Innovations in Quantitative Risk Management:TU München, September 2013
Quantitative models are omnipresent –but often controversially discussed– in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing...
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oai:scholar.dlu.edu.vn:DLU123456789-576282023-11-11T05:46:40Z Innovations in Quantitative Risk Management:TU München, September 2013 Glau, Kathrin Scherer, Matthias Zagst, Rudi Financial risk management Congresses Quantitative research Quantitative Finance Quantitative models are omnipresent –but often controversially discussed– in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well. 2015-08-19T07:28:31Z 2015-08-19T07:28:31Z 2015 Book 978-3-319-09113-6 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57628 en application/pdf Springer |
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Thư viện Trường Đại học Đà Lạt |
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English |
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Financial risk management Congresses Quantitative research Quantitative Finance |
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Financial risk management Congresses Quantitative research Quantitative Finance Glau, Kathrin Scherer, Matthias Zagst, Rudi Innovations in Quantitative Risk Management:TU München, September 2013 |
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Quantitative models are omnipresent –but often controversially discussed– in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well. |
format |
Book |
author |
Glau, Kathrin Scherer, Matthias Zagst, Rudi |
author_facet |
Glau, Kathrin Scherer, Matthias Zagst, Rudi |
author_sort |
Glau, Kathrin |
title |
Innovations in Quantitative Risk Management:TU München, September 2013 |
title_short |
Innovations in Quantitative Risk Management:TU München, September 2013 |
title_full |
Innovations in Quantitative Risk Management:TU München, September 2013 |
title_fullStr |
Innovations in Quantitative Risk Management:TU München, September 2013 |
title_full_unstemmed |
Innovations in Quantitative Risk Management:TU München, September 2013 |
title_sort |
innovations in quantitative risk management:tu münchen, september 2013 |
publisher |
Springer |
publishDate |
2015 |
url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57628 |
_version_ |
1819767128166760448 |