Chapter 1. Introduction to Modelling Investment and Risk Decisions
Understand the role of modelling in financial and risk decisions, differentiate different types and models and identify the key steps of the implementation process for investment and risk models.
Chapter 2. Understanding Valuation Theory
Understand the key principles and elements of modern valuation theory which is the basis of modern pricing, risk and performance models
Chapter 3. Data Model Blue Prints for Investment & Risk
Understand the key elements of and principles behind the data models needed to represent the data required store the inputs, parameters and output of investment and risk models.
Chapter 4. Introduction to Practical Valuation
Understand the role of models in the valuation process. Identify the key elements of the implementation of modern valuation models. Understand the key steps of the implementation of such models and the valuation processes they support from research to finished model price and opinion.
Chapter 5. Implementing Valuation Models
Learn how to implement valuation models and valuation processes for common instruments including debt, equities and common derivatives step by step.
Chapter 6. Introduction to Practical Risk Modelling
Understand the role of models in the risk management process. Identify earlier risk models and their use. Understand the principles behind and key elements of Value at Risk and Expected Tail Loss models. Identify and understand the role of the key elements of the process for implementing risk modelling in practice.
Chapter 7. Implementing Risk Models
Learn how to implement VAR/ETL models and risk modelling processes using Historical Data, Parametric and Monte Carlo simulation approaches.
Chapter 8. Introduction to Practical Performance Measurement
Understand the role of models in the performance measurement process. Understand the principles behind and key elements of performance measurement models. Understand they key elements of the process for implementing performance measurement in practice.
Chapter 9. Implementing Performance Models
Learn how to implement performance measurement models step by step from construction of benchmarks to finished analysis.
How can managers increase their ability to calculate price and risk data for financial instruments while decreasing their dependence on a myriad of specific instrument variants? Wolfgang Schwerdt and Marcelle von Wendland created a simple and consistent way to handle and process large amounts of complex financial data. By means of a practical framework, their approach analyzes market and credit risk exposure of financial instruments and portfolios and calculates risk adjusted performance measures. Its emphasis on standardization yields significant improvements in speed and accuracy.
Schwerdt and von Wendland's focus on practical implementation directly addresses limitations imposed by the complex and costly processing time required for advanced risk management models and pricing hundreds of thousands of securities each day. Their many examples and programming codes demonstrate how to use standards to build financial instruments, how to price them, and how to measure the risk and performance of the portfolios that include them.
Feature: The authors have designed and implemented a standard for the description of financial instruments
Benefit: The reader can rely on accurate and valid information about describing financial instruments
Feature: The authors have developed an approach for pricing and analyzing any financial instrument using a limited set of atomic instruments
Benefit: The reader can use these instruments to define and set up even very large numbers of financial instruments.
Feature: The book builds a practical framework for analysing the market and credit risk exposure of financial instruments and portfolios
Benefit: Readers can use this framework today in their work and identify and measure market and credit risk using a reliable method.
Risk Managers, Portfolio Analysts, Financial Analysts, Business Analysts, Data Project Managers, Systems and Data Analysts and Developers. Secondary: Analysts at Financial Market Regulators such as Central Banks and Federal Reserve Bank, analysts at software vendors working with financial data
- No. of pages:
- © Academic Press 2010
- 16th October 2009
- Academic Press
- eBook ISBN:
- Hardcover ISBN:
Senior Data Quality Analyst, Optum Analytics
Vice President for FINCORE risk analystics, Finsoft Financial Systems, Ltd