Understanding Commonality in Liquidity Around the World

By G. Karolyi, Kuan-Hui Lee, Mathijs A. Van Dijk. 2011

686 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/3a2194a07fd6680d8ac44fe9a881a2fb18fc175b

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Citations in the corpus

Understanding FX Liquidity (2015, methodology): “The stock market liquidity is based on the PCA across price impact proxies of the monthly Amihud (2002) measure (from Karolyi, Lee, and Dijk 2012), calculated as the value-weighted average of all individual stock in each country.”
Pair-Copula Constructions for Financial Applications: A Review (2016, background): “Studies on the commonality in liquidity have revealed clear empirical evidence for strong comovements in the bid-ask spreads of individual stocks; see, e.g., [88].”
The effects of uncertainty on market liquidity: Evidence from Hurricane Sandy (2019, positive): “However, uncertainty may well be an additional determinant of market-wide liquidity commonality, as studied for instance in Chung and Chuwonganant (2014) and Karolyi et al. (2012). In this respect, this paper also contributes to the stream of the literature that is concerned with the broader economi”
Do Funds Make More When They Trade More (2016, positive): “More recently, Koch, Ruenzi, and Starks (2010) and Karolyi, Lee, and van Dijk (2012) argue that such correlated trading gives rise to common-ality in liquidity among stocks.”
The Value of the Revolving Door: Political Appointees and the Stock Market (2012, neutral): “Another reason is that career 34 We compute a measure for daily liquidity based on Amihud (2002) and equation (1) in Karolyi et al. (2012) and drop the bottom 2 percent of the distribution for a time window of +/- 20 days around political and corporate appointments.”
Culture and R 2 (2014, neutral): “Kashima and Kashima (1998) code this language rule for 39 dominant languages in 71 countries.”
How Does Deposit Insurance Affect Bank Risk? Evidence from the Recent Crisis (2012, background): “Hovakimian et al. (2003) and Laeven (2002) show that weak institutional environments undermine deposit-insurance design.”
Transparency and Liquidity Uncertainty in Crisis Periods (2011, methodology): “that espoused in Kyle (1985) and captures the ability of an investor to trade in a stock without affecting its price.”
Forecasting Liquidity-Adjusted Intraday Value-at-Risk with Vine Copulas (2013, positive): “In order to model the joint distribution of returns and spreads, we follow in the footsteps of Nolte (2008) who models the price changes, transaction volumes, bid-ask spreads and intertrade durations of single stocks by the use of a parametric copula.”