By Luc Bauwens, Winfried Pohlmeier, David Veredas
This intriguing quantity offers state-of-the-art advancements in excessive frequency monetary econometrics, spanning a various diversity of issues: industry microstructure, tick-by-tick information, bond and foreign currency echange markets and massive dimensional volatility modelling. The chapters on industry microstructure care for liquidity, asymmetries of data, and restrict order aggressiveness in natural restrict order e-book markets. The chapters on tick-by-tick info current statistical strategies for the research of the discrete nature of fee routine, the intraday seasonal styles of monetary periods, and the joint chance legislations of costs, quantity and periods. Bond markets are introduced into concentration throughout the research of macroeconomic bulletins sooner or later bond industry as a functionality of the enterprise cycle. alternate markets are tested from views: the learn of the effect of data arrival on trade cost volatility and the uncovering of chartist styles within the euro/dollar alternate fee. final, dynamic modelling of enormous dimensional covariance matrices can be offered. laying off mild on the most proper open questions within the research of excessive frequency facts, this quantity should be of curiosity to graduate scholars, researchers and professionals.
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Extra info for High Frequency Financial Econometrics: Recent Developments
The ﬁrst is the continuation method suggested by Stevens (1950) and Denuit and Lambert (2005), which is based upon generating artiﬁcially continued variables Y1t∗ , . . , Ynt∗ by adding independent random variables U1t , . . , Unt (each of them being uniformly distributed on the set [−1, 0]) to the discrete count variables Y1t , . . , Ynt and which does not change the concordance measure between the variables (Heinen and Rengifo (2003)). The second method, on which we rely, has been proposed by Meester and MacKay (1994) and Cameron et al.
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We thank Richard Olsen and Olsen Financial Technologies for providing us with the data. 48 K. Bien et al. References Amilon H (2003) GARCH estimation and discrete stock prices: an application to low-priced Australian stocks. Econ Lett 81(2):215–222 Andersen TG, Bollerslev T, Diebold FX, Labys P (1999) (Understanding, optimizing, using and forecasting) realized volatility and correlation, New York University, Leonard N. Stern School Finance Department Working Paper, No. 99–061 Antoniou A, Vorlow CE (2005) Price clustering and discreteness: is there chaos behind the noise?