Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Christina Erlwein-Sayer"'
Autor:
Christina Erlwein-Sayer
Publikováno v:
Risks, Vol 6, Iss 4, p 141 (2018)
We enhance the modelling and risk assessment of sovereign bond spreads by taking into account quantitative information gained from macro-economic news sentiment. We investigate sovereign bonds spreads of five European countries and improve the predic
Externí odkaz:
https://doaj.org/article/33abbaf552694f9998d51a2bed8250b9
Publikováno v:
Applied Stochastic Models in Business and Industry. 36:307-334
We consider portfolio optimization in a regime‐switching market. The assets of the portfolio are modeled through a hidden Markov model (HMM) in discrete time, where drift and volatility of the single assets are allowed to switch between different s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::add4749d5d1fcad45a0a518b3b67b8fc
https://doi.org/10.1002/asmb.2491
https://doi.org/10.1002/asmb.2491
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf7d7b846248ddb860b12f7e0ce5bcef
https://doi.org/10.2139/ssrn.4003338
https://doi.org/10.2139/ssrn.4003338
Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, d
Publikováno v:
Computational Management Science. 17:493-494
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e55f0444df6693c1fc98a97425b4996
https://doi.org/10.1007/s10287-020-00384-3
https://doi.org/10.1007/s10287-020-00384-3
Publikováno v:
Computational Management Science. 15:135-137
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a497c5334fdbedef7913815a68522594
https://doi.org/10.1007/s10287-018-0322-0
https://doi.org/10.1007/s10287-018-0322-0
Publikováno v:
Nonlinear Analysis: Hybrid Systems. 35:100814
This paper details the implementation in discrete time of filters for a mean-reverting model formulated under a continuous-time framework, whereby a hidden Markov chain governs the model’s parameters. Parameter estimates are determined via adaptive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::969874d45218371f48b71145d383bd92
https://doi.org/10.1016/j.nahs.2019.08.001
https://doi.org/10.1016/j.nahs.2019.08.001
Publikováno v:
High-Performance Computing in Finance ISBN: 9781315372006
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::263eefb7353cfbd3ebb99ff62eed6665
https://doi.org/10.1201/9781315372006-2
https://doi.org/10.1201/9781315372006-2
Publikováno v:
SSRN Electronic Journal.
In this study, we introduce a new method of assessing the credit risk of corporate bonds; where in addition to the historical market data news sentiment data is used. Typically, a higher yield spread is usually associated with higher credit risk. By
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f73e0730f00a5e3f52d1bd1aa771d67
https://doi.org/10.2139/ssrn.3405977
https://doi.org/10.2139/ssrn.3405977
Publikováno v:
SSRN Electronic Journal.
We consider portfolio optimization in a regime-switching market. The assets of the portfolio are modeled through a hidden Markov model (HMM) in discrete time, where drift and volatility are allowed to switch between different states. We consider diff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18d040c8bc1f4cede91bcec3ce30ca84
https://doi.org/10.2139/ssrn.2876807
https://doi.org/10.2139/ssrn.2876807