Multi-Asset Risk Modeling: Techniques for a Global Economy in an Electronic and Algorithmic Trading Era

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9780124016903: Multi-Asset Risk Modeling: Techniques for a Global Economy in an Electronic and Algorithmic Trading Era

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

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From the Back Cover:

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.

About the Author:

Professor Morton Glantz serves as a financial consultant, educator, and adviser to a broad spectrum of professionals, including corporate financial executives, government ministers, privatization managers, investment and commercial bankers, public accounting firms, members of merger and acquisition teams, strategic planning executives, management consultants, attorneys, and representatives of foreign governments and international banks. Professor Morton Glantz is a principal of Real Consulting and Real Options Valuation, firms specializing in risk consulting, training, certification, and advanced analytical software in the areas of risk quantification, analysis, and management solutions.

As a JP Morgan Chase (heritage bank) senior banker, Professor Glantz built a progressive career path specializing in credit analysis and credit risk management, risk grading systems, valuation models, and professional training. He was instrumental in the reorganization and development of the credit analysis module of the Bank’s Management Training Program-Finance, which at the time was recognized as one of the foremost training programs in the banking industry.

Professor Glantz is on the (adjunct) finance faculty of the Fordham Graduate School of Business. He has appeared in the Harvard University International Directory of Business and Management Scholars and Research, and has earned Fordham University Deans Award for Faculty Excellence on three occasions. He is a Board Member of the International Standards Board, International Institute of Professional Education and Research (IIPER). The IIPER is a global institute with partners and offices around the world, including the United States, Switzerland, Hong Kong, Mexico, Portugal, Singapore, Nigeria, and Malaysia. Professor Glantz is widely published in financial journals and has authored 8 books.

Dr. Robert Kissell is the president and founder of Kissell Research Group. He has over twenty years of experience specializing in economics, finance, math & statistics, risk, and sports modeling.

Dr. Kissell is author of the leading industry books, “The Science of Algorithmic Trading & Portfolio Management, (Elsevier, 2013), “Multi-Asset Risk Modeling (Elsevier, 2014), and “Optimal Trading Strategies, (AMACOM, 2003). He has published numerous research papers on trading, electronic algorithms, risk management, and best execution. His paper, “Dynamic Pre-Trade Models: Beyond the Black Box, (2011) won Institutional Investor’s prestigious paper of the year award.

Dr. Kissell is an adjunct faculty member of the Gabelli School of Business at Fordham University and is an associate editor of the Journal of Trading and the Journal of Index Investing. He has previously been an instructor at Cornell University in their graduate Financial Engineering program.

Dr. Kissell has worked with numerous Investment Banks throughout his career including UBS Securities where he was Executive Director of Execution Strategies and Portfolio Analysis, and at JPMorgan where he was Executive Director and Head of Quantitative Trading Strategies. He was previously at Citigroup/Smith Barney where he was Vice President of Quantitative Research, and at Instinet where he was Director of Trading Research. He began his career as an Economic Consultant at R.J. Rudden Associates specializing in energy, pricing, risk, and optimization.

During his college years, Dr. Kissell was a member of the Stony Brook Soccer Team and was Co-Captain in his Junior and Senior years. It was during this time as a student athlete where he began applying math and statistics to sports modeling problems. Many of the techniques discussed in “Optimal Sports Math, Statistics, and Fantasy were developed during his time at Stony Brook, and advanced thereafter. Thus, making this book the byproduct of decades of successful research.

Dr. Kissell has a Ph.D. in Economics from Fordham University, an MS in Applied Mathematics from Hofstra University, an MS in Business Management from Stony Brook University, and a BS in Applied Mathematics & Statistics from Stony Brook University.

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Book Description Elsevier Science Publishing Co Inc, United States, 2014. Hardback. Book Condition: New. Language: English . Brand New Book. 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. Bookseller Inventory # AA59780124016903

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