The probability of informed trading (PIN) is used widely as a measure of information asymmetry. Relatively little work has appeared on how well PIN models fit empirical trade data. We reveal structural limitations in PIN models by examining their marginal distributions and dependence structures represented by copulas. We develop a distribution-free test of the goodness-of-fit of PIN models. Our results indicate that estimated PIN models have generally poor fit to actual trade data. These results suggest that researchers should be cautious when PIN estimates are plugged into empirical models as explanatory variables.
Vol. 52 No. 1 - February 2017
Using a version of the ITCH data set time stamped to the millisecond, O’Hara, Yao and Ye find that odd-lot trades are highly informed. However, NASDAQ reports trades based on the size of the resting limit order, creating a bias in the count of odd-lot trades. Using ITCH data from 2013, time stamped to the nanosecond, we find that roughly 50% of odd-lot trades are created by the resting limit order and are part of larger marketable orders. We show that odd-lot marketable orders are not more informed than round/mixed lot marketable orders.
We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive co-movement of clustering, quote activity, price volatility and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.
The literature widely documents the negative liquidity impact of foreign participation in firms that permit high foreign institutional ownership. This paper employs a unique setting for the limited participation of qualified foreign institutional investors (QFIIs) in China’s A-share market and examines how this impacts on stock liquidity in emerging markets. Contrary to the findings in the literature, foreign investor participation helps enhance the liquidity of affected stocks by promoting trade activities and price discovery. The improvement in liquidity does not occur through the information friction channel, but rather the real friction channel. Our results are robust to endogeneity issue and the possible influence of the global financial crisis, industry effects and the stock exchange. Further, the liquidity improving effects of QFII are even stronger when the analysis is performed on a subsample of QFII firms.
We use high frequency data and the “identification through heteroskedasticity” approach of Rigobon (2003) to capture the contemporaneous volatility spillover effects between the US and UK equity markets. We demonstrate the relevance of taking into account the information present during simultaneous trading hours by comparing the results generated by our structural vector
autoregression with those of a traditional reduced-form vector autoregression. Our findings clearly demonstrate that contemporaneous relations matter and that ignoring them leads to inappropriate conclusions regarding the magnitude and direction of volatility spillover.