Price Discovery and Trading After Hours

Barclay, Michael J.; Hendershott, Terrence

doi:10.1093/rfs/hhg030

Cited by 345 publications

(255 citation statements)

References 45 publications

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“…The pattern of the market pre-opening trading has been studied in the earlier literature (e.g., by Amihud and Mendelson (1991), Biais, Hillion, and Spatt (1999), , Ciccotello and Hatheway (2000), Madhavan and Panchapagesan (2000), and Barclay and Hendershott (2003)). However, much of this literature is dated, and is based on research conducted well before the rapid growth in the number of HFTs over the course of the past decade or so.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this manner, we take advantage of our detailed data, as we can pinpoint an order (trade) that moves the quoted (traded) price and, thus, we can identify which trader group submitted that order (initialized that trade) and the type of the order. We measure the amount of new information incorporated into stock prices using the weighted price contribution (W P C) suggested and used also by Barclay and Warner (1993), , and Barclay and Hendershott (2003).…”

Section: C2 Price Discoverymentioning

confidence: 99%

“…First, we investigate price discovery by looking at the deviation of the pre-opening quoted price from the opening price, computed for each second of the entire pre-opening period, in different stock groups. Second, we test the price efficiency of the pre-opening quotes, using an unbiasedness regression that has been widely used in the literature (e.g., Biais, Hillion, and Spatt (1999), Barclay and Hendershott (2003), and Barclay and Hendershott (2008)). This analysis highlight results that are consistent with the W P C study presented in this section.…”

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confidence: 99%

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Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods

Bellia¹,

Pelizzon²,

Subrahmanyam³

et al. 2017

SSRN Journal

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We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to market quality, defined by price discovery and liquidity provision, in the opening auction. We use a unique dataset from the Tokyo Stock Exchange (TSE) based on server-IDs and find that HFTs dynamically alter their presence in different stocks and on different days. In spite of the lack of immediate execution, about one quarter of HFTs participate in the pre-opening period, and contribute significantly to market quality in the pre-opening period, the opening auction that ensues and the continuous trading period. Their contribution is largely different from that of the other HFTs during the continuous period.JEL classification: G12, G14. Key-words: High-Frequency Traders (HFTs), Pre-Opening, Opening Call Auction, Price Discovery, Liquidity provision. * Bellia and Pelizzon are with SAFE, Goethe University and Ca' Foscari University of Venice. Subrahmanyam is with Leonard N. Stern School of Business, New York University. Uno is with Waseda University and Ca' Foscari University of Venice and Yuferova is with Norwegian School of Economics (NHH). We are grateful to Jonathan Brogaard, Austin Gerig, Björn Hagströmer, Joel Hasbrouck, Frank Hatheway, Terry Hendershott, Andrei Kirilenko, Mark van Achter, anonymous high-frequency traders, and participants at the FMA European Conference 2015, the 4th International Conference on the Industrial Organization of Securities and Derivatives Markets: High Frequency Trading, the SAFE Microstructure Workshop, Goethe University, the Conference on Securities Markets Trends, Risks and Policies, CONSOB-BAFFI CAREFIN, Bocconi University, the Swiss Society for Financial Market Research SGF Conference, the Nippon Finance Association Meeting, and the CFS Conference on High Frequency Trading, for helpful suggestions. We also thank the Tokyo Stock Exchange for providing us with anonymous detailed account-level data, which formed the basis of the research reported on in this paper. This work was carried out with the generous financial support of EUROFIDAI, which we appreciate. We also thank the Research Center SAFE, funded by the State of Hessen Initiative for Research (LOEWE), for financial support. Darya Yuferova also gratefully acknowledges the Vereniging Trustfonds Erasmus Universiteit Rotterdam for supporting her research visit to NYU Stern and is also grateful to Rotterdam School of Management, Erasmus University, where some work on this paper was carried out during her PhD studies.Global equity markets have been fundamentally altered in the past decade due to vast improvements in the speed of trading and the consequent fragmentation of market activity. Among other changes, in many markets, traditional market makers have been replaced by high-frequency traders (HFTs), operating at the level of a few milliseconds or even mi- croseconds.1 This increase in trading speed allows markets to operate far beyond human capabilities, given that the average t...

