Table 4 - uploaded by Naoufel Liouane
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This paper provides empirical evidence on the relationship between order size, volatility and spread in the
foreign exchange market based on a FX dealer’s quotes. It uses a new data set that includes intra-daily data on
trading volumes. The results are broadly consistent with the findings of the literature. It is found that spreads
are independent...
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The ship demolition sector is one of the major
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Citations
... However, dealers can achieve this without any adjustment in the markup because core half-spreads already respond to volatility. With respect to trade size, Ho and Stoll (1981) predicts a positive impact but the empirical findings of Glosten and Harris (1988) reveal a negative impact that has subsequently been confirmed in other studies (e.g., Osler et al., 2011;Gtifa and Liouane, 2013). ...
This study shows that first-degree price discrimination drives substantial cross-client variation in OTC bid-ask spreads, and that dealers price discriminate in response to three client characteristics: trading volume, market sophistication, and information. Such discrimination is possible due to the lack of client anonymity and the high trade opacity of OTC markets; it is generally not feasible in order-driven markets. Cross-client variation is substantial in our data, which comprise the complete trading record from a top-10 institution the world's largest OTC market. We develop and test a new spread decomposition model tailored to OTC markets. Price discrimination accounts for 80% of cross-client variation, with the largest contribution from market sophistication.
... Rahman et al. (2002) documented that intraday variations of bid-ask spread and intraday return volatility are expected to be positively correlated because an information arrival is supposed to stimulate an increase in volatility which in turn widens the bid-ask spread. In line with microstructure theory, a group of researchers like Wei (1991); Bollerslev and Melvin (1994); Galati (2001); McGroarty et al. (2009) and Gtifa and Liouane (2013) in foreign exchange markets, Ding and Chong (1997); Wang and Yau (2000); Frank and Garcia (2011); Wang et al. (2014) in futures market and Rahman et al. (2002) andHussain (2011) in equity markets find positive relationship between return volatility and spread. In addition, Rahman et al. (2002) and Hussain (2011) also reported lagged relationship in between them. ...
Relying on the mixture of distribution hypothesis (MDH) and the sequential information arrival hypothesis (SIAH), this paper empirically examines the relationship between stock returns, trading volume and bid-ask spread for 50 Indian stocks using high frequency 5-minute data set for the period July 2, 2012 to December 31, 2012. This is the first study in India using bid-ask spread as yet another measure of information flow variable along with trading volume. Our empirical findings provide evidence of a positive contemporaneous relationship between absolute returns and trading volume as well as between absolute returns and bid-ask spread. The Granger causality test results show that the information content of trading volume and bid-ask spread are useful for predicting stock returns in Indian stock market. Overall results seem to indicate that information arrival to investors tends to follow a sequential rather than simultaneous process as suggested by SIAH. In summary, both trading volume and bid-ask spread serve as a good measure of information variable in India. ?
This paper empirically examines the relationship between stock return volatility, trading volume and bid-ask spread within the scope of mixture of distribution hypothesis (MDH) and sequential information arrival hypothesis (SIAH) in the Indian stock market using high frequency 5-minute data set over the period of 2 July 2012 to 31 December 2012. This is the first kind of study in India using bid-ask spread as an additional information variable along with trading volume to investigate the relationship with stock return volatility. Our empirical findings provide evidence of a positive contemporaneous relationship between return volatility and trading volume, and also between return volatility and bid-ask spread. Moreover, the results of Granger causality test show that the information content of trading volume and bid-ask spread are useful for predicting stock return volatility. Our results indicate that information arrival to investors tends to follow a sequential rather than a simultaneous process. This finding is consistent with the sequential information arrival hypothesis and contradicts the mixture of distribution hypothesis.
