivares (2013). Their main contribution is that they capture stochastic mean-reversion leve...     »
Intellectual Contribution:
Discipline-based Research
Journal title:
Applied Stochastic Models in Business and Industry
Journal listet in FT50 ranking:
nein
Year:
2016
Journal volume:
32
Journal issue:
5
Pages contribution:
585-606
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1002/asmb.2179
Status:
Postprint / reviewed
TUM Institution:
Lehrstuhl für Finanzmathematik
Judgement review:
0
Key publication:
Nein
Peer reviewed:
Nein
International:
Ja
Book review:
Nein
Commissioned:
not commissioned
Professional Journal:
Nein
Technology:
Nein
Interdisciplinarity:
Nein
Mission statement:
;
Ethics and Sustainability:
Nein
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