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020 _a9783031546884
_9978-3-031-54688-4
024 7 _a10.1007/978-3-031-54688-4
_2doi
050 4 _aQA273.A1-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
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072 7 _aPBT
_2thema
072 7 _aPBWL
_2thema
100 1 _aRossello, Damiano.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980862
245 1 2 _aA Cookbook with Probability One
_h[electronic resource] :
_bWith Financial Applications /
_cby Damiano Rossello.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXII, 402 p. 46 illus., 4 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLa Matematica per il 3+2,
_x2038-5757 ;
_v161
505 0 _a1 Probability, Events and Random Variables -- 2 Distribution of Random Variables -- 3 Multidimensional Random Variables -- 4 Moments and the Alike -- 5 Special Distributions -- 6 Conditioning -- 7 Regression, Prediction and more Dependence -- 8 Convergence Concepts -- 9 Introduction to Stochastic Processes -- 10 Introduction to Market Risk Measures.
520 _aThis book offers accessible probabilistic modelling of relevant financial problems. It is divided into two parts. The first part (cookbook) is written by emphasizing the key definitions and theorems without wasting too much of the reader with unnecessary technical details. Here, the first kind of target audience is graduate students in Economics with no prior exposition to probability theory (except for undergraduate courses in Applied Statistics) which are provided by a self-contained account of probabilistic modelling mainly applied to finance. The fundamental concepts of random variable/vector and probability distributions are introduced beforehand with respect to the usual treatment of this subject in standard probability textbook, trying to strike a balance between precise mathematical definitions and their applied knowledge. All the analytic tools developed are illustrated through examples of probability distributions of future stock prices, returns and profit and loss, together with their main characteristics, such as moments, moment generating and characteristic functions, location-scale families, and quantiles. The extension to the multivariate case for fixed time horizons is presented, together with the fundamentals of stochastic processes both in discrete and continuous time as candidate models for asset prices and return dynamics. Convergence concepts are presented as applied to the problem of point estimation of means, variances, correlation coefficients and risk measures. Short sections on risk and copula functions, further illustrate the potential application of probability models to financial problems. The second part of the book can be accessed by those students with more mathematical preparation. All the relevant proofs of results which are only stated in the first part and some advanced exercises with complete solutions are presented. .
650 0 _aProbabilities.
_965724
650 0 _aStatistics.
_965982
650 1 4 _aProbability Theory.
_967428
650 2 4 _aStatistical Theory and Methods.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031546877
776 0 8 _iPrinted edition:
_z9783031546891
830 0 _aLa Matematica per il 3+2,
_x2038-5757 ;
_v161
_970145
856 4 0 _uhttps://doi.org/10.1007/978-3-031-54688-4
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
999 _c61727
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