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Prebuilt Code for Modeling and Pricing Today’s Complex Derivatives
Justin London shows how to implement pricing algorithms for a wide variety of complex derivatives, including rapidly emerging instruments covered in no other book. Utilizing actual Bloomberg data, London covers credit derivatives, CDOs, mortgage-backed securities, asset-backed securities, fixed-income securities, and today’s increasingly important weather, power, and energy derivatives. His robust models are designed for both ease of use and ease of adaptation, and may be downloaded by the book’s purchasers from a secured Web site.
Modeling Derivatives Applications in Matlab, C++, and Excel will be indispensable to sell-side professionals who model derivatives; buy-side professionals who must understand the derivatives offered to them; experienced quants; developers at Wall Street firms; and any financial engineering practitioner or student entering the derivatives field for the first time.
The entire book utilizes Matlab, C++, and Excel. Users need Matlab installed, Visual C++, and Excel. In addition, some examples using Matlab toolkits are used: Chapter 1 makes use of the Fixed-Income Toolkit. Appendix A makes use of the Financial Derivatives Toolkit and Matlab Excel Link. These toolkits do not come with the book, but can be obtained from Mathworks.
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Justin London has developed fixed-income and equity models for trading companies and his own quantitative consulting firm. He has analyzed and managed bank corporate loan portfolios using credit derivatives in the Asset Portfolio Group of a large bank in Chicago, Illinois, as well as advised several banks in their implementation of derivative trading systems. London is the founder of a global online trading and financial technology company. A graduate of the University of Michigan, London holds a B.A. in economics and mathematics, an M.A. in applied economics, and an M.S. in financial engineering, computer science, and mathematics, respectively.
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