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008			100301s2008 xxk| s |||| 0|eng d
020			_a9781848000032
024	7		_a10.1007/978-1-84800-003-2 _2doi
035			_a978-1-84800-003-2
072		7	_aPBT _2bicssc
072		7	_aPBWL _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.2
090			_amg
100	1		_aSchmidli, Hanspeter. _91934
245	1	0	_aStochastic Control in Insurance _h[electronic resource]/ _cby Hanspeter Schmidli.
260			_aLondon: _bSpringer, _c2008.
300			_bdigital.
490	0		_aProbability and Its Applications, _x1431-7028
505	0		_aStochastic Control in Discrete Time -- Stochastic Control in Continuous Time -- Problems in Life Insurance -- Asymptotics of Controlled Risk Processes -- Appendices -- Stochastic Processes and Martingales -- Markov Processes and Generators -- Change of Measure Techniques -- Risk Theory -- The Black-Scholes Model -- Life Insurance -- References -- Index -- List of Principal Notation .
520			_aStochastic control is one of the methods being used to find optimal decision-making strategies in fields such as operations research and mathematical finance. In recent years, stochastic control techniques have been applied to non-life insurance problems, and in life insurance the theory has been further developed. This book provides a systematic treatment of optimal control methods applied to problems from insurance and investment, complete with detailed proofs. The theory is discussed and illustrated by way of examples, using concrete simple optimisation problems that occur in the actuarial sciences. The problems come from non-life insurance as well as life and pension insurance and also cover the famous Merton problem from mathematical finance. Wherever possible, the proofs are probabilistic but in some cases well-established analytical methods are used. The book is directed towards graduate students and researchers in actuarial science and mathematical finance who want to learn stochastic control within an insurance setting, but it will also appeal to applied probabilists interested in the insurance applications and to practitioners who want to learn more about how the method works. Readers should be familiar with basic probability theory and have a working knowledge of Brownian motion, Markov processes, martingales and stochastic calculus. Some knowledge of measure theory will also be useful for following the proofs .
650		0	_aMathematics _943458
650		0	_aMathematical optimization _937398
650		0	_aDistribution (Probability theory) _937119
697			_aMatemáticas Gerais- _x(inclusive alguns textos elementares sobre assuntos específicos) _923752
710	1		_aSpringerLink (Online service). _98857
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781848000025
830		0	_aProbability and its applications (Springer-Verlag) _915194
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-84800-003-2
942			_2impa _cEBK
999			_aSCHMIDLI, Hanspeter. <b> Stochastic Control in Insurance. </b> London: Springer, 2008. (Probability and Its Applications, 1431-7028). ISBN 9781848000032. Disponível em: <http://dx.doi.org/10.1007/978-1-84800-003-2 > _c38556 _d38556