Realistic Statistical Modelling of Financial Data

By Tina Hviid Rydberg. 2000

120 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/b69c9017aca4ba28f764839baa2ed64fb3f86f15

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Citations in the corpus

Hyperbolic Processes in Finance (2003, methodology): “The well established features of nancial data are for instance reviewed in Barndor-Nielsen (1998) and Rydberg (2000) .”
Recent Advances in ARCH Modelling (2007, unknown): “For statistical and econometric aspects of ARCH modelling, see the surveys of Bollerslev et al. (1992), Shephard (1996), Bera and Higgins (1993), Bollerslev et al. (1994); for specific features of modelling the financial data, including ARCH, see Pagan (1996), Rydberg (2000), Mikosch (2003).”
ESTIMATION FOR A NONSTATIONARY SEMI-STRONG GARCH(1,1) MODEL WITH HEAVY-TAILED ERRORS (2009, methodology): “Since the seminal work of Engle (1982), ARCH/GARCH models have been widely used in finance and economics (see Shephard, 1996; Rydberg, 2000).”
The Normal-Laplace Distribution and Its Relatives (2006, background): “Exactly this sort of behaviour has been observed in various studies on high-frequency financial data (e.g. Rydberg, 2000) -very little kurtosis in the distribution of logarithmic returns over long intervals but increasingly fat tails as the reporting interval is shortened.”
Direct Estimation of Equity Market Impact (2005, background): “But the distribution is extremely fat-tailed, as is normal for returns distributions on short time intervals (Rydberg (2000) has a nice illustration), and hence does not indicate that the model is poorly specified.”
Estimating value-at-risk: a point process approach (2005, background): “The quasi-long-range dependence structure that can be shown in an ACF representation of the squared returns of the original data over the entire period of study—a stylized fact discussed, for example, in Rydberg (2000)—does not appear in the ACF of the squared residuals.”
Using local Gaussian correlation in a nonlinear re-examination of financial contagion (2014, methodology): “We have only considered bivariate problems here, but a multivariate extension is possible under certain simplifying assumptions, as outlined in Støve et al. (2012). As a final point, we mention that contagion, in general and as we have defined it, implies in fact a causal statement: The cross-market”