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内容説明
This book is the definitive and most comprehensive guide to modeling derivatives in C++ today. Providing readers with not only the theory and math behind the models， as well as the fundamental concepts of financial engineering， but also actual robust object-oriented C++ code， this is a practical introduction to the most important derivative models used in practice today， including equity (standard and exotics including barrier， lookback， and Asian) and fixed income (bonds， caps， swaptions， swaps， credit) derivatives. The book provides complete C++ implementations for many of the most important derivatives and interest rate pricing models used on Wall Street including Hull-White， BDT， CIR， HJM， and LIBOR Market Model. London illustrates the practical and efficient implementations of these models in real-world situations and discusses the mathematical underpinnings and derivation of the models in a detailed yet accessible manner illustrated by many examples with numerical data as well as real market data. A companion CD contains quantitative libraries， tools， applications， and resources that will be of value to those doing quantitative programming and analysis in C++. Filled with practical advice and helpful tools， Modeling Derivatives in C++ will help readers succeed in understanding and implementing C++ when modeling all types of derivatives.
About the Author
Justin London is the Senior Quantitative Analyst at Bank of Montreal. London has analyzed and managed bank corporate loan portfolios using credit derivatives in the Investment Banking Group in Chicago， Illinois. A former quant developer， London developed fixed-income and equity models for trading companies and his own quantitative consulting firm. He wrote code and algorithms in C++/VC++ and Java to price and hedge various equity and fixed-income derivatives， building interest rate models including HJM， Hull-White， and LIBOR market models. In 1999， London founded Global Max Trading (GMT)， a global online trading and financial technology company. He has worked as a senior developer/consultant for technology companies like Compuware and taught business math and statistics courses at Oakland Community College as an adjunct professor in 2000. A graduate of the University of Michigan， London has five degrees， including a BA in economics and mathematics， an MA in applied economics， and MSs in financial engineering， computer science， and mathematics. London is working part time on his JD at The John Marshall Law School. He is also a frequent guest speaker at financial engineering programs and on Wall Street.