Price Clustering on the Tokyo Stock Exchange

Ascioglu, Asli; Comerton‐Forde, Carole; McInish, Thomas H.

doi:10.1111/j.1540-6288.2007.00172.x

Cited by 48 publications

(18 citation statements)

References 18 publications

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“…By contrast, the frequency for sell orders at the prices with a last digit of 9 is 0.083 and higher than that at the prices with a last digit of 1 (0.073). This phenomenon is consistent with Aşçıoğlu, Comerton‐Forde and McInish (2007) who find evidence of strategic trading behavior on the Tokyo Stock Exchange. We discuss this issue in .…”

Section: Resultssupporting

confidence: 91%

“…This paper examines the association between price clustering and price barriers. Finally, we investigate whether some traders who anticipate the clustering tendencies attempt to step ahead of limit order congestion and assure faster execution, as claimed by Niederhoffer (1965) and Aşçıoğlu, Comerton‐Forde and McInish (2007).…”

Section: Resultsmentioning

confidence: 99%

“…Recall that, in Figure 1, the asymmetric clustering patterns are observed around the last digits 0 and 5 for class I stocks. Regarding the presence of the asymmetry, Aşçıoğlu, Comerton‐Forde and McInish (2007) state that some traders familiar with the clustering tendencies could step ahead of limit order congestion to assure faster executions. If front running exists, there are more sell limit orders than buy limit orders at one tick below round prices and more buy orders at one tick above round prices.…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Price Clustering: Evidence Using Comprehensive Limit‐Order Data

Chiao

Wang

2009

The Financial Review

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Employing comprehensive limit-order data which identify investor types, this paper examines the clustering pattern of limit-order prices. First, limit orders, particularly those submitted by individual investors (IIs), tend to cluster at integer and even prices. Second, nonmarketable limit-order prices cluster more than marketable limit-order prices, indicating that aggressive limit orders generally embed more information. Third, investors choosing even-priced limit orders are not penalized by lower execution ratios. Fourth, investors (particularly IIs) strategically exhibit front-running behavior. Fifth, price clustering indeed creates price barriers. Finally, the degree of price clustering using trade data is significantly underestimated, compared to that using limit-order data.

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Section: Resultssupporting

confidence: 91%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Price Clustering: Evidence Using Comprehensive Limit‐Order Data

Chiao

Wang

2009

The Financial Review

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“…Aşçıoğlu, Comerton-Forde and McInish [34] show that investors submit orders with one tick better than zero and five to avoid queuing orders at prices ending in these digits. Given prices cluster on round numbers, a water trader who places a bid and wants a higher probability of execution than a bid at the clustered price will tend to place the bid one cent away from the clustered price.…”

Section: Evidence Of Strategic Price Clustering Behaviormentioning

confidence: 99%

Understanding Irrigator Bidding Behavior in Australian Water Markets in Response to Uncertainty

Zuo

Brooks

Wheeler

et al. 2014

Water

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Water markets have been used by Australian irrigators as a way to reduce risk and uncertainty in times of low water allocations and rainfall. However, little is known about how irrigators' bidding trading behavior in water markets compares to other markets, nor is it known what role uncertainty and a lack of water in a variable and changing climate plays in influencing behavior. This paper studies irrigator behavior in Victorian water markets over a decade (a time period that included a severe drought). In particular, it studies the evidence for price clustering (when water bids/offers end mostly around particular numbers), a common phenomenon present in other established markets. We found that clustering in bid/offer prices in Victorian water allocation markets was influenced by uncertainty and strategic behavior. Water traders evaluate the costs and benefits of clustering and act according to their risk aversion levels. Water market buyer clustering behavior was mostly explained by increased market uncertainty (in particular, hotter and drier conditions), while seller-clustering behavior is mostly explained by strategic behavioral factors which evaluate the costs and benefits of clustering.

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“…In the equity market, Kandel et al (2001) and Aşçıoğlu et al (2007) provide the evidence to support the attraction hypothesis in the markets where there is no direct involvement of professional traders or negotiation in pricing. Unlike the equity market, foreign exchange transactions are dominated by professional traders who deal with millions of dollars in each trade.…”

Section: Hypothesesmentioning

confidence: 71%