Industry co-movement and cross-listing: Do home country factors matter?

Chen, Mei‐Ping; Chang, Chi-Hung

doi:10.1016/j.japwor.2014.09.001

Cited by 5 publications

(7 citation statements)

References 98 publications

(102 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The sector effect hypothesis states that price discovery for stocks in certain sectors is more efficient in the market that specializes in those sectors. This hypothesis was previously supported by Eun and Sabherwal (2003) and Lee et al (2014) but we do not know if a robust evidence for price discovery efficiency exits in some sectors across intraday data frequencies. It is hypothesized that price discovery efficiency for stocks in the basic materials sector should be more efficient in the Canadian TSX as it is specialized in the basic materials sector.…”

Section: Panel Data Model and Hypothesis Testingmentioning

confidence: 54%

“…With the U.S. being the baseline case, the country dummy is defined as Canada = 1 for Canada and Canada = 0 otherwise. 28 The panel data model includes two exchange dummy variables. While all the 115 stocks are traded in the TSX in Canada, they are also traded in the different U.S. stock exchanges.…”

Section: Factors Affecting Price Discovery Efficiencymentioning

confidence: 99%

“…Eun and Sabherwal (2003) show that price discovery efficiency could vary by sectors, trading volume, medium-sized trades, and market-cap. Lee et al (2014) note that industries may have different comovements that will affect returns of cross-listed stocks. Frijns et al (2015aFrijns et al ( , 2018 find that liquidity, which may vary across sectors as well, can be an important factor contributing to price discovery.…”

Section: Introductionmentioning

confidence: 99%

“…Basic Information of Companies Actively Traded in the U.S. and Canadian Stock Exchanges: Feb. 14, 2016-July 28, . 2017 Notes: The authors' calculation is based on the sector and industry data retrieved from finviz.com and the market-capitalization data retrieved from www.theglobeandmail.com.…”

mentioning

confidence: 99%

“…The ticker symbol for Barrick Gold became GOLD on January 2, 2019 after Barrick and Randgold merged into one corporation still named as Barrick Gold 27. We use log(S) as this logarithmic transformation gives the panel model a better fit 28. Among the 115 companies studied, 106 are Canadian and 9 are American.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Information flow and price discovery dynamics

Meng

2020

Rev Quant Finan Acc

View full text Add to dashboard Cite

Non-homogeneous and time-varying information flow that affects the price discovery processes within and across markets is a common occurrence in reality but is often neglected in the literature of price discovery. To analyze such information flow within and across markets, we propose a new strategy with a new dynamic price discovery measure. We use this strategy to test the efficient home market hypothesis and the sector effect hypothesis based on the intraday data of the 115 stocks cross-listed and traded in the Canadian and U.S. stock markets. We find that the Canadian stock market is more efficient in price discovery for the Canadian stocks cross-listed in the U.S. stock market. A higher trading volume in the Canadian market makes price discovery in that market more efficient. The Canadian stock market is more efficient in price discovery for stocks in the basic materials sector but not in the technology and financial sectors. The NYSE Alternext is more efficient for junior stocks while the NASDAQ is more efficient for technology stocks.

show abstract

Section: Panel Data Model and Hypothesis Testingmentioning

confidence: 54%

Section: Factors Affecting Price Discovery Efficiencymentioning

confidence: 99%