Asymmetric power distribution: Theory and applications to risk measurement

By Ivana Komunjer. 2007

129 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/db7f2777577be2ded69a422a31ed16386977b2ff

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

Citations in the corpus

Frontiers in VaR forecasting and backtesting (2016, background): “Therefore, ES is likely to gain prominence in the future; see, for example, Wu and Xiao (2002), Yamai and Yoshiba (2005), Komunjer (2007), Chen (2008), Chen et al. (2012), Lönnbark (2013), Stoyanov et al. (2013), Brandtner (in press) and Xu (in press) for some recent references on forecasting ES.”
PADM2M: a penalized maximum likelihood model of the 0–2 Ma palaeomagnetic axial dipole moment (2011, methodology): “Numerous lacustrine records have been used in Holocene geomagnetic models (Korte et al. 2009), but we omit almost all these records from our collection because we already have good coverage from archaeomagnetic data with generally better age constraints. We primarily use marine cores which provide l”
Properties and Estimation of Asymmetric Exponential Power Distribution (2007, methodology): “By a method similar to that of Fernandez et al (1995), Theodossiou (2000) and Komunjer (2007), respectively, constructed seemingly di¤erent classes of SEPD, which are actually reparametrizations of that of Fernandez et al (1995).”
Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions (2011, methodology): “The special case in which p1 = p2 is equivalent to the skewed exponential power distributions given by Komunjer (2007), Theodossiou (1998) and Fernandez et al. (1995); for a detailed discussion see Zhu and Zinde-Walsh (2009).”
Comparing Sharpe ratios: So where are the p-values? (2007, methodology): “…0.5) is not shown to maintain graphical clarity, it is simulated in the study to test the robustness of the estimators, even though returns typically are negatively skewed (i.e., have a longer left tail – see Komunjer, 2006, Cajigas & Urga, 2005, and Cappiello et al., 2003 for just a few examples).”
Forecasting Value at Risk and Expected Shortfall Using a Semiparametric Approach Based on the Asymmetric Laplace Distribution (2019, methodology): “(4) The likelihood framework has led to useful developments for quantile regression, such as statistical inference via quasimaximum likelihood (see Komunjer 2005) and Bayesian quantile regression (see, e.g., Gerlach, Chen, and Chan 2011).”
Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression (2015, methodology): “In addition, Komunjer (2007) developed a parametric estimator for the risk of financial time series expected shortfall based on the asymmetric power distribution, derived the asymptotic distribution of the MLE, and constructed a consistent estimator for its asymptotic covariance matrix.”