內容簡介
This book is a second edition of the book of the same title by the first authorwhich was published in 2000. The subject of ruin probabilities and related top- ics has since then undergone a considerable development, not to say boom. This much expanded and revised second edition aims at covering a substantial part of these developments as well as the classical topics.
R,isk theory in general and ruin probabilities in particular are traditionally considered as part of insurance mathematics, and has been an active area of research from the days of Lundberg all the way up to today. One reason for writing tlus book is a feeling that the area has in recent years achieved a con-siderable mathematical maturity, which has in particular removed one of the standard criticisms of the area, namely that it can only say something about very simple models and questions. Although in insurance practice, usually sim- pler (and coarser) risk measures like Value-at-Risk are used, it is widely believed that the thinking advocated by ruin theory is still important for modern risk management. For instance, in times of market-consistent valuation principles, the role of the time diversification effect of insurance portfolios, which is one of the core elements of ruin theory, should not be forgotten. In addition, ruin the- ory has fruitful methodological links and applications to other fields of applied probability, like queueing theory and mathematical finance (pricing of barrier options, credit products etc.). Apart from these remarks, we have deliberately stayed away from discussing the practical relevance of the theory; if the formu- lations occasionally give a different impression, it is not by intention. Thus, the book is basically mathematical in its flavor.
內頁插圖
目錄
Preface
Notation and conventions
Ⅰ Introduction
1 The risk process
2 Claim size distributions
3 The arrival process
4 A summary of main results and methods
Ⅱ Martingales and simple ruin calculations
1 Wald martingales
2 Gambler's ruin.Two-sided ruin.Brownian motion
3 Further simple martingale calculations
4 More advanced martingales
Ⅲ Further general tools and results
1 Likelihood ratios and change of measure
2 Duality with other applied probability models
3 Random walks in discrete or continuous time
4 Markov additive processes
5 The ladder height distribution
Ⅳ The compound Poisson model
1 Introduction
2 The Pollaczeck-Khinchine formula
3 Special cases of the Pollaczeck-Khinchine formula
4 Change of measure via exponential families
5 Lundberg conjugation
6 Further topics related to the adjustment coefficient
7 Various approximations for the ruin probability
8 Comparing the risks of different claim size distributions
9 Sensitivity estimates
10 Estimation of the adjustment coefficient
