Dynamics of Markets

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Product Description

This second edition presents the advances made in finance market analysis since 2005. The book provides a careful introduction to stochastic methods along with approximate ensembles for a single, historic time series. The new edition explains the history leading up to the biggest economic disaster of the 21st century. Empirical evidence for finance market instability under deregulation is given, together with a history of the explosion of the US Dollar worldwide. A model shows how bounds set by a central bank stabilized FX in the gold standard era, illustrating the effect of regulations. The book presents economic and finance theory thoroughly and critically, including rational expectations, cointegration and arch/garch methods, and replaces several of those misconceptions by empirically based ideas. This book will be of interest to finance theorists, traders, economists, physicists and engineers, and leads the reader to the frontier of research in time series analysis.

Dynamics of Markets Review

This is an excelent critical analysis of (financial) economics. It suggests a scientific attitude towards financial markets that has the potential of providing deeper insights into the nature of economy and money with applications to financial engineering. The mathematical similarities between physics and finance are also exploited towards future progress. Some deficiencies:

(1) Discussions are at points sketchy and inaccurate. The text needs more work and elaboration for those not deep into this material. This feature of sketchy expositions has definitely damaged the popularity of the book and the included important ideas.

(2) The author misrepresents mathematics research in many cases. For example he speaks of mathematicians and mathematics as if the latter does not include the branch of mathematical modeling. Mathematical modeling indicates clearly the scientific character of mathematics since it discovers new mathematical facts by empirical observation of the "real" world. Certainly,
a mathematical model is not postulatory in nature but starts from the data. This mode of mathematical thinking is ignored in the text.

(3) The same problem as in (2) also appears in his critique of elaborated mathematical analysis of classical economic models. He seems to consider it almost a luxury. Quite the opposite, a deep mathematical analysis is always welcome since it can help you see that new ad-hoc mathematical models might already be (unsuspected) consequences of previous ones. Economics has enormously benefitted by rigorous mathematical analysis, and the latter is not inconsistent with paying emphasis on the empirical value of a mathematical model.

Overall an excelent work that despite some deficiencies ought to be read by all mathematically inclined people in finance.

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