rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: A
    title: probability metrics approach to financial risk measures
  name:
    name part: Rachev, S. T. (Svetlozar Todorov)
    role:
      role term: creator
  name:
    name part: Stoyanov, Stoyan V.
  name:
    name part: Fabozzi, Frank J.
  name:
    name part: Wiley InterScience (Online service)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: enk
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xvi, 375 pages) : illustrations
  abstract: "A Probability Metrics Approach to Financial Risk Measures relates the field of probability metrics and risk measures to one another and applies them to finance for the first time. Helps to answer the question: which risk measure is best for a given problem? Finds new relations between existing classes of risk measures. Describes applications in finance and extends them where possible. Presents the theory of probability metrics in a more accessible form which would be appropriate for non-specialists in the field. Applications include optimal portfolio choice, risk theory, and numerical methods in finance. Topics requiring more mathematical rigor and detail are included in technical appendices to chapters."--Provided by publisher.
  abstract: "Is the behavior of the stocks in our portfolio close to their behavior during the most recent crisis? How close is the strategy of hedge fund A to the strategy of hedge fund B? In which proportions do we invest in a given universe of stocks so that the resulting portfolio matches as much as possible the strategy of fund C? All of these questions are essential to finance and they have one feature in common: measuring distances between random quantities. Problems of this kind have been explored for many years in areas other than finance. In A Probability Metrics Approach to Financial Risk Measures, the field of probability metrics and risk measures are related to one another and applied to finance for the first time, revealing groundbreaking new classes of risk measures, finding new relations between existing classes of risk measures, and providing answers to the question of which risk measure is best for a given problem. Applications include optimal portfolio choice, risk theory, and numerical methods in finance"--Provided by publisher.
  table of contents: Front Matter -- Introduction -- Probability Distances and Metrics -- Choice under Uncertainty -- A Classification of Probability Distances -- Risk and Uncertainty -- Average Value-at-Risk -- Computing AVaR through Monte Carlo -- Stochastic Dominance Revisited -- Index.
  table of contents: Machine generated contents note: Chapter 1 Introduction. -- 1.1 Probability metrics. -- 1.2 Applications in finance. -- Chapter 2 Probability distances and metrics. -- 2.1 Introduction. -- 2.2 Some examples of probability metrics. -- 2.2.1 Engineer's metric. -- 2.2.2 Uniform (or Kolmogorov) metric. -- 2.2.3 Levy metric. -- 2.2.4 Kantorovich metric. -- 2.2.5 Lp-metrics between distribution functions. -- 2.2.6 Ky Fan metrics. -- 2.2.7 Lp-metric. -- 2.3 Distance and semidistance spaces. -- 2.4 Definitions of probability distances and metrics. -- 2.5 Summary. -- 2.6 Technical appendix. -- 2.6.1 Universally measurable separable metric spaces. -- 2.6.2 The equivalence of the notions of p. (semi- )distance on P2 and on X. -- Chapter 3 Choice under uncertainty. -- 3.1 Introduction. -- 3.2 Expected utility theory. -- 3.2.1 St. Petersburg Paradox. -- 3.2.2 The von Neumann-Morgenstern expected utility theory. -- 3.2.3 Types of utility functions. -- 3.3 Stochastic dominance. -- 3.3.1 First-order stochastic dominance. -- 3.3.2 Second-order stochastic dominance. -- 3.3.3 Rothschild-Stiglitz stochastic dominance. -- 3.3.4 Third-order stochastic dominance. -- 3.3.5 Efficient sets and the portfolio choice problem. -- 3.3.6 Return versus payoff. -- 3.4 Probability metrics and stochastic dominance. -- 3.5 Cumulative Prospect Theory. -- 3.6 Summary. -- 3.7 Technical appendix. -- 3.7.1 The axioms of choice. -- 3.7.2 Stochastic dominance relations of order n. -- 3.7.3 Return versus payoff and stochastic dominance. -- 3.7.4 Other stochastic dominance relations. -- Chapter 4 A classification of probability distances. -- 4.1 Introduction. -- 4.2 Primary distances and primary metrics. -- 4.3 Simple distances and metrics. -- 4.4 Compound distances and moment functions. -- 4.5 Ideal probability metrics. -- 4.5.1 Interpretation and examples of ideal probability metrics. -- 4.5.2 Conditions for boundedness of ideal probability metrics. -- 4.6 Summary. -- 4.7 Technical appendix. -- 4.7.1 Examples…
  note: Svetlozar T. Rachev, Stoyan V. Stoyanov, Frank J. Fabozzi, CFA.
  note: Includes bibliographical references and index.
  subject:
    topic: Financial risk management
  subject:
    topic: Probabilities
  subject:
    topic: Financial risk management
  subject:
    topic: Probabilities
  classification: HD61 .R33 2011
  classification: 332.01/5192
  related item:
    title info:
      title: Probability metrics approach to financial risk measures
    name:
      name part: Rachev, S.T. (Svetlozar Todorov).
    origin info:
      publisher: Chichester, West Sussex, U.K. ; Malden, MA : Wiley-Blackwell, 2011
    identifier: (DLC) 2010040519
    identifier: (OCoLC)630507815
  identifier: 9781444392715
  identifier: 1444392719
  identifier: 9781405183697
  identifier: 1405183691
  identifier: 1283407981
  identifier: 9781283407984
  identifier: 9781444392692
  identifier: 1444392697
  identifier: 10.1002/9781444392715 Wiley InterScience
  identifier: https://doi.org/10.1002/9781444392715
  record info:
    record content source: DG1
    record creation date: 110609
    record change date: 20170124072407.9
    record identifier: ocn729731400
    language of cataloging:
      language term: eng