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The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).  .

Markov processes. --- Statistical decision. --- Markov processes --- Programming (Mathematics) --- Stochastic control theory --- Finance --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Mathematical models --- Decision problems --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Mathematics. --- Applied mathematics. --- Engineering mathematics. --- Economics, Mathematical. --- Probabilities. --- Probability Theory and Stochastic Processes. --- Quantitative Finance. --- Applications of Mathematics. --- Game theory --- Operations research --- Statistics --- Management science --- Stochastic processes --- Distribution (Probability theory. --- Finance. --- Math --- Science --- Funding --- Funds --- Economics --- Currency question --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Stochastic control theory. --- Mathematical models. --- Economics, Mathematical . --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematical economics --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Methodology

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Dieses Lehrbuch bietet eine leicht verständliche Einführung in die moderne Finanzmathematik und erläutert grundlegende mathematische Konzepte der Optionsbewertung, der Portfolio-Optimierung und des Risikomanagements. Hierzu gehören die Preisbestimmung durch Arbitrageüberlegungen, die Preisbestimmung von amerikanischen Optionen über die Lösung optimaler Stopp-Probleme, die Bestimmung von optimalen Konsum- und Investitionsstrategien und Erwartungswert-Varianz Portfolios. Aktuelle Konzepte der Risikomessung wie Value at Risk und Expected Shortfall werden ebenso vorgestellt. Grundlagen in Stochastik und Optimierung reichen für das Verständnis der Inhalte aus, und zahlreiche Übungsaufgaben mit ausführlichen Lösungen sowie drei Anhänge erleichtern das Selbststudium. Die Autoren Prof. Dr. Nicole Bäuerle, Institut für Stochastik, Karlsruher Institut für Technologie Prof. Dr. Ulrich Rieder, Institut für Optimierung und Operations Research, Universität Ulm.

Economics, Mathematical . --- Statistics . --- Quantitative Finance. --- Statistics for Business, Management, Economics, Finance, Insurance.

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The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).  

Quantitative methods (economics) --- Operational research. Game theory --- Mathematics --- Financial analysis --- toegepaste wiskunde --- stochastische analyse --- financiële analyse --- kansrekening --- Markov processes --- Programming (Mathematics) --- Stochastic control theory --- Finance --- Markov, Processus de --- Programmation (Mathématiques) --- Commande stochastique --- Finances --- Mathematical models --- Modèles mathématiques --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B