Price impact of block trades in the Saudi stock market

Alzahrani, Ahmed; Gregoriou, Andros; Hudson, Robert

doi:10.1016/j.intfin.2012.11.003

Cited by 22 publications

(37 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This implies that the market has learnt something new about the instrument, which leads to a new price equilibrium. In this study, we follow Mayers (1990), Gemmill (1996), Frino, Jarnecic, and Lepone (2007) and Alzahrani, Gregoriou, and Hudson (2013) …”

Section: Methodsmentioning

confidence: 99%

“…3 We adopt the model of Frino, Jarnecic, and Lepone (2007), thereafter employed by Alzahrani, Gregoriou, and Hudson (2013), in examining some likely determinants of block trade price impact on the ECX. Accordingly, we estimate the following time series regression with EUA contracts-specific variables: where PI t corresponds to one of three price impact measures: total price impact, permanent price impact and temporary price impact.…”

Section: Methodsmentioning

confidence: 99%

“…Holthausen, Leftwich, and Mayers (1987) also investigate price impact due to block trades, and discover that larger trades induce larger price impact than smaller trades. Barclay and Warner (1993), Chakravarty (2001) and Alzahrani, Gregoriou, and Hudson (2013) also provide evidence that order size and subsequent execution potentially result in corresponding trade price impact. In relation to temporary price impact, the first study to show asymmetry in block trades' price effects is Gemmill's (1996) on the London Stock Exchange, with significant differences in the magnitude of price impact being reported.…”

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

Price impact of block trades: the curious case of downstairs trading in the EU emissions futures market

Ibikunle¹,

Gregoriou²,

Pandit³

2014

The European Journal of Finance

Self Cite

View full text Add to dashboard Cite

Using high-frequency data from the European Climate Exchange (ECX), we examine the determinants of price impact of €21 billion worth of block trades during 2008-2011 in the European carbon market. We find that wider bid-ask spreads and volatility are characterised by smaller price impact. Larger levels of price impact are more likely to occur during the middle of the trading day, specifically the four-hour period between 11am and 3pm, than during the first or final hours. Purchase block trades induce relatively smaller price impact on price run-up, while sell block trades exhibit larger price impact on price run-up. We conclude that block trades on the ECX induce less price impact than in equity or conventional futures markets, and that a significant proportion of the effects contradict findings on block trades in those markets; thus, we provide the first evidence of the curious bent to block trading in the EU Emissions Trading Scheme (EU-ETS).

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Price impact of block trades: the curious case of downstairs trading in the EU emissions futures market

Ibikunle¹,

Gregoriou²,

Pandit³

2014

The European Journal of Finance

Self Cite

View full text Add to dashboard Cite

show abstract

“…Finally, given that Alzahrani, Gregoriou, and Hudson (2013) and Frino, Jarnecic, and Lepone (2007) report intraday effects for block trades for consistency, we introduce trading hour, day of week and month of year dummy variables in equations (5) and (7) in order to capture trading time/period effects. The results which can be seen in Table 3 …”

Section: [Insert Table 2 Here]mentioning

confidence: 99%

The accuracy of spread decomposition models in capturing informed trades

Gregoriou

Rhodes

2017

RBF

Self Cite

View full text Add to dashboard Cite

Purpose -The purpose is to examine the empirical relationship between trades undertaken by informed agents (managers) and the proxies for informed trades computed by bid-ask spread decomposition models.Design/methodology/approach -An econometric application of spread decomposition models to data from the London Stock Exchange, with an examination of whether the model predictions are co-integrated with actual outcomes.Findings -We find overwhelming evidence of non stationary behaviour between the actual and predicted informed trade prices. Our findings suggest that there is a clear need for an alternative to extant spread decomposition models perhaps incorporating findings from behavioural finance.Originality/value -Given the importance of stock market liquidity and the extensive use of spread decomposition models in predicting informed trades, we believe that the research conducted in our paper is an important contribution to the market microstructure literature.Keywords; Spread Decomposition Models, Information Asymmetry, Bid-Ask Spread, Time Series Modelling, Behavioural Finance. Paper type: Empirical paper. Page2 AbstractIn this paper we examine the empirical relationship between trades undertaken by informed agents (managers) and the proxies for informed trades computed by bid-ask spread decomposition models. Behavioural finance offers a rationale for examining the efficacy of existing approaches. We find overwhelming evidence of non stationary behaviour between the actual and predicted informed trade prices. Our results are robust to non linear speed of adjustments of stock prices, trade sizes, trading time and calendar anomalies. Our findings suggest that there is a clear need for an alternative to extant spread decomposition models. As we present evidence that spread decomposition models do not serve to adequately address observed behaviour, we suggest avenues for further research. Given the importance of stock market liquidity and the extensive use of spread decomposition models in predicting informed trades, we believe that the research conducted in our paper is an important contribution to the market microstructure literature.

show abstract

“…Further, Lillo et al 16 develop a market impact function, and present a positive correlation between volume and stock price change. In addition, there are other factors that research on the securities market impact [17][18][19][20][21][22] . In fact, the market impact is one of the most costly transaction cost components and always causes adverse price movement.…”

Section: Transaction Costmentioning

confidence: 99%

Research Progress of Algorithmic Trading at Home and Abroad

Gao¹,

Yan²,

Wu³

2016

Proceedings of the First International Conference Economic and Business Management 2016

View full text Add to dashboard Cite

In recent years, many institutional investors use algorithmic trading to complete their investment decisions. This method reduces the transaction costs, improves the investment return. Algorithmic trading is a new transaction mode. This paper introduces the algorithmic trading and the development process, presents the development process of transactions costs, reviews the latest research literatures of algorithmic trading strategy, and introduces the literatures of investment portfolio selection. Based on the present research and the current situation of algorithmic trading in our country, this paper develops the application and suggestion for algorithmic trading.

show abstract

Price impact of block trades in the Saudi stock market

Cited by 22 publications

References 53 publications

Price impact of block trades: the curious case of downstairs trading in the EU emissions futures market

Price impact of block trades: the curious case of downstairs trading in the EU emissions futures market

The accuracy of spread decomposition models in capturing informed trades

Research Progress of Algorithmic Trading at Home and Abroad

Contact Info

Product

Resources

About