Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong

Ahn, Hee-Joon; Cai, Jun; Cheung, Yan‐Leung

doi:10.1016/j.finmar.2005.07.001

Cited by 63 publications

(37 citation statements)

References 36 publications

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“…In several studies, price clustering is found to increase during high volatility periods (see Ahn et al, 2005 andap Gwilym et al, 1998). Also, Moulton (2005) and ap Gwilym and Meng (2010) show that volatility is also a positive determinant for size clustering.…”

Section: Size and Price Clustering: Supplements Or Substitutes?mentioning

confidence: 93%

“…Fourthly, and Christie, Harris and Schultz (1994) attribute price clustering at NASDAQ to the anticompetitive behaviour of dealers who implicitly colluded to increase market making revenues. Numerous empirical studies document price clustering in the equity, derivatives and foreign exchange markets (see Ahn et al, 2005, ap Gwilym and Verousis, 2010, Chung and Chiang, 2006, Narayan et al, 2011and Sopranzetti and Datar, 2002.…”

Section: Literature Review and Positioning Of The Papermentioning

confidence: 99%

“…The first theme investigates to what extent differences in market structure affect price and size clustering. Previous literature has documented price clustering on the order book (see Ahn et al, 2005) and on a dealer market (see . However, the market structure of the LSE allows us to compare clustering of prices and sizes at downstairs and upstairs markets for the same assets.…”

Section: Literature Review and Positioning Of The Papermentioning

confidence: 99%

“…PrcLvl denotes the average daily price level for each asset and market segment. Ahn et al (2005) suggest that PrcLvl is positively related to price clustering and Harris (1991) suggests that a positive sign is expected because minimum tick size rules are more restrictive for lower-priced stocks. Finally, Tck is a control variable that takes the value of 1 for stocks with a minimum tick of xx.50p and 0 for stocks trading at xx.25p.…”

Section: Size and Price Clustering: Supplements Or Substitutes?mentioning

confidence: 99%

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Trade size clustering and the cost of trading at the London Stock Exchange

Verousis

Gwilym

2013

International Review of Financial Analysis

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For the London Stock Exchange, this paper investigates differences in trading costs between market maker (off-book) and order book trades, in the context of clustering in trade sizes and prices. We report several substantial findings. Even after controlling for differences in trade size, the realised spread measure is lower for off-book trades. For the order book, trade size clustering is not associated with differences in transaction costs nor with differences in the information content of trades. For the off-book market, trades in clustered (popular) sizes carry significantly more information than non-clustered trades. Despite the significant differences in the price impact estimates between the order book and off-book, we show that traders placing large orders off-book are still better off than trading via the order book as they benefit from a large discount from the current midpoint price. Additionally, we highlight that price and size clustering tend to occur simultaneously rather than being substitutes in this market setting.

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Section: Size and Price Clustering: Supplements Or Substitutes?mentioning

confidence: 93%

Section: Literature Review and Positioning Of The Papermentioning

confidence: 99%

Section: Literature Review and Positioning Of The Papermentioning

confidence: 99%

Section: Size and Price Clustering: Supplements Or Substitutes?mentioning

confidence: 99%

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Trade size clustering and the cost of trading at the London Stock Exchange

Verousis

Gwilym

2013

International Review of Financial Analysis

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“…There is long-standing evidence that stock prices cluster at round numbers (e.g., Niederhoffer, 1965Niederhoffer, , 1966Harris, 1991;Ahn, Cai, and Cheung, 2005;Sonnemans, 2006;Ikenberry and Weston, 2007;Bhattacharya, Holden, and Jacobsen, 2012;Kuo, Lin, and Zhao, 2015). It is unlikely that the fundamental values of stocks cluster at round numbers, and thereforeat least recently, as models of bounded rationality (Simon, 1955) have become more popular in financial economics -price clustering has been attributed to limited cognition on the part of traders.…”

Section: Introductionmentioning

confidence: 99%

Limited cognition and clustered asset prices: Evidence from betting markets

Brown

Yang

2016

Journal of Financial Markets

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Asset prices tend to cluster at round numbers. We examine betting exchange data on U.K. horse races to establish whether limited cognition is partially responsible for this clustering. The key tool in this study is the stark increase in cognitive load faced by traders during races compared to prior to races. Using an approach that is part regression discontinuity and part difference-in-differences, we find that traders exhibit a substantially higher propensity to quote round numbers, rather than the nearest non-round numbers, during races. This result is robust to a series of placebo tests.JEL classification: G02, G12, G14

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Bid‐Ask Spreads, Commissions, and Other Costs

Verousis

2013

Market Microstructure in Emerging and Developed Markets

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This chapter examines trading costs that are associated with the "costs of exchanging ownership titles". Costs are categorized as (i) commission charges which are determined by the exchange and (ii) cost components of the bid-ask spread that are determined by market participants. There are three main components of the bid-ask spread. The order processing cost which is associated with the cost of providing liquidity, the inventory cost that is due to short-term order imbalances and the adverse selection cost that refers to the cost of trading with informed traders. Spreads and commission charges are currently at very low levels in developed markets which have led to a great expansion in algorithm trading and trading volume. Trading costs for emerging markets appear to be considerably higher than for the more developed markets. Market capitalisation and liquidity differences explain some of the variability in trading costs in exchanges around the world. A second element of variability is attributed to differences in market structures.

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Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong

Cited by 63 publications

References 36 publications

Trade size clustering and the cost of trading at the London Stock Exchange

Trade size clustering and the cost of trading at the London Stock Exchange

Limited cognition and clustered asset prices: Evidence from betting markets

Bid‐Ask Spreads, Commissions, and Other Costs

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