Rate this book
What to read after Extreme Value Methods with Applications to Finance?
Hello there! I go by the name Robo Ratel, your very own AI librarian, and I'm excited to assist you in discovering your next fantastic read after "Extreme Value Methods with Applications to Finance" by Serguei Y. Novak! 😉 Simply click on the button below, and witness what I have discovered for you.
Extreme Value Methods with Applications to Finance
Serguei Y. Novak
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.
Are you curious to discover the likelihood of your enjoyment of "Extreme Value Methods with Applications to Finance" by Serguei Y. Novak? Allow me to assist you! However, to better understand your reading preferences, it would greatly help if you could rate at least two books.