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News-Driven Expectations and Volatility Clustering [PDF]

Journal of Risk and Financial Management, 2020
Financial volatility obeys two fascinating empirical regularities that apply to various assets, on various markets, and on various time scales: it is fat-tailed (more precisely power-law distributed) and it tends to be clustered in time. Many interesting models have been proposed to account for these regularities, notably agent-based models, which ...
exaly   +5 more sources

Social interaction, volatility clustering, and momentum

Journal of Economic Behavior and Organization, 2022
Caterina Santi, Xue-Zhong He, Kai Li
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Multiscaling and clustering of volatility

Physica A: Statistical Mechanics and its Applications, 1999
Abstract The dynamics of prices in stock markets has been studied intensively both experimentally (data analysis) and theoretically (models). Nevertheless, while the distribution of returns of the most important indices is known to be a truncated Levy, the behaviour of volatility correlations is still poorly understood.
Pasquini M, SERVA, Maurizio
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Pricing VIX options with volatility clustering

Journal of Futures Markets, 2020
AbstractWe investigate the valuation of volatility index (VIX) options by developing a model with a self‐exciting Hawkes process that allows for clustering in the VIX. In the proposed framework, we find semianalytical expressions for the characteristic function and forward characteristic function, and then we solve the pricing problem of standard‐start
Yong Ma
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Asymmetric volatility, volatility clustering, and herding agents with a borrowing constraint

Physica A: Statistical Mechanics and Its Applications, 2010
Abstract Recent empirical research has documented asymmetric volatility and volatility clustering in stock markets. We conjecture that a limit of arbitrage due to a borrowing constraint and herding behavior by investors are related to these phenomena.
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Volatility clustering in monthly stock returns

Journal of Empirical Finance, 2003
We investigate volatility clustering using a modeling approach based on the temporal aggregation results for generalized autoregressive conditional heteroscedasticity (GARCH) models in Drost and Nijman [Econometrica 61 (1993) 909]. Our findings highlight that volatility clustering, contrary to widespread belief, is not only present in high-frequency ...
Ben Jacobsen
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Clustering of volatility in variable diffusion processes

Physica A: Statistical Mechanics and Its Applications, 2009
Abstract Increments in financial markets have anomalous statistical properties including fat-tailed distributions and volatility clustering (i.e., the autocorrelation functions of return increments decay quickly but those of the squared increments decay slowly).
Gemunu Gunaratne, Matthew Nicol, Lars Seemann   +2 more
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Contrarians and volatility clustering

Complex Syst., 1994
Summary: We introduce a new origin of volatility clustering in economic time series generated by systems of interacting adaptive agents. Each agent is assigned a random subset of a fixed collection of predictors. At every time step each agent generates an action based upon its assigned predictors.
E. R. Grannan, G. H. Swindle
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Herding behaviour and volatility clustering in financial markets

Quantitative Finance, 2017
We propose a financial market model in which speculators follow a linear mix of technical and fundamental trading rules to determine their orders. Volatility clustering arises in our model due to speculators’ herding behaviour. In case of heightened uncertainty, speculators observe other speculators’ actions more closely.
Westerhoff, Frank H., Schmitt, Noemi
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Structural attribution of observed volatility clustering

Journal of Econometrics, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Granger, Clive W. J., Machina, Mark J.
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