cam a22 2 4500 317106341 CHVBK 20201009031808.0 cr nn|008mamaa 140514s2014 xxu-----s---- 0 0-eng-d 978-1-4899-7441-9 print 978-1-4899-7442-6 eISBN 10.1007/978-1-4899-7442-6 doi (OCoLC)882944029 (IDSSG)000655368 Springer ger SzZuIDS HSG kids HD30.23 BUS049000 bisacsh 658.40301 23 CH0018D57F264D49E3427C1257F07007015F4 iCapture Hidden Markov Models in Finance Further Developments and Applications, Volume II edited by Rogemar S. Mamon, Robert J. Elliott Boston, MA Springer US 2014 Online-Ressource Text txt rdacontent/ger Computermedien c rdamedia/ger Online-Ressource cr rdacarrier/ger International Series in Operations Research & Management Science 209 Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research. The use of hidden Markov models (HMMs) has become one of the hottest areas of research for such applications to finance. This handbook offers systemic applications of different methodologies that have been used for decision making solutions to the financial problems of global markets. As the follow-up to the authors' Hidden Markov Models in Finance (2007), this offers the latest research developments and applications of HMMs to finance and other related fields. Amongst the fields of quantitative finance and actuarial science that will be covered are: interest rate theory, fixed-income instruments, currency market, annuity and insurance policies with option-embedded features, investment strategies, commodity markets, energy, high-frequency trading, credit risk, numerical algorithms, financial econometrics and operational risk. Hidden Markov Models in Finance: Further Developments and Applications, Volume II presents recent applications and case studies in finance, and showcases the formulation of emerging potential applications of new research over the book's 11 chapters. This will benefit not only researchers in financial modeling, but also others in fields such as engineering, the physical sciences and social sciences. Ultimately the handbook should prove to be a valuable resource to dynamic researchers interested in taking full advantage of the power and versatility of HMMs in accurately and efficiently capturing many of the processes in the financial market. Economics Distribution (Probability theory) Operations research Mamon Rogemar S. Elliott Robert J. https://doi.org/10.1007/978-1-4899-7442-6 Volltext für Angehörige der Universität St. Gallen / FHS St. Gallen BK020053 XK020053 XK020000 noalma ids I IDSSG HSG HSG ONL HONL000655368 IDSSG HFHS HFHS ONL HONL000655368 IDSSG 490 0- International Series in Operations Research & Management Science 209 IDSSG 700 1- Mamon Rogemar S. IDSSG 700 1- Elliott Robert J. IDSSG 856 4- https://doi.org/10.1007/978-1-4899-7442-6 Volltext für Angehörige der Universität St. Gallen / FHS St. Gallen SWISSBIB 034451161