Sensitivity Analysis of VaR and CVaR | Sensitivity Analysis and Computational aspects of Value at Risk (VaR) and Conditional Value at Risk (CVaR)

Narendra Varma

ISBN 10: 3659180645 / ISBN 13: 9783659180644

Published by LAP LAMBERT Academic Publishing, 2012

About this Item

Sensitivity Analysis of VaR and CVaR | Sensitivity Analysis and Computational aspects of Value at Risk (VaR) and Conditional Value at Risk (CVaR) | Narendra Varma | Taschenbuch | 116 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659180644 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.

Seller Inventory # 106380658

Bibliographic Details

• Title: Sensitivity Analysis of VaR and CVaR | Sensitivity Analysis and Computational aspects of Value at Risk (VaR) and Conditional Value at Risk (CVaR)
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3659180645
• ISBN 13: 9783659180644
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 8D millimeters 220 millimeters width by 150 millimeters height by 8 millimeters depth
• Weight: 191 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Value at Risk (VaR) and conditional value at Risk (CVaR) are frequently used risk measures. Finding optimal portfolio using VaR or CVaR as a risk measure is computationally intensive especially when number of instruments and scenarios size is huge. This problem was analyzed and a computational efficient method, beating the industry's best methods, was proposed in this work. Parallel computing techniques were further applied to attain even higher computational efficiencies. Also models were built to find sensitivities in VaR and CVaR for different set of parameters like risk free interest rates on stocks, Market interest rates on bonds, volatilities in stocks and bonds and portfolio allocation weights. Illustrated ways to overcome limitations in finite difference methods to find sensitivities in VaR and CVaR. Finally an application of our work is presented using a portfolio of different types of options, bonds and stocks.

About the Author

Narendra completed his Master's in Industrial Engineering and Operations Research at Indian Institute of Technology - Bombay in 2009. Narendra is a certified financial risk manager (FRM) and is currently working in one of the leading financial services firm.