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The real world is perceived and broken down as data, models and
algorithms in the eyes of physicists and engineers. Data is noisy
by nature and classical statistical tools have so far been
successful in dealing with relatively smaller levels of randomness.
The recent emergence of Big Data and the required computing power
to analyse them have rendered classical tools outdated and
insufficient. Tools such as random matrix theory and the study of
large sample covariance matrices can efficiently process these big
data sets and help make sense of modern, deep learning algorithms.
Presenting an introductory calculus course for random matrices, the
book focusses on modern concepts in matrix theory, generalising the
standard concept of probabilistic independence to non-commuting
random variables. Concretely worked out examples and applications
to financial engineering and portfolio construction make this
unique book an essential tool for physicists, engineers, data
analysts, and economists.
Risk control and derivative pricing have become of major concern to
financial institutions, and there is a real need for adequate
statistical tools to measure and anticipate the amplitude of the
potential moves of the financial markets. Summarising theoretical
developments in the field, this 2003 second edition has been
substantially expanded. Additional chapters now cover stochastic
processes, Monte-Carlo methods, Black-Scholes theory, the theory of
the yield curve, and Minority Game. There are discussions on
aspects of data analysis, financial products, non-linear
correlations, and herding, feedback and agent based models. This
book has become a classic reference for graduate students and
researchers working in econophysics and mathematical finance, and
for quantitative analysts working on risk management, derivative
pricing and quantitative trading strategies.
Summarizing market data developments, some inspired by statistical physics, this book explains how to better predict the actual behavior of financial markets with respect to asset allocation, derivative pricing and hedging, and risk control. Risk control and derivative pricing are major concerns to financial institutions. The need for adequate statistical tools to measure and anticipate amplitude of potential moves of financial markets is clearly expressed, in particular for derivative markets. Classical theories, however, are based on assumptions leading to systematic (sometimes dramatic) underestimation of risks. First edition Hb (2000): 0-521-78232-5
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For the Kids CD (2002) (CD)
Various Artists; Contributions by Christopher Marc Potter, Craig Long, Ducky Carlisle, Geoff Sanoff, …
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R327
Discovery Miles 3 270
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Out of stock
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