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Because the field of financial engineering integrates multiple disciplines, it is important that stochastic models describe financial assets sufficiently. Optimal Statistical Inference in Financial Engineering provides an introduction to the optimal inference of financial engineering models and demonstrates how to properly estimate the proposed models. The book presents a wide range of illustrative examples along with numerous detailed real-world case studies, implemented with analyses using S-Plus and R. It also covers the fundamentals of statistical inference and probability and addresses such topics as time series analysis, term structure, and credit rating. |
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