Trade Size, Order Imbalance, and the Volatility-Volume Relation

By Kalok Chan, Wai-Ming Fong. 2000

442 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/446d19712770ae00f697240c4bc5939df460f462

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Citations in the corpus

Order Imbalance, Liquidity, and Market Returns (2002, methodology): “Chan and Fong (2000) analyze how order imbalance changes the contemporaneous relation between stock volatility and volume using data for about six months.”
The Impact of Trades on Daily Volatility (2006, unknown): “…based, in part, on Campbell, Grossman, and Wang (1993) who apply their theory to daily data, and because several other papers that use trading variables (e.g., Jones, Kaul, and Lipson (1994), Chan and Fong (2000), and Chordia, Roll, and Subrahmanyam (2001)), as we do, resort to daily observations.”
Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards (2004, methodology): “Results are reported in table (8) and are mostly fairly consistent with Chordia, Roll and Subrahmanyam (2001).”
Does herding affect volatility? Implications for the Spanish stock market (2012, background): “From a number of empirical studies that use different measures of volume to test these paradigms, we have taken Jones et al. (1994) and Chan and Fong (2000, 2006).”
Order Imbalances and Market Efficiency: Evidence from the Taiwan Stock Exchange (2001, background): “Using data for about six months, Chan and Fong (2000) estimate how order imbalances change the contemporaneous relation between stock volatility and volume.”
Trading activity, realized volatility and jumps (2010, methodology): “Following Chan and Fong (2006) (CF), we estimate this relation by OLS, use autocorrelation and heteroskedasticity-robust (Newey and West) standard errors, and include a”
An Empirical Analysis of Stock and Bond Market Liquidity (2005, background): “9 1990, Jones, Kaul, and Lipson, 1994, and Chan and Fong, 2000): Rit = a1 + 4∑ j=1 a2jDj + 12∑ j=1 a3jRit−j + eit, (1) where Dj is a dummy variable for the day of the week and Rit represents the daily return on the Lehmann Brothers’ bond index or on the CRSP value-weighted index.”