Extreme Value Methods with Applications to Finance

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A01=Serguei Y. Novak
Assume Conditions
Author_Serguei Y. Novak
Berry Esseen Inequality
Borel Cantelli Lemma
Borel Set
Category=KCH
Category=PBT
Compound Poisson Process
convergence
CP
CP Approximation
Daily Log Returns
Distribution Functions
Distribution of Extremes
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Excess Process
Extreme Quantiles
heavy tail analysis
independent
index
Inference on Heavy Tails
Methods of Extreme Value Theory
Multiplicity Distribution
nonparametric estimation
Normal Approximation
Point Process
Poisson Point Process
probability theory
random
Recurrent Inequalities
risk modeling
sequence
stationary
Stationary Sequence
stationary sequence extremes
Statistics of Extremes
stein
Stein Method
stochastic processes
tail
Tail Index
Tail Index Estimation
Tail Index Estimators
tail probability estimation
Taylor's Formula
Taylor’s Formula
Total Variation Distance
USD Exchange Rate
variable
weak
Weak Convergence
Weekly Log Returns

Product details

  • ISBN 9781439835746
  • Weight: 680g
  • Dimensions: 156 x 234mm
  • Publication Date: 20 Dec 2011
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Extreme value theory (EVT) deals with extreme (rare) events, which are sometimes reported as outliers. Certain textbooks encourage readers to remove outliers—in other words, to correct reality if it does not fit the model. Recognizing that any model is only an approximation of reality, statisticians are eager to extract information about unknown distribution making as few assumptions as possible.

Extreme Value Methods with Applications to Finance concentrates on modern topics in EVT, such as processes of exceedances, compound Poisson approximation, Poisson cluster approximation, and nonparametric estimation methods. These topics have not been fully focused on in other books on extremes. In addition, the book covers:

  • Extremes in samples of random size
  • Methods of estimating extreme quantiles and tail probabilities
  • Self-normalized sums of random variables
  • Measures of market risk

Along with examples from finance and insurance to illustrate the methods, Extreme Value Methods with Applications to Finance includes over 200 exercises, making it useful as a reference book, self-study tool, or comprehensive course text.

A systematic background to a rapidly growing branch of modern Probability and Statistics: extreme value theory for stationary sequences of random variables.

Dr S.Y. Novak earned his Ph.D. at the Novosibirsk Institute of Mathematics under the supervision of Dr S.A. Utev in 1988. The Novosibirsk group forms a part of Russian tradition in Probability & Statistics that extends its roots to Kolmogorov and Markov.

Dr S.Y. Novak began his teaching carrier at the Novosibirsk Electrotechnical Institute (NETI) and Novosibirsk Institute of Geodesy, held post-doctoral positions at the University of Sussex and Eurandom (Technical University of Eindhoven), and taught at Brunel University in West London, before joining the Middlesex University (London) in 2003. He published over 40 papers, mostly on the topic of Extreme Value Theory, in which he is considered an expert.

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