Multi-Asset Risk Modeling
Techniques for a Global Economy in an Electronic and Algorithmic Trading Era
By- Morton Glantz, Fordham Graduate School of Business, NY, NY
- Robert Kissell, Executive Director for analytics product intitiatives within UBS Direct Execution and UBS Portfolio Trading
This single volume describes the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. With mathematics playing a prominent role, the authors present standard risk-management and asset allocation models and more advanced extensions, discuss the laws in standard models that contributed to the 2008 financial crisis, and talk about current and future banking regulation. Importantly, they also explore algorithmic trading, which currently receives sparse attention in the literature. Their focus on practical issues and their ability to translate difficult risk management material into practice with insights into the difficulties of implementation and techniques for the required parameter estimation set their volume apart from others. By giving coherent recommendations about which statistical models to use for which asset class, they make a real contribution to the sciences of portfolio management and risk management.
Audience
Undergraduate and graduate students, professors, and professionals working with financial risk management techniques who want reference information about theoretical models and applications.
Hardbound, 352 Pages
Published: October 2013
Imprint: Academic Press
ISBN: 978-0-12-401690-3
Contents
- 1. Introduction to Multi-Asset Risk Modeling - Lessons from the Debt Crisis
2. A Primer on Risk Mathematics
3. A Primer on Quantitative Risk Analysis
4. Volatility Models
5. Factor Models
6. Equity Derivatives Volatility
7. FX Markets
8. Algorithmic Trading Risk
9. Risk Hedging Techniques
10. Ensuring Sustainability of an Institution as a Going Concern: An Approach to Dealing with Black Swan or Tail Risk 11. Rating Credit Risk: Current Practices, Design and Applications
12. Credit Risk and Credit Derivatives: Lessons from the Debt Crisis
13.Multi-Asset Corporate Restructurings and Valuations
Case Study
14. Case Study: Multi-Asset Class Investment Risk Management and Performance Attribution

