Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series
By Raffaello Morales, T. Di Matteo, Ruggero Gramatica, Tomaso Aste. 2011
145 citations recorded by the source corpus.
We investigate the use of the Hurst exponent, dynamically computed over a weighted moving time-window, to evaluate the level of stability/instability of financial firms. Financial firms bailed-out as a consequence of the 2007–2008 credit crisis show a neat increase with time of the generalized Hurst exponent in the period preceding the unfolding of the crisis. Conversely, firms belonging to other market sectors, which suffered the least throughout the crisis, show opposite behaviors. We find that the multifractality of the bailed-out firms increase at the crisis suggesting that the multi fractal properties of the time series are changing. These findings suggest the possibility of using the scaling behavior as a tool to track the level of stability of a firm. In this paper, we introduce a method to compute the generalized Hurst exponent which assigns larger weights to more recent events with respect to older ones. In this way large fluctuations in the remote past are less likely to influence the recent past. We also investigate the scaling associated with the tails of the log-returns distributions and compare this scaling with the scaling associated with the Hurst exponent, observing that the processes underlying the price dynamics of these firms are truly multi-scaling.
Subfields: Condensed Matter Physics, Economics and Econometrics, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/e967acb281a86e54145d93a4080e41c36d5bc2dc
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In Condensed Matter Physics
In Economics and Econometrics
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Citations in the corpus
- Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics (2020, methodology): “The closest method in the literature is a time-varying GHE using the EWMA [57].”
- Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates (2017, background): “In some papers, when estimating the Hurst exponents in a window, a bigger weight is given to the closer past [37], exactly as when computing an exponentially-weighted volatility.”