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the pricing of financial derivatives, this book is ideal for you. You should be familiar with the basic programming concepts and C;
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with straightforward option pricing on binomial trees, the book gradually progresses towards more advanced topics, including nonlinear solvers;
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with straightforward option pricing on binomial trees, the book gradually progresses towards more advanced topics, including nonlinear solvers;
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with straightforward option pricing on binomial trees, the book gradually progresses towards more advanced topics, including nonlinear solvers;
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With more and more physicists and physics students exploring the possibility of utilizing their advanced math skills for a career;
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Quantitative Finance: An Object-Oriented Approach in C++ provides readers with a foundation in the key methods and models of quantitative;
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This is an advanced guide to optimal stopping and control, focusing on advanced Monte Carlo simulation and its application to finance;
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making sense of applying mathematics to investing decisions. With this complete guide, you'll gain a solid understanding of futures, options and;
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facilitate portfolio-wide risk assessment and regulatory calculations (like xVA). Complete with a professional scripting library written;
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This book provides readers with a systematic approach to quantitative investments and bridges the gap between theory and practice;
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This book provides readers with a systematic approach to quantitative investments and bridges the gap between theory and practice;
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). This book describes the state-of-the-art in quantitative and computational modelling of CDOs. Beginning with an overview of the structured;
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Quantitative equity portfolio management combines theories and advanced techniques from several disciplines, including financial economics;
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Quantitative Finance with R offers a winning strategy for devising expertly-crafted and workable trading models using the R open source;
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a tool to describe probabilistic phenomena. The level of familiarity with computer programming is kept to a minimum. To make the book;
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This Festschrift resulted from a workshop on Advanced Modelling in Mathematical Finance held in honour of Ernst Eberlein's 70th birthday;
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If you want to learn how to use R to build quantitative finance models with ease, this book is for you. Analysts who want to learn R to solve;
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modern financial economy. Practical examples and case studies provide the reader with a comprehensive introduction to the fundamentals of the;
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proven and new methodologies from finance, physics and engineering, along with years of industry and academic experience to provide a cookbook;
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Presents a multitude of topics relevant to the quantitative finance community by combining the best of the theory with the usefulness;
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. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples;
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. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples;
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Introductory Mathematical Analysis for Quantitative Finance is a textbook designed to enable students with little knowledge of mathematical;
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Introductory Mathematical Analysis for Quantitative Finance is a textbook designed to enable students with little knowledge of mathematical;
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business management. Its objective is to promote interaction between academic research in finance and accounting with applied research in the;
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University and Trinity University). Advances in Quantitative Analysis of Finance and Accounting, New Series (AQAFANS) is a continuation (with new;
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