Multi-Asset Risk Modeling
Techniques for a Global Economy in an Electronic and Algorithmic Trading Era
Business & Finance, Finance & Investing, Banks & Banking, Investments & Securities
| Author: | Morton Glantz, Robert L. Kissell | ISBN: | 9780124016941 |
| Publisher: | Elsevier Science | Publication: | December 3, 2013 |
| Imprint: | Academic Press | Language: | English |
| Author: | Morton Glantz, Robert L. Kissell |
| ISBN: | 9780124016941 |
| Publisher: | Elsevier Science |
| Publication: | December 3, 2013 |
| Imprint: | Academic Press |
| Language: | English |
Multi-Asset Risk Modeling describes, in a single volume, 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. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management.
- Covers all asset classes
- Provides mathematical theoretical explanations of risk as well as practical examples with empirical data
- Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities
Multi-Asset Risk Modeling describes, in a single volume, 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. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management.
- Covers all asset classes
- Provides mathematical theoretical explanations of risk as well as practical examples with empirical data
- Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities
