An application of extreme value theory in estimating liquidity risk

Muela, Sonia Benito; Martín, Carmen; Sanz, Raquel Arguedas

doi:10.1016/j.iedeen.2017.05.001

Cited by 13 publications

(13 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(iv) Muela et al (2017) observed that the GPD VaR is more conservative and accurate than uncorrected CF VaR in forecasts.…”

Section: Insights From a Review Of Advanced Semi-parametric Var-es Estimation Techniquesmentioning

confidence: 96%

“…Select empirical studies that belong to the first sub-strand include Bali andNeftci (2003), Brooks et al (2004), and Chan and Gray (2006), Ozun et al (2010), Ren and Giles (2010), Karmakar (2013), Chou and Wang (2014), Wijeyakulasuriya and Wickremasinghe (2015), Dahlen et al (2015), and Youssef et al (2015), Kellner and Rösch (2016), Muela et al (2017), Gkillas and Katsiampa (2018), and Liu et al (2018). Unlike majority of these studies, Ren and Giles (2010) and Dahlen et al (2015) did not employ the usual Hill scatterplots and the mean excess function to identify the threshold for extreme returns.…”

Section: Insights From a Review Of Advanced Semi-parametric Var-es Estimation Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Measurement of extreme market risk: Insights from a comprehensive literature review

Chakraborty

Chandrashekhar

Balasubramanian

2021

Cogent Economics & Finance

View full text Add to dashboard Cite

“…(iv) Muela et al (2017) observed that the GPD VaR is more conservative and accurate than uncorrected CF VaR in forecasts.…”

Section: Insights From a Review Of Advanced Semi-parametric Var-es Estimation Techniquesmentioning

confidence: 96%

Section: Insights From a Review Of Advanced Semi-parametric Var-es Estimation Techniquesmentioning

confidence: 99%

Measurement of extreme market risk: Insights from a comprehensive literature review

Chakraborty

Chandrashekhar

Balasubramanian

2021

Cogent Economics & Finance

View full text Add to dashboard Cite

“…Allaj (2017) presents a theoretical framework for incorporating of liquidity risk, arising from a bank's trading activities in securities, into the standard risk measures and discusses the VaR measure. Schmielewski (2010) and Muela, Martín, and Sanz (2017), use extreme value theory EVT by focusing on market liquidity risks. Bartetzky (2008) defines the liquidity risks in two dimensions: as the inability to pay risks as they come due and as LMT risks.…”

Section: Complying With the Regulatory Requirementsmentioning

confidence: 99%

Stress Testing of Liquidity Maturity Transformation Risk in Banks

Schmitt¹

2018

View full text Add to dashboard Cite

One of the main causes of the past crisis was the inability of financial institutions to acquire funding at appropriate costs. The importance of applying a good liquidity risk measurement system becomes apparent. The present paper provides an approach to the measurement of liquidity maturity transformation risk within a stress testing framework, for middle-sized banks. The costs of liquidity arising due to a downturn in refinancing conditions are calculated by using modern risk measures. The forward-looking way is based on a liquidity gap report, where the consideration of the counterbalancing capacity enables to gain an insight into the real liquidity needs. The measurement of both, the portfolio-value in the respective time bucket and liquidity costs, is possible. Applying the expected shortfall can easily be included into the calculation. The results show that by using historical simulation, if no sufficient data are available, expected shortfall delivers an approximate value. Still, it can serve as an indicator of insurance against extreme events. The present approach combines a scenario-based view to a possible distress with a quantitative risk measurement. Therewith, it contributes to the bank's wide stress testing as required by the regulatory authorities.

show abstract

“…Furthermore, in the context of VaR models, Daka and Basu (2016) provide evidence for the importance of liquidity risk in emerging markets from 2010 to 2014 and assess liquidity-adjusted LVaR based on CF expansion. Muela, Martín, and Sanz (2017) focus on modeling exogenous liquidity risk and show that extreme value theory (EVT) is superior to the standard approach on the basis of five selected equities for the period between 2000 and 2015. Further studies in the area of LVaR models can be found, among others, by Weiß and Supper (2013), Dionne et al (2015) and Gong et al (2017).…”

Section: Introductionmentioning

confidence: 99%

Assessing liquidity‐adjusted risk forecasts

Berger

Uffmann

2021

Journal of Forecasting

View full text Add to dashboard Cite

In this paper, we provide a thorough study on the relevance of liquidity-adjusted value-at-risk (LVaR) and expected shortfall (LES) forecasts. We measure additional liquidity of an asset via the difference between its respective bid and ask prices and we assess the non-normality of bid-ask spreads, especially in turbulent market times. The empirical assessment comprises German stocks in both calm and turmoil market times, and our results provide evidence that liquidity risk turns out to be crucial for the quality of regulatory risk assessment in turmoil market times. We find that a Cornish-Fisher approximation describes a sensible choice for LVaR forecasts whereas an extreme value approach results in adequate LES forecasts.

show abstract

An application of extreme value theory in estimating liquidity risk

Cited by 13 publications

References 10 publications

Measurement of extreme market risk: Insights from a comprehensive literature review

Measurement of extreme market risk: Insights from a comprehensive literature review

Stress Testing of Liquidity Maturity Transformation Risk in Banks

Assessing liquidity‐adjusted risk forecasts

Contact Info

Product

Resources

About