Sensitivity analysis of Mixed Tempered Stable parameters with implications in portfolio optimization

Hitaj, Asmerilda; Mercuri, Lorenzo; Rroji, Edit

doi:10.1007/s10287-018-0306-0

Cited by 3 publications

(2 citation statements)

References 34 publications

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“…The multivariate mixed tempered stable (MMixedTS) distribution has been proposed in Hitaj et al (2018) and applied to portfolio selection in Hitaj et al (2019). This multivariate model is built on the basis of the standardized classical tempered stable (stdCTS) distribution.…”

Section: The Multivariate Mixed Ts Distributionmentioning

confidence: 99%

Multivariate non-Gaussian models for financial applications

Bianchi,

Hitaj,

Tassinari

2020

Preprint

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In this paper we consider several continuous-time multivariate non-Gaussian models applied to finance and proposed in the literature in the last years. We study the models focusing on the parsimony of the number of parameters, the properties of the dependence structure, and the computational tractability. For each model we analyze the main features, we provide the characteristic function, the marginal moments up to order four, the covariances and the correlations. Thus, we describe how to calibrate them on the time-series of log-returns with a view toward practical applications and possible numerical issues. To empirically compare these models, we conduct an analysis on a five-dimensional series of stock index log-returns.

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Section: The Multivariate Mixed Ts Distributionmentioning

confidence: 99%

Multivariate non-Gaussian models for financial applications

Bianchi,

Hitaj,

Tassinari

2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The employment of nonstandard probability distributions in financial risk theory represents a growing field of research, leading to either theoretical additions as well as relevant practical implications (see e.g. the monograph [20] and the recent contributions [16,19]). In this context, a relevant role is played by the Skew Normal distributions.…”

Section: Introductionmentioning

confidence: 99%