This paper proposes markovian models in portfolio theory and risk management. In a first analysis, we describe discrete time optimal allocation models. Then, we examine the investor’s optimal choices either when returns are uniquely determined by their mean and variance or when they are modeled by a Markov chain. Moreover we propose different models to compute VaR and CVaR when returns are modeled by a Markov chain.

Financial Risk Modeling with Markov Chains

LECCADITO, Arturo;ORTOBELLI LOZZA, Sergio;RUSSO, Emilio;IAQUINTA, Gaetano
2006-01-01

Abstract

This paper proposes markovian models in portfolio theory and risk management. In a first analysis, we describe discrete time optimal allocation models. Then, we examine the investor’s optimal choices either when returns are uniquely determined by their mean and variance or when they are modeled by a Markov chain. Moreover we propose different models to compute VaR and CVaR when returns are modeled by a Markov chain.
book chapter - capitolo di libro
scientifica
Inglese
2006
Intelligent Data Engineering and Automated Learning - IDEAL 2006: 7th International Conference, Burgos, Spain, September 20-23, 2006, Proceedings
Corchado, E.; Yin, H.; Botti, V. Fyfe, C.
cartaceo
online
978-3-540-45485-4
4224
1275
1282
Germany
Berlin-Heidelberg
Springer Verlag
esperti anonimi
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie
Computational complexity; Markov chain; VaR; Portfolio selection
info:eu-repo/semantics/bookPart
none
1.2 Contributi in volume - Book chapters::1.2.01 Contributi in volume (Capitoli o Saggi) - Book Chapters/Essays
no full text
Leccadito, Arturo; ORTOBELLI LOZZA, Sergio; Russo, Emilio; Iaquinta, Gaetano
4
268
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/19482
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