How Does Liquidity React to Stress Periods in a Limit Order Market?

Beltran-Lopez, Helena M.; Durré, Alain; Giot, Pierre

doi:10.2139/ssrn.1691595

Cited by 150 publications

(5 citation statements)

References 82 publications

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“…The place before continuous trading commences and leads to opening prices being set while the second auction ("end-of-day") takes place at day-close between 17:25 and 17:30 followed by a 10-minute window of trading to allow traders to transact at the "end-of-day" auction"s prices (Beltran et al, 2004). The system allows the placement of traditional (limit/market) and more sophisticated (fill-orkill 18 ; must-be-filled 19 ; iceberg 20 ) orders.…”

Section: The Euronextmentioning

confidence: 99%

“…The system allows the placement of traditional (limit/market) and more sophisticated (fill-orkill 18 ; must-be-filled 19 ; iceberg 20 ) orders. Block trading is allowed for large-volume orders within price-limits set by the market (Beltran et al, 2004). Details on all orders/trades are available to traders pre-and post-trade, with trader-anonymity being ensured (Andrikopoulos et al, 2014).…”

Section: The Euronextmentioning

confidence: 99%

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Herding dynamics in exchange groups: Evidence from Euronext

Economou

Gavriilidis

Goyal

et al. 2015

Journal of International Financial Markets, Institutions and Mo

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 We examine whether joining an exchange group confers an effect over herding in the group's member-markets and if this effect persists when accounting for various domestic and international market states, the dynamics of the group's member-markets and the outbreak of financial crises  We test for the above in the context of the Euronext, which contains four equity markets (Belgium, France, the Netherlands and Portugal)  Herding is significant post-merger in all four markets; herding in Portugal is significant (yet less strong) pre-merger as well. These results are robust when controlling for various domestic/international market states and the dynamics of the group's markets  Herding following the outbreak of the euro-zone crisis is significant in Belgium, the Netherlands and Portugal, and is motivated by the dynamics of the group's two largest markets (France and the Netherlands). *Highlights (for review)Page 2 of 33 A c c e p t e d M a n u s c r i p t Herding Dynamics in Exchange Groups: Evidence from Euronext AbstractThis study investigates in the context of the Euronext, whether joining an exchange group affects herding in the group"s member-markets and if this effect persists when accounting for various domestic and international market states, the dynamics of the group"s member-markets and the outbreak of financial crises. We find that herding is significant post-merger in all four constituent equity markets (Belgium, France, the Netherlands and Portugal) of the Euronext, with herding in Portugal being significant (yet less strong) pre-merger as well. These results are robust when controlling for various domestic and international market states, as well as the dynamics of the group"s markets. The period following the outbreak of the euro-zone sovereign debt crisis produces significant herding in Belgium, the Netherlands and Portugal, with this herding being motivated by the dynamics of the group"s two largest markets (France and the Netherlands).JEL classification: G12, G15, G31

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Section: The Euronextmentioning

confidence: 99%

Section: The Euronextmentioning

confidence: 99%

Herding dynamics in exchange groups: Evidence from Euronext

Economou

Gavriilidis

Goyal

et al. 2015

Journal of International Financial Markets, Institutions and Mo

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“…This topic is considered in the European Regulation 1228/2003 ("on conditions for access to the network for cross-border exchanges in electricity"), which states that network congestion problems must be addressed with non-discriminatory and market-based solutions. Currently, a wide range of congestion management methods are used across Europe 49 . In continental Europe, the most used method is explicit auctioning, while market splitting/coupling, initially only used in Scandinavia, should expand considerably with the decision taken recently by the Belgian, Dutch and French power exchanges to link their markets to integrate their exchanges (APX, Powernext and Belpex) and to use this technique to allocate (part of) the cross-border capacity.…”

Section: Congestion Managementmentioning

confidence: 99%

The Single European Electricity Market: A Long Road to Convergence

2006

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In the context of a first Working Paper the authors argued that electricity has a number of characteristics that set it apart from other commodities. It was demonstrated that some of these characteristics might complicate the deregulation process. This paper analyses the ongoing deregulation process in the European electricity sector and attempts to establish whether these difficulties can more readily be solved at European level. It would appear that some problems, e.g. economies of scale in electricity generation, have less of an impact at European level than within smaller national markets. However, a number of difficulties have to be overcome before a unified European electricity market can become a reality. These include the limited interconnection capacities between Member States. The European Commission has taken steps to improve the situation, for example by offering financial support for investments and promoting the development of regional markets as an interim measure ultimately leading to a fully integrated market. Apart from the difficulties related to electricity generation and transmission there are also exogenous factors that influence the ongoing deregulation process, e.g. the implementation of the Kyoto protocol and the dramatic increases in primary fuel prices. This paper argues that a consistent, stable and uniform European regulatory framework must be put in place if the impact of these difficulties is to be minimised. JEL Classification: L94.

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“…In addition, we extend the work of Beltran-Lopez et al (2004), Gomber et al (2004), Naes and Skjeltorp (2006) and Cao et al (2009), and investigate the time-varying structure of the order book. Using data from Euronext over a period of five months, Beltran-Lopez et al (2004) study the impact of volatility on liquidity; however, their data is restricted to the top five limit orders on both sides of the order book. In contrast, we use the full depth of the limit order book throughout our analyses.…”

Section: Introductionmentioning

confidence: 99%

Intraday liquidity patterns in limit order books

Malik

Ng²

2014

Studies in Economics and Finance

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Purpose – Algorithmic trading attempts to reduce trading costs by selecting optimal trade execution and scheduling algorithms. Whilst many common approaches only consider the bid-ask spread when measuring market impact, the authors aim to analyse the detailed limit order book data, which has more informational content. Design/methodology/approach – Using data from the London Stock Exchange's electronic SETS platform, the authors transform limit order book compositions into volume-weighted average price curves and accordingly estimate market impact. The regression coefficients of these curves are estimated, and their intraday patterns are revealed using a nonparametric kernel regression model. Findings – The authors find that market impact is nonlinear, time-varying, and asymmetric. Inferences drawn from marginal probabilities regarding Granger-causality do not show a significant impact of slope coefficients on the opposite side of the limit order book, thus implying that each side of the market is simultaneously rather than sequentially influenced by prevailing market conditions. Research limitations/implications – Results show that intraday seasonality patterns of liquidity may be exploited through trade scheduling algorithms in an attempt to minimise the trading costs associated with large institutional trades. Originality/value – The use of the detailed limit order book to reveal intraday patterns in liquidity provision offers better insight into the interactions of market participants. Such valuable information cannot be fully recovered from the traditional transaction data-based approaches.

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How Does Liquidity React to Stress Periods in a Limit Order Market?

Cited by 150 publications

References 82 publications

Herding dynamics in exchange groups: Evidence from Euronext

Herding dynamics in exchange groups: Evidence from Euronext

The Single European Electricity Market: A Long Road to Convergence

Intraday liquidity patterns in limit order books

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