Online Public Access Catalogue (OPAC)
Library,Documentation and Information Science Division

“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


Image from Google Jackets

Bayesian risk management : a guide to model risk and sequential learning in financial markets / Matt Sekerke.

By: Material type: TextTextSeries: Wiley finance seriesPublication details: New Jersey : John Wiley & Sons, Inc., ©2015.Description: xiv, 219 p. : illustrations ; 24 cmISBN:
  • 9781118708606
Subject(s): DDC classification:
  • 000SB:332.0415 23 Se463
Contents:
1. Models for discontinuous markets -- Part I: Capturing uncertainty in statstical models -- 2. Prior knowledge, parameter uncertainty, and estimation -- 3. Model uncertainty -- Part II: Sequential learning with adaptive statistical models -- 4. Introduction to sequential modeling -- 5. Bayesian inference in state-space time series models -- 6. Sequential Monte Carlo inference -- Part III: Sequential models of financial risk -- 7. Volatility modeling -- 8. Asset-pricing models and hedging -- Part IV: Bayesian risk management -- 9. From risk measurement to risk management.
Summary: Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model–driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning–based methods, the framework presented here allows you to measure risk in a fully–Bayesian setting without losing the structure afforded by parametric risk and asset–pricing models.
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SB:332.0415 Se463 (Browse shelf(Opens below)) Available 137007
Total holds: 0

Includes bibliographical references and index.

1. Models for discontinuous markets --
Part I: Capturing uncertainty in statstical models --
2. Prior knowledge, parameter uncertainty, and estimation --
3. Model uncertainty --
Part II: Sequential learning with adaptive statistical models --
4. Introduction to sequential modeling --
5. Bayesian inference in state-space time series models --
6. Sequential Monte Carlo inference --
Part III: Sequential models of financial risk --
7. Volatility modeling --
8. Asset-pricing models and hedging --
Part IV: Bayesian risk management --
9. From risk measurement to risk management.

Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model–driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning–based methods, the framework presented here allows you to measure risk in a fully–Bayesian setting without losing the structure afforded by parametric risk and asset–pricing models.

There are no comments on this title.

to post a comment.
Library, Documentation and Information Science Division, Indian Statistical Institute, 203 B T Road, Kolkata 700108, INDIA
Phone no. 91-33-2575 2100, Fax no. 91-33-2578 1412, ksatpathy@isical.ac.in