Price Discovery in Fragmented Markets

Jong, Frank de; Schotman, Peter C.

doi:10.1093/jjfinec/nbp015

Cited by 46 publications

(49 citation statements)

References 21 publications

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“…We analyse the contribution of the trading pit to price discovery using the information share methodology of De Jong and Schotman (2010). This method relies on a structural model related to our model for afterhours trading.…”

Section: Hypothesesmentioning

confidence: 99%

“…We accomplish this using the information share methodology of De Jong and Schotman (2010). In this framework, the observed prices of an asset in different venues, in this case in the trading pit and the ECN, are driven by a latent efficient price process.…”

Section: Information Sharesmentioning

confidence: 99%

“…De Jong and Schotman (2010) propose a price discovery measure quantifying the ex-planatory power of changes in each of the observed security prices for the innovations in the latent price. The total price innovation of each venue in period t is defined as…”

Section: Information Sharesmentioning

confidence: 99%

“…De Jong and Schotman (2010) decompose the goodness-of-fit of this regression into information shares which show how much of the price innovations is explained by the total innovations in each market. Ozturk, Van der Wel and Van Dijk (2014) show that the information shares are defined as…”

Section: Information Sharesmentioning

confidence: 99%

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Why Do Pit-Hours Outlive the Pit?

2015

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Why do pit-hours outlive the pit? Terms of use: Documents in Sait R. Ozturk Michel van der Wel Dick van Dijk ABSTRACTWe study why a majority of trades still happen during the pit hours, i.e. when the trading pit is open, even after the pit ceased to be a liquid and informative venue. We investigate the case of 30-year U.S. Treasury futures using a ten-years-long intraday data set which contains the introduction of the CME Globex platform as an example of sophistication in electronic trading. We use a structural model to estimate the timevariation in potential factors of the clustering of trading activity around the pit hours, namely price informativeness, information asymmetry and price impact of trades. We find evidence for a feedback mechanism between trading activity and these factors. Across the sample period, price informativeness during the afterhours is a consistently significant factor attracting trade activity. Information asymmetry has a negative effect on afterhours activity, particularly during the crisis years. The negative effect of price impact on afterhours activity ceases to be a significant factor from 2007 on, possibly due to improvements in order execution algorithms and electronic trading facilities.

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Section: Hypothesesmentioning

confidence: 99%

Section: Information Sharesmentioning

confidence: 99%

Section: Information Sharesmentioning

confidence: 99%

Section: Information Sharesmentioning

confidence: 99%

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Why Do Pit-Hours Outlive the Pit?

2015

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“…Our definition follows the calendar time measures proposed by De Jong and Schotman (2004) for an unobserved components model. It exploits the structural interpretation of the unobserved components model, in contrast to the reduced form expressions in Hasbrouck (1995).…”

Section: Introductionmentioning

confidence: 99%

Price discovery in tick time

Frijns

Schotman

2009

Journal of Empirical Finance

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In this paper we propose a tick time model for the quote setting process on Nasdaq using a time series of all quote updates by the most active dealers and ECN's (Electronic Communication Networks). The model includes duration effects in the volatility of the efficient price and in the covariance of quote updates with the efficient price. As a measure of price discovery we define information shares in tick time. When aggregated to calendar time they provide an alternative for the Hasbrouck (1995) information shares.In the empirical analysis we compare quotes from two ECN"s (Island and Instinet), and three wholesale market makers for 20 actively traded stocks with varying liquidity. We find that volatility does not increase with the duration between quote updates, and that longer quote durations lead to lower price discovery. In terms of price discovery we find that ECNs tend to dominate the liquid stocks, whereas market makers are important for less liquid stocks.

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Components of the Bid–Ask Spread and Variance: A Unified Approach

Hagströmer

Henricsson

Nordén

2016

Journal of Futures Markets

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We develop a structural model for the price formation and liquidity supply of an asset. Our model facilitates decompositions of both the bid–ask spread and the return variance into components related to adverse selection, inventory, and order processing costs. Furthermore, the model shows how the fragmentation of trading volume across trading venues influences inventory pressure and price discovery. We use the model to analyze intraday price formation for gold futures traded at the Shanghai Futures Exchange. We find that order processing costs explain about 50% of the futures bid–ask spread, whereas the remaining 50% is equally due to asymmetric information and to inventory costs. About a third of the variance in futures returns is attributable to microstructure noise. Trading at the spot market has a significant influence on futures price discovery, but only a limited impact on the futures bid–ask spread. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:545–563, 2016

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Price Discovery in Fragmented Markets

Cited by 46 publications

References 21 publications

Why Do Pit-Hours Outlive the Pit?

Why Do Pit-Hours Outlive the Pit?

Price discovery in tick time

Components of the Bid–Ask Spread and Variance: A Unified Approach

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