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  • 保險和金融用的例外事件模型(英文版)
    該商品所屬分類:經濟 -> 經濟
    【市場價】
    1081-1568
    【優惠價】
    676-980
    【作者】 PEmbrechtsCKluppelbergTMikosch 
    【所屬類別】 圖書  經濟  保險圖書  管理  金融/投資  金融理論 
    【出版社】世界圖書出版公司 
    【ISBN】9787506259293
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    內容介紹



    紙張:膠版紙
    包裝:平裝
    是否套裝:否

    國際標準書號ISBN:9787506259293
    作者:P.Embrechts,C.Kluppelberg,T,Mikosch
    出版社:世界圖書出版公司

    出版時間:2003年06月 

        
        
    "

    內容簡介
    In a recent issue, The New Scientist ran a cover story under the title: "Mission improbable. How to predict the unpredictable"; see Matthews [448]. In it, the author describes a group of mathematicians who claim that extreme value theory (EVT) is capable of doing just that: predicting the occurrence of rare events, outside the range of available data. All members of this group, the three of us included, would immediately react with: "Yes, but, ...", or, "Be aware...". Rather than at this point trying to explain what EVT can and cannot do, we would like to quote two members of the group referred to in [448]. Richard Smith said, "There is always going to be an element of doubt, as one is extrapolating into areas one doesn't know about. But what EVT is doing is making the best use of whatever data you have about extreme phenomena." Quoting from Jonathan Tawn, "The key message .is that EVT cannot do magic - but it can do a whole lot better than empirical curvefitting and guesswork. My answer to the sceptics is that if people aren't given well-founded methods like EVT, they'll just use dubious ones instead."
    目錄
    Reader Guidelines
    1 Risk Theory
    1.1 The Ruin Problem
    1.2 The Cramer-Lundberg Estimate
    1.3 Ruin Theory for Heavy-Tailed Distributions
    1.3.1 Some Preliminary Results
    1.3.2 Cramer-Lundberg Theory for Subexponential Distributions
    1.3.3 The Total Claim Amount in the Subexponential Case
    1.4 Cramer-Lundberg Theory for Large Claims: a Discussion
    1.4.1 Some Related Classes of Heavy-Tailed Distributions
    1.4.2 The Heavy-Tailed Cramer-Lundberg Case Revisited
    2 Fluctuations of Sums
    2.1 The Laws of Large Numbers
    2.2 The Central Limit ProblemReader Guidelines
    1 Risk Theory
    1.1 The Ruin Problem
    1.2 The Cramer-Lundberg Estimate
    1.3 Ruin Theory for Heavy-Tailed Distributions
    1.3.1 Some Preliminary Results
    1.3.2 Cramer-Lundberg Theory for Subexponential Distributions
    1.3.3 The Total Claim Amount in the Subexponential Case
    1.4 Cramer-Lundberg Theory for Large Claims: a Discussion
    1.4.1 Some Related Classes of Heavy-Tailed Distributions
    1.4.2 The Heavy-Tailed Cramer-Lundberg Case Revisited
    2 Fluctuations of Sums
    2.1 The Laws of Large Numbers
    2.2 The Central Limit Problem
    2.3 Refinements of the CLT
    2.4 The Functional CLT: Brownian Motion Appears
    2.5 Random Sums
    2.5.1 General Randomly Indexed Sequences
    2.5.2 Renewal Counting Processes
    2.5.3 Random Sums Driven by Renewal Counting Processes
    3 Fluctuations of Maxima
    3.1 Limit Probabilities for Maxima
    3.2 Weak Convergence of Maxima Under Affine Tranformations
    3.3 Maximum Domains of Attracion and Norming Constants
    3.3.1 The Mazimum Domain of Attraction of the Frechet Distribution
    ……
    4 Fluctuations of Upper Order Statistics
    5 An Approach to Extremes via Point Processes
    6 Statistical Methods for Extremal Events
    7 Time Series Analysis for Heavy-Tailed Procces
    8 Special Topics
    Appendix
    References
    Index
    List of Abbreviations and Symbols


     
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