Ⅴ The probability of ruin within finite time
1 Exponential claims
2 The ruin probability with no initial reserve
3 Laplace transforms
4 When does ruin occur?
5 Diffusion approximations
6 Corrected diffusion approximations
7 How does ruin occur?
Ⅵ Renewal arrivals
1 Introduction
2 Exponential claims.The compound Poisson model with negative claims
3 Change of measure via exponential families
4 The duality with queueing theory
Ⅶ Risk theory in a Markovian environment
1 Model and examples
2 The ladder height distribution
3 Change of measure via exponential families
4 Comparisons with the compound Poisson model
5 The Markovian arrival process
6 Risk theory in a periodic environment
7 Dual queueing models
Ⅷ Level-dependent risk processes
1 Introduction
2 The model with constant interest
3 The local adjustment coefficient.Logarithmic asymptotics
4 The model with tax
5 Discrete-time ruin problems with stochastic investment
6 Continuous-time ruin problems with stochastic investment
Ⅸ Matrix-analytic methods
1 Definition and basic properties of phase-type distributions
2 Renewal theory
3 The compound Poisson model
4 The renewal model
5 Markov-modulated input
6 Matrix-exponential distributions
7 Reserve-dependent premiums
8 Erlangization for the finite horizon case
Ⅹ Ruin probabilities in the presence of heavy tails
1 Subexponential distributions
2 The compound Poisson model
3 The renewal model
4 Finite-horizon ruin probabilities
5 Reserve-dependent premiums
6 Tail estimation
Ⅺ Ruin probabilities for Levy processes
1 Preliminaries
2 One-sided ruin theory
3 The scale function and two-sided ruin problems
4 Further topics
5 The scale function for two-sided phase-type jumps
Ⅻ Gerber-Shiu functions
1 Introduction
2 The compound Poisson model
3 The renewal model
4 Levy risk models
ⅩⅢ Further models with dependence
1 Large deviations
2 Heavy-tailed risk models with dependent input
3 Linear models
4 Risk processes with shot-noise Cox intensities
5 Causal dependency models
6 Dependent Sparre Andersen models
7 Gaussian models.Fractional Brownian motion
8 Ordering ofruin probabilities
9 Multi-dimensional risk processes
ⅩⅣ Stochastic control
1 Introduction
2 Stochastic dynamic programming
3 The Hamilton-Jacobi-Bellman equation
ⅩⅤ Simulation methodology
1 Generalities
2 Simulation via the Pollaczeck-Khinchine formula
3 Static importance sampling via Lundberg conjugation
4 Static importance sampling for the finite horizon case
5 Dynamic importance sampling
6 Regenerative simulation
7 Sensitivity analysis
ⅩⅥ Miscellaneous topics
1 More on discrete-time risk models
2 The distribution of the aggregate claims
3 Principles for premium calculation
4 Reinsurance
Appendix
A1 Renewal theory
A2 Wiener-Hopf factorization
A3 Matrix-exponentials
A4 Some linear algebra
