000 03616nam a22005415i 4500
001 978-1-4614-4103-8
003 DE-He213
005 20140220083249.0
007 cr nn 008mamaa
008 120719s2012 xxu| s |||| 0|eng d
020 _a9781461441038
_9978-1-4614-4103-8
024 7 _a10.1007/978-1-4614-4103-8
_2doi
050 4 _aHB135-147
072 7 _aKF
_2bicssc
072 7 _aMAT003000
_2bisacsh
072 7 _aBUS027000
_2bisacsh
082 0 4 _a519
_223
100 1 _aHult, Henrik.
_eauthor.
245 1 0 _aRisk and Portfolio Analysis
_h[electronic resource] :
_bPrinciples and Methods /
_cby Henrik Hult, Filip Lindskog, Ola Hammarlid, Carl Johan Rehn.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2012.
300 _aXIII, 335 p. 57 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598
520 _aInvestment and risk management problems are fundamental problems for  financial institutions and involve both speculative and hedging decisions. A structured approach to these problems naturally leads one to the field of applied mathematics in order to translate subjective probability beliefs and attitudes towards risk and reward into actual decisions.   In Risk and Portfolio Analysis the authors present sound principles and useful methods for making investment and risk management decisions in the presence of hedgeable and non-hedgeable risks using the simplest possible principles, methods, and models that still capture the essential features of the real-world problems. They use rigorous, yet elementary mathematics, avoiding technically advanced approaches which have no clear methodological purpose and are practically irrelevant. The material progresses systematically and topics such as the pricing and hedging of derivative contracts, investment and hedging principles from portfolio theory, and risk measurement and multivariate models from risk management are covered appropriately. The theory is combined with numerous real-world examples that illustrate how the principles, methods, and models can be combined to approach concrete problems and to draw useful conclusions. Exercises are included at the end of the chapters to help reinforce the text and provide insight.   This book will serve advanced undergraduate and graduate students, and practitioners in insurance, finance as well as regulators. Prerequisites include undergraduate level courses in linear algebra, analysis, statistics and probability.    
650 0 _aMathematics.
650 0 _aFinance.
650 0 _aEconomics
_xStatistics.
650 1 4 _aMathematics.
650 2 4 _aQuantitative Finance.
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aOperations Research/Decision Theory.
650 2 4 _aActuarial Sciences.
650 2 4 _aFinancial Economics.
700 1 _aLindskog, Filip.
_eauthor.
700 1 _aHammarlid, Ola.
_eauthor.
700 1 _aRehn, Carl Johan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461441021
830 0 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-4103-8
912 _aZDB-2-SMA
999 _c101481
_d101481