Markets liquidity risk under extremal dependence: Analysis with VaRs methods

Ourir, Awatef; Snoussi, Wafa

doi:10.1016/j.econmod.2012.05.036

Cited by 12 publications

(2 citation statements)

References 20 publications

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“…Moreover, the unpredictable financial environments tend to cause a structural change of cross-market dependence, which lead naturally to an application to time-varying copula functions (Patton, 2006). The liquidityrelated literature has concerned the impact of negligence of liquidity dependency in extreme risk assessment (Ourir and Snoussi, 2012), and then investigated determinants of aggregate liquidity (Hadhri and Ftiti, 2019) and evidences about "flight-to-liquidity" (Li et al, 2019) across markets. Nevertheless, there seems to be insufficient attention to liquidity dependence and to how it evolves in the general and/or extreme scenario.…”

Section: Literature Reviewmentioning

confidence: 99%

Liquidity of China’s agricultural futures market: measurement and cross-market dependence

Wang

et al. 2022

CAER

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PurposeThis paper aims to present the first empirical liquidity measurement of China’s agricultural futures markets and study time-varying liquidity dependence across markets.Design/methodology/approachBased on both high- and low-frequency trading data of soybean and corn, this paper evaluates short-term liquidity adjustment in Chinese agricultural futures market measured by liquidity benchmark and long-term liquidity development measured by liquidity proxies.FindingsBy constructing comparisons, the authors identify the seminal paper of Fong, Holden and Trzcinka (2017) as the best low-frequency liquidity proxy in China’s agricultural futures market and capture similar historical patterns of the liquidity in soybean and corn markets. The authors further employ Copula-generalized autoregressive conditional heteroskedasticity models to investigate liquidity dependence between soybean and corn futures markets. Results show that cross-market liquidity dependence tends to be dynamic and asymmetric (in upper versus lower tails). The liquidity dependence becomes stronger when these markets experience negative shocks than positive shocks, indicating a concern on the contagion effect of liquidity risk under negative financial situations.Originality/valueThe findings of this study provide useful information on the dynamic evolution of liquidity pattern and cross-market dependence of fastest-growing agricultural futures in the largest emerging economy.

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Section: Literature Reviewmentioning

confidence: 99%

Liquidity of China’s agricultural futures market: measurement and cross-market dependence

Wang

et al. 2022

CAER

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“…During the past few years, there have been tremendous efforts on measuring risk using value at risk (VaR) techniques. Ourir and Snoussi (2012) investigated the impact of negligence of dependency in liquidity extreme risk assessment of Tunisian stock market. They used returns dependency to evaluate market risk based on Time series-Extreme Value Theory combination.…”

Section: Introductionmentioning

confidence: 99%

Measuring liquidity risk in Social Security using VaR technique

Valahzaghard¹,

Tizfahmfard²

2013

msl

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Measuring liquidity risk plays an important role on any business unit especially financial organizations. Social security systems in most countries around the world are responsible to provide necessary requirements in many countries such as health care, pension plans, etc. Therefore, it is necessary to reduce any risk associated with these systems as much as possible. In this paper, we study liquidity risk in Iranian social security using VaR technique. The proposed model of this paper uses historical information for a fiscal year of 2008-2011. We first divide the information of each year into two groups of first and second half and using VaR technique analyzed whether there was any trend change in these two groups. The results of our survey indicate that the mean of VaR in the second half of the year is greater than the first half of the year. Therefore, we can confirm that VaR maintains an increasing trend over the time horizon. We also study the trend in liquidity using regression analysis for each year, separately and the results of our survey confirm that there was an increasing trend in liquidity over time.

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