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Books > Business & Economics > Finance & accounting > Finance
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Optimal Statistical Inference in Financial Engineering (Hardcover, New)
Loot Price: R4,952
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Optimal Statistical Inference in Financial Engineering (Hardcover, New)
Expected to ship within 12 - 19 working days
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Until now, few systematic studies of optimal statistical inference
for stochastic processes had existed in the financial engineering
literature, even though this idea is fundamental to the field.
Balancing statistical theory with data analysis, Optimal
Statistical Inference in Financial Engineering examines how
stochastic models can effectively describe actual financial data
and illustrates how to properly estimate the proposed models. After
explaining the elements of probability and statistical inference
for independent observations, the book discusses the testing
hypothesis and discriminant analysis for independent observations.
It then explores stochastic processes, many famous time series
models, their asymptotically optimal inference, and the problem of
prediction, followed by a chapter on statistical financial
engineering that addresses option pricing theory, the statistical
estimation for portfolio coefficients, and value-at-risk (VaR)
problems via residual empirical return processes. The final
chapters present some models for interest rates and discount bonds,
discuss their no-arbitrage pricing theory, investigate problems of
credit rating, and illustrate the clustering of stock returns in
both the New York and Tokyo Stock Exchanges. Basing results on a
modern, unified optimal inference approach for various time series
models, this reference underlines the importance of stochastic
models in the area of financial engineering.
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