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Nonlinear Modelling of High Frequency Financial Time Series (Hardcover)
Loot Price: R3,284
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Nonlinear Modelling of High Frequency Financial Time Series (Hardcover)
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Nonlinear Modelling of High Frequency Financial Time Series Edited
by Christian Dunis and Bin Zhou In the competitive and risky
environment of today's financial markets, daily prices and models
based upon low frequency price series data do not provide the level
of accuracy required by traders and a growing number of risk
managers. To improve results, more and more researchers and
practitioners are turning to high frequency data. Nonlinear
Modelling of High Frequency Financial Time Series presents the
latest developments and views of leading international researchers
and market practitioners, in modelling high frequency data in
finance. Combining both nonlinear modelling and intraday data for
financial markets, the editors provide a fascinating foray into
this extremely popular discipline. This book evolves around four
major themes. The first introductory section focuses on high
frequency financial data. The second part examines the exact nature
of the time series considered: several linearity tests are
presented and applied and their modelling implications assessed.
The third and fourth parts are dedicated to modelling and
forecasting these financial time series.
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