A5 Complements on phase-type distributions
A6 Tauberian theorems
Bibliography
Index
前言/序言
風險的邊界:現代金融與保險中的不確定性管理 內容提要: 本書深入探討瞭現代金融、保險及其他高風險行業中,理解、量化和管理不確定性所必需的理論基礎、分析工具和實踐應用。它超越瞭傳統的風險度量模型,聚焦於在極端不利情景下係統性崩潰的可能性,以及如何構建更具韌性的操作框架。全書結構嚴謹,從概率論和隨機過程的基本原理齣發,逐步過渡到復雜的衍生品定價、信用風險建模、操作風險管理,以及宏觀經濟衝擊下的金融穩定分析。 --- 第一部分:不確定性與隨機過程的基礎重述 本部分旨在為讀者構建理解復雜風險現象所需的數學和統計學基石。我們不局限於經典的正態分布假設,而是將重點放在分布的“厚尾”特性和跳躍過程的建模上,這些特性在金融時間序列中錶現得尤為突齣。 第一章:概率論的重新審視:從精確到近似 本章首先迴顧瞭概率論的核心概念,如隨機變量、期望值和方差的定義。然而,重點迅速轉嚮對極端事件(尾部風險)的關注。我們將探討極值理論(Extreme Value Theory, EVT)在金融危機分析中的應用,包括 Block Maxima 和 Peaks Over Threshold 方法。詳細討論瞭非對稱分布(如偏度和峰度)對風險估計的影響,並引入瞭更適閤描述市場劇烈波動的非高斯模型,例如 $alpha$-穩定分布的初步概念。 第二章:隨機過程的動態視角 理解風險隨時間演變至關重要。本章係統介紹瞭描述連續時間隨機現象的關鍵工具。布朗運動(Wiener 過程)作為最基礎的連續時間模型被深入分析,探討其路徑依賴性和非可預測性。在此基礎上,我們引入瞭復閤泊鬆過程(Compound Poisson Process)來模擬資産價格或索賠事件的離散、隨機到達,及其對纍積損失的影響。更進一步,本章詳細講解瞭伊藤積分(Itô Calculus)的基本規則及其在描述資産價格隨機微分方程(SDEs)中的核心地位,為後續的衍生品定價和動態資産負債管理奠定理論基礎。 第二部分:信用、違約與係統性壓力分析 金融機構麵臨的最大風險之一是交易對手方無法履行閤約義務。本部分聚焦於對這種信用風險的量化和建模。 第三章:違約建模的進化:從結構到簡約 信用風險建模的演變是本部分的核心。我們首先分析瞭 Merton 的結構模型,該模型將公司股權視為一種看漲期權,並探討瞭該模型在實踐中的局限性,特彆是關於違約時間點和資産波動率的假設。隨後,轉嚮更具操作性的簡約模型,重點分析瞭 Jarrow-Turnbull 框架,該框架利用瞭信用違約互換(CDS)的市場價格來校準違約強度(Intensity Rate)。強度過程的建模是關鍵,我們探討瞭如 Vasicek 或 Hull-White 模型在描述利率和信用強度動態相關性方麵的應用。 第四章:相關性、傳染與多違約分析 在復雜的金融網絡中,單個違約事件可能引發連鎖反應。本章深入探討瞭信用風險中的相關性問題。我們詳細分析瞭經典的 Copula 函數族(如 Gaussian Copula、t-Copula),它們在構建多變量違約模型中扮演的角色,特彆是用於估算投資組閤層麵尾部風險的聚閤作用。此外,本章還引入瞭網絡理論中的傳染模型,用於模擬一個機構的失敗如何通過其資産負債錶連接傳遞至其他參與者,評估“大而不倒”的機構在係統中的潛在影響。 第三部分:保險數學與巨災風險管理 本部分將視角轉嚮保險業,核心關注巨額、不定期索賠的積纍與管理,特彆是當索賠頻率和規模受外部衝擊影響時。 第五章:索賠過程的積纍與重塑 保險負債的估計依賴於對未來索賠到達和嚴重程度的準確預測。本章重新審視瞭破産風險模型的核心要素:索賠到達過程和單個索賠的分布。重點分析瞭如何利用精算學中的生存分析(Survival Analysis)技術來建模投保人生命周期中的事件發生概率。在損失嚴重性(Severity)方麵,除瞭傳統的伽馬或韋布爾分布外,本章詳細討論瞭帶有厚尾特徵的分布(如帕纍托分布)如何影響重置成本和巨災賠付的估計。 第六章:重保險、再保險與資本配置的優化 風險管理在保險領域體現為資本的有效配置。本章探討瞭再保險機製作為轉移極端風險的工具。從比例再保險(Proportional Reinsurance)到超額損失再保險(Excess of Loss Reinsurance)的結構和定價被詳細解析。在此基礎上,我們將現代資本模型(如基於風險價值 Value-at-Risk 或預期虧空 Expected Shortfall 的度量)應用於確定最優的風險轉移比例,以最小化資本成本的同時,滿足監管機構設定的償付能力要求。 第四部:衍生品定價與動態對衝的局限性 金融衍生品市場是高杠杆和不確定性的交匯點。本部分考察瞭經典定價模型(如 Black-Scholes-Merton)的假設在現實市場中的失效,以及如何應對這些失效。 第七章:跳躍擴散與隨機波動率 經典 Black-Scholes 模型在平滑的、連續的資産價格變動假設下運行良好,但現實中市場波動往往伴隨著突發性的、劇烈的價格跳躍。本章引入瞭包含跳躍項的擴散模型(如 Kou 模型或 Merton 的跳躍擴散模型),用以更真實地描述期權價格隨時間的動態。隨後,我們轉嚮隨機波動率模型(Stochastic Volatility Models),如 Heston 模型,探討波動率本身作為一種隨機過程如何影響期權微笑(Volatility Smile)的形成和演變,以及它對 Delta 對衝策略的深刻影響。 第八章:模型風險與對衝的有效邊界 動態對衝(如 Delta 對衝)的有效性依賴於模型對底層資産路徑的準確預測。本章的核心議題是“模型風險”——即所使用的數學模型與真實市場結構不匹配所帶來的風險。我們將分析當市場波動率不是常數、利率也存在隨機性時,傳統對衝策略的失效點。討論瞭高頻交易中的滑點(Slippage)和流動性風險如何侵蝕對衝收益,以及如何在存在模型不確定性的情況下,設定對衝策略的“安全邊際”。 --- 結論:麵嚮韌性的風險框架 本書的結論部分強調,在理解瞭這些復雜的數學工具和模型之後,真正的挑戰在於如何將這些理論轉化為具有韌性的決策框架。這要求管理者超越單一風險指標的限製,采納情景分析、壓力測試和反脆弱性設計(Antifragility Design)的理念,以準備好應對那些傳統模型認為“不可能”發生的極端事件。本書為從業者和研究人員提供瞭一個全麵且深入的工具箱,以在日益復雜和相互關聯的全球風險環境中做齣更明智的決策。