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Section: Literature Reviewmentioning

confidence: 99%

Section: C2 Price Discoverymentioning

confidence: 99%

mentioning

confidence: 99%

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Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods

Bellia¹,

Pelizzon²,

Subrahmanyam³

et al. 2017

SSRN Journal

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“…the daytime and overnight time-series parameters). So, an intraday trading requires a different set of TTF trading functionalities rather than an overnight-position based trading (Blackrock, 2010;Avellaneda & Zhang, 2010;Barclay & Hendershott, 2003).…”

Section: The Temporal Leveraged Etf In Overnight-position Vs Daytimementioning

confidence: 99%

The Leveraged ETF Inefficiency in Trending & Range-Bound Markets: An Application Case Study for a 3x Leveraged Gold Miners ETF

Basdekidou¹

2017

IJEF

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The main goal of this paper is to introduce the leveraged ETF die-down price action technical market anomaly (leveraged ETF anomaly), and then to discuss the temporal dimension and the subsequent (time-series) functionalities of this anomaly (temporal leveraged ETF anomaly). Our approach not only challenging the efficient-market hypothesis with regards to constantly declining leveraged ETF price action course, but also has a temporal dimension because it uses the Jesse Livermore's "psychological time" as parameter in both functions: (i) "emotional control" for opening position at the beginning of an intraday or short-term move and thereafter for holding this position; and (ii) in "money risk management -exit policy" for closing position. Traditional fundamental analysis theories and technical analysis rules and approaches are not able to interpret the die-down (i.e. a constantly declining in a mid-and long-term basis) leveraged ETF price action course. Instead, a rational dynamic and temporal representative agent could explain and document better this anomaly and this is the case of this article (i.e. trading exploitation functionality). The presented research shows that the proposed temporal leveraged ETF anomaly accumulates profit entirely overnight in sideways and in choppy markets, while in a trending market the profit occurs intraday. These findings for the leveraged ETF instruments reject classical theories of trending and sideways markets returns. Hence, (i) in a sideways or in a choppy market, a well designed overnight-position return strategy based on temporal leveraged ETF anomaly; and (ii) in a trending market, a well designed daytime-position return strategy based on temporal leveraged ETF anomaly as well, could gain benefit at the expense of hedgers and long-term investors respectively. After back-testing our research in available 5-year data for the JNUG 3x leveraged ETF (gold miners juniors), we found that overnight-position speculators, in sideways or choppy markets, profit from the proposed temporal leveraged ETF trading strategy approach at the expense of hedgers; and daytime swing traders, in trending markets, profit from the proposed temporal leveraged ETF trading strategy approach at the expense of long-term investors.

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“…Technology is now a very important determinant of asset price discovery process (see among others Barclay & Hendershott, 2003, Barclay et al, 1990, Chan et al, 1995, Easley et al, 1996, Easley et al, 1997, Flood et al, 1999, Hendershott & Riordan, 2011. The advent of high frequency trading/traders (HFT) or algorithmic trading (AT) has seen the gradual erosion of the classic floor trading by computer algorithm controlled trading.…”

Section: High Frequency Tradingmentioning

confidence: 99%

A taxonomy of the 'dark side' of financial innovation: the cases of high frequency trading and exchange traded funds

Diaz‐Rainey

Ibikunle

2012

IJEIM

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Price Discovery and Trading After Hours

Cited by 345 publications

References 45 publications

Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods

Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods

The Leveraged ETF Inefficiency in Trending & Range-Bound Markets: An Application Case Study for a 3x Leveraged Gold Miners ETF

A taxonomy of the 'dark side' of financial innovation: the cases of high frequency trading and exchange traded funds

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