Forecasting Multifractal Volatility

By Laurent E. Calvet, Adlai J. Fisher. 2001

276 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/d2be61980dfe8fd3f8f7f98454f19b7e434163f3

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Citations in the corpus

Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching (2007, methodology): “These limitations have been overcome by the introduction of the closely related Markov-Switching Multifractal Model (MSM) in Calvet and Fisher (2001).”
The Levered Equity Risk Premium and Credit Spreads: A Unified Framework (2010, methodology): “One can overcome this restriction by modeling the time variation of drifts and volatilities via a multifrequency regime-switching process (see Calvet and Fisher (2001)).”
Multivariate stochastic volatility (2009, background): “Calvet, Fisher, and Thompson (2006) generalize the univariate Markov-switching multifractal (MSM) model proposed by Calvet and Fisher (2001) to the multivariate MSM and factor MSM models.”
Stochastic behavioral asset pricing models and the stylized facts (2008, methodology): “An example is the Markov-switching multifractal model introduced by Calvet and Fisher (2001) which has `long memory over a nite interval' that could be made arbitrarily long by appropriate choice of the speci cation.”
The Markov-Switching Multifractal Model of Asset Returns (2008, methodology): “Estimation of multifractal models has proceeded from adaption of the so-called “scaling estimator” in Calvet et al. (1997) for the combinatorial MMAR—which is still pervasively used in natural sciences—to the seminal proposal of maximum likelihood estimation for the discretized MSM in Calvet and Fis”
Multifrequency News and Stock Returns (2007, methodology): “Since MSM specifications with different k̄ are nonnested, we can assess significance in the log-likelihood differences using the Vuong (1989) test and a heteroskedasticity and autocorrelation consistent (HAC) version proposed in Calvet and Fisher (2004). For each sample and each value of k̄ 2 f1; .”
Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility (2003, unknown): “…others, along with the discussion of the related component GARCH model in Engle and Lee (1999), the corresponding multi-factor continuous time stochastic volatility model in Gallant, Hsu and Tauchen (1999), and the related multifractal regime switching models in Calvet and Fisher (2001, 2002).”
Multi-scaling in finance (2007, background): “…literature (Ding et al. 1993, Muzy et al. 1994, 2000, Ghashghaie et al. 1996, Mandelbrot et al. 1997, Arneodo et al. 1998, Mandelbrot 1999, Bacry et al. 2001, Calvet and Fisher 2001, Muzy and Bacry 2002, Lux 2003, 2004, 2006, Eisler and Kertesz 2004, Borland and Bouchaud 2005, Borland et al. 2005).”
Multifractality in Asset Returns: Theory and Evidence (2002, methodology): “Calvet and Fisher (2001) develop a likelihood-based filter under which b can be estimated for the class of multinomial multifractals.”
Bad Environments, Good Environments: A Non-Gaussian Asymmetric Volatility Model (2015, unknown): “Compared to Calvet and Fisher (2004), the persistence of the regimes is relatively low (low γ1).”
Stock price jumps: news and volume play a minor role (2008, background): “Many of these properties look very similar to endogenous noise generated by complex, non-linear systems with feedback, such as turbulent flows [5, 6, 7, 8, 9], stick balancing dynamics [10], etc.”