Multifractality in Asset Returns: Theory and Evidence

By Laurent E. Calvet, Adlai J. Fisher. Review of Economics and Statistics, 2002

358 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/f601470b43205083b5dca74799d14c53ba7990b7

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Citations in the corpus

Volatility Forecasting With Range-Based EGARCH Models (2006, background): “Studies such as those of Baillie, Bollerslev, and Mikkelsen (1996), Andersen et al. (2001), and Calvet and Fisher (2002) have documented strong evidence for long memory in volatility.”
The Markov-Switching Multifractal Model of Asset Returns (2008, methodology): “We tried model comparisons along the line of the SMM approach in Calvet and Fisher (2002b) combining the minimized moment functions with simulated weighting matrices for varying numbers k′, but results were practically constant across all choices of k and k′ beyond some threshold.”
Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility (2003, neutral): “…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).”
The Volatility of Realized Volatility (2005, methodology): “In addition, other approaches for reproducing long-memory dependence, such as the multifractals and cascade models of Calvet and Fisher ( 2002 , 2004 ) and Mandelbrot et al.”
The Levered Equity Risk Premium and Credit Spreads: A Unified Framework (2010, background): “…empirical evidence combined with that in Bansal and Yaron (2004) suggests that the drifts and volatilities of macroeconomic fundamentals contain different components, which revert to their means at different speeds (see, e.g. Calvet and Fisher (2002) for evidence of such behavior in asset returns).”
The multi-fractal model of asset returns: Its estimation via GMM and its use for volatility forecasting (2003, methodology): “To see the similarity to the model analyzed in Mandelbrot, Calvet and Fisher (1997) and Calvet and Fisher (2002a), we compute the unconditional moments of the resulting process.”
Variation, jumps, market frictions and high frequency data in financial econometrics (2005, neutral): “This relates to the work of, for example, Calvet and Fisher (2002) on multifractals.”
Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching (2007, methodology): “While this model had been shown to generate scaling behaviour of moments in accordance with empirical observations (Calvet and Fisher, 2002), its attractiveness for applied research had been limited due to the combinatorial nature of the underlying multifractal time transformation and the…”
Multi-scaling in finance (2007, methodology): “A stochastic process fXðtÞg is called multi-scaling if it has stationary increments and satisfies (Calvet and Fisher 2002)”
Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series (2011, background): “The search for scaling behaviors in financial markets is nowadays a very rich discipline [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] where the growing amount of empirical data is continuously advancing the understanding of markets behaviors.”
Volatility in Equilibrium: Asymmetries and Dynamic Dependencies (2009, positive): “In particular, on assuming that the dividend growth volatility follows a multifractal process, as in Calvet and Fisher (2002), along with an EpsteinZin-Weil type representative agent, as in the model developed here, the equilibrium models in Calvet and Fisher (2007, 2008) are also able to generate…”