Order Flow, Transaction Clock, and Normality of Asset Returns

By Thierry Ané, Helyette Geman. 2000

413 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/0ff91c10479d351f401da81f21dd67ee438fde8b

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Citations in the corpus

Optimal portfolio allocation with higher moments (2007, background): “KURT− 3 = K(4)− 4K(3) + 6K(2)− 4K(1) (K(2)− 2K(1))2 v −1 (59)”
Flow Toxicity and Liquidity in a High-frequency World (2012, neutral): “1 See Clark [1973] or Ané and Geman [2000] for a primer on subordinated stochastic processes.”
Fact or friction: jumps at ultra high frequency (2014, neutral): “This sampling is standard in the literature and tends to homogenize the data in the common scenario in which the frequency of trade arrivals is correlated with volatility, i.e., heteroskedasticity is reduced through time deformation (Ane and Geman, 2000).”
A multivariate jump-driven financial asset model (2006, neutral): “…process is modelled by an non-decreasing process with stationary and independent increments, i.e. a subordinator (a special case of a Lévy process). yFor an extensive discussion of the economic interpretation of time change and its relationship with the market activity, see Geman and Ané (2000).”
A Gaussian approach for continuous time models of the short-term interest rate (2001, methodology): “It is based on the Gaussian estimation method developed by Bergstrom (1983, 1984,1985, 1986,1990) for linear systems. Since the general form of continuous time models of interest rates involve con ditional heteroscedasticity, however, the process is not Gaussian. So, in order to use Gaussian estimat”
Pure jump L'evy processes for asset price modeling (2002, positive): “(2001), Carr et al. (2002) on the other hand. We also show how that they are related to Brownian motion, a process which does exhibit both properties of normality and continuity mentioned. This relationship holds through a stochastic time change which is in fact a measure of the economic activity as”
Trading activity, realized volatility and jumps (2010, neutral): “Supportive evidence is given by Andersen (1996) who tests the MD model based on the microstructure framework of Glosten and Milgrom (1985), and by Ane and Geman (2000) who use high frequency data on actively traded stocks.”
Macroeconomic News, Announcements, and Stock Market Jump Intensity Dynamics (2011, positive): “Since changes in prices and volatility primarily occur through trades motivated for reasons of information, then the form of those responses can be related to the nature of the process of information arrival, as suggested in Clark (1973) and Ane and Geman (2000).1 Discontinuities in information flow”
Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns (2010, background): “1 The robustness of the empirical findings in Ane and Geman (2000) have recently been called into question by Gillemot et al. (2005) and Murphy and Izzeldin (2006).”
Realizing smiles: Options pricing with realized volatility (2013, positive): “In spite of this consideration, Clark (1973) and Ane and Geman (2000) theoretically argue that, for an underlying continuous-time diffusion process, the standard Gaussian distribution can be recovered rescaling the log-returns by an appropriate measure of”
Non-Gaussian OU based models and some of their uses in financial economics (2000, methodology): “Recent work on this topic includes the variance gamma model of Madan and Seneta (1990) (which is particularly notable as it uses a Lévy process as its subordinator) and that of Ghysels and Jasiak (1994), Conley, Hansen, Luttmer, and Scheinkman (1997) and Ané and Geman (2000). Subordination of Browni”
STOP-LOSS ORDERS AND PRICE CASCADES IN CURRENCY MARKETS (2002, background): “However, the aggregate face value of open orders is likely to be smaller, not larger, in the New York afternoon (Osler (2002)).”