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Published in 2020 at "Empirical Economics"
DOI: 10.1007/s00181-020-01969-2
Abstract: Tails of the return distribution of an asset are informative about the (financial) risk behavior of that asset. Stochastic tail index (STI) models are designed to quantify riskiness by estimating a time-varying tail index from…
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Keywords:
high frequency;
estimation;
tail index;
tail ... See more keywords
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Published in 2019 at "Journal of the Korean Statistical Society"
DOI: 10.1016/j.jkss.2018.09.002
Abstract: Abstract In this paper, we reveal the relationship between the tail exponent introduced by Parzen (1979) and tail index for a distribution function. Furthermore, we analyze the domain of attraction of the weighted sum of…
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Keywords:
extreme quantiles;
tail index;
distribution;
index distribution ... See more keywords
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Published in 2017 at "Journal of Statistical Planning and Inference"
DOI: 10.1016/j.jspi.2016.08.010
Abstract: Abstract We construct a sequential monitoring procedure for changes in the tail index and extreme quantiles of β -mixing random variables, which can be based on a large class of tail index estimators. The assumptions…
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Keywords:
monitoring tail;
tail index;
sequential monitoring;
tail behavior ... See more keywords
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Published in 2019 at "Econometric Reviews"
DOI: 10.1080/07474938.2016.1224024
Abstract: ABSTRACT For a GARCH(1,1) sequence or an AR(1) model with ARCH(1) errors, one can estimate the tail index by solving an estimating equation with unknown parameters replaced by the quasi maximum likelihood estimation, and a…
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Keywords:
arch errors;
tail index;
model arch;
model ... See more keywords
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Published in 2019 at "Bernoulli"
DOI: 10.3150/18-bej1043
Abstract: Asymptotic theory of tail index estimation has been studied extensively in the frequentist literature on extreme values, but rarely in the Bayesian context. We investigate whether popular Bayesian kernel mixture models are able to support…
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Keywords:
tail index;
mixture models;
index;
bayesian kernel ... See more keywords