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Does the Probability of Informed Trading Measure Informed Trading?

Author : James Petchey

Publisher :

Page : 47 pages

File Size : 35,98 MB

Release : 2015

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Book Description

Recent research has raised concerns over whether the probability of informed trading model (PIN) is an appropriate proxy of information asymmetry. We investigate PIN and test whether the model can detect illegal insider trading prior to M&A announcements. We then compare the performance of PIN to an alternative proxy, the PIN asymmetric autoregressive conditional duration model (PIN-AACD), to determine if this model offers a better proxy for informed trading. We find that PIN does not measure informed trading prior to M&A announcements, and that PIN-AACD offers a better measure of information asymmetry.



Measuring the Probability of Informed Trading in an Order-Driven Auction Market and a Comprehensive Analysis on the Determinants of Informed Trading

Author : Tai Ma

Publisher :

Page : 36 pages

File Size : 46,13 MB

Release : 2004

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Book Description

In this study, we are able to estimate the probability of informed trading on a transactional basis, which makes the hitherto difficult task of examining the transactional dynamics between informed trading, market depth and spread feasible. In addition, we have integrated the determinants of informed trading by a comprehensive analysis.We find that, as informed traders arrive, current volume and spread increase. This supports the clustering of trading hypothesis and provides empirical evidence to Admati and Pfleiderer (1988) viewpoint that both volatility and volume increase with informed trading. The VAR result suggests that uninformed traders avoid trading with the informed, and the decision of the uninformed depends on previous condition. The decision of the informed is based more on current situation and is attracted by price volatility.Overall, it is clear that the ultimate determinants of informed trading lies with the firm's financial quality and ownership structure. The condition of the market influences the timing of the informed trading, rather than the level of informed trading between firms.



Decomposing the Probability of Informed Trading Measure

Author : Wang Chun Wei

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Page : 37 pages

File Size : 47,64 MB

Release : 2018

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Book Description

This paper aims to analyze the dynamics of information asymmetry in market microstructure through the Easley et al. (2002)'s PIN framework in two segments. Firstly, we test to see if factors such as size, value and illiquidity can be used to explain PIN. Secondly, we extend beyond the traditional literature by examining individual components of PIN, especially the informed and uninformed trade intensities. We contribute to the literature by documenting non-linear relationships between trade intensities, and their autocorrelation functions. Our study show that uninformed intensity is more persistent than informed trading and that there exists statistically significant spillover effects from informed trading into liquidity trades, suggesting that liquidity trades lag behind that of informed trades.



An Ex-Ante Measure of the Probability of Informed Trading

Author : Marius Popescu

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Page : 45 pages

File Size : 31,98 MB

Release : 2008

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Book Description

The paper develops a new measure for the probability of informed trading, which can be estimated from the observed quotes and depths. This measure (PROBINF) represents the specialist's ex-ante estimate of the probability of informed trading. We find that PROBINF exhibits a strong and robust relationship with the observed level of insider trading and with measures of the price impact of trades. Moreover, the time series pattern of our measure in an intra-day analysis around earnings announcements is consistent with previous findings and with expectations regarding informed trading. An important advantage of PROBINF is that it can be estimated for each quote, and thus can be used to measure short term (e.g. intra-day, daily etc.) changes in informed trading and information asymmetry around events such as merger and acquisition announcements, share repurchases, stock splits, dividend announcements and index additions and deletions.





Does the Probability of Informed Trading Model Fit Empirical Data?

Author : Quan Gan

Publisher :

Page : 43 pages

File Size : 34,88 MB

Release : 2015

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Book Description

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.



Estimating the Probability of Informed Trading - Does Trade Misclassification Matter?

Author : Ekkehart Boehmer

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Page : 39 pages

File Size : 41,20 MB

Release : 2006

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Book Description

Easley et al. (1996) have proposed an empirical methodology to estimate the probability of informed trading (PIN). This approach has been employed in a wide range of applications in market microstructure, corporate finance, and asset pricing. To estimate the model, a researcher only needs the number of buyer- and seller-initiated trades. This information, however, is generally unobservable and has to be inferred from trade-classification algorithms, which are known to be inaccurate. In this paper, we show analytically that inaccurate trade classification leads to downward biased PIN estimates and that the magnitude of the bias is related to a security's trading intensity. Simulation results and empirical evidence based on order and transaction data from the New York Stock Exchange are consistent with this argument. We propose a data-based adjustment procedure that substantially reduces the misclassification bias.



Estimating the Probability of Informed Trading

Author : Ken Nyholm

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Page : pages

File Size : 34,1 MB

Release : 2001

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Book Description

Using a new empirical model, I estimate the probability of trades being generated by privately informed traders. Inference is drawn on a trade-by-trade basis using data samples from the New York Stock Exchange (NYSE). The modeling setup facilitates in-depth analysis of the estimated probability of informed trading at the intraday level and for stocks with different levels of trading activity. The most important empirical results are: (a) the intradaily pattern of the inferred probability of informed trading is highly correlated with the intradaily pattern of observed quoted spreads, (b) differences in the magnitude of quoted spreads across volume categories are not exclusively related to differences in the level of informed trading, and (c) private information is incorporated faster in the quotes for high-volume stocks than in the quotes for low-volume stocks.





Empirical Market Microstructure

Author : Joel Hasbrouck

Publisher : Oxford University Press

Page : 209 pages

File Size : 10,25 MB

Release : 2007-01-04

Category : Business & Economics

ISBN : 0198041306

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Book Description

The interactions that occur in securities markets are among the fastest, most information intensive, and most highly strategic of all economic phenomena. This book is about the institutions that have evolved to handle our trading needs, the economic forces that guide our strategies, and statistical methods of using and interpreting the vast amount of information that these markets produce. The book includes numerous exercises.