Insider Trading and Intraday Stock Price Behavior on the Tehran Stock Exchange

Document Type : Research Paper

Authors

1 Assistant Prof., Department of Economics, Factuly of Management and Economics, Sharif University of Technology, Tehran, Iran.

2 Department of Economics, Factuly of Management and Economics, Sharif University of Technology, Tehran, Iran.

Abstract

Objective: We study intraday patterns of trading volume, size, return, and volatility using the Tehran Stock Exchange (TSE) high frequency data from 2008 to 2015.
Methods: We first document the intradaily patterns in stock returns, volatility, and trading value and volume. We subsequently examine the insider trading hypothesis by identifying the contribution of large, medium, and small order sizes to price changes.
Results: Our results indicate that trading value and volume follow a J-Shaped pattern, whereas absolute return exhibit an L-Shaped behavior. Our findings are consistent with the existing studies which document an increase in trading value and volume as well as absolute return. However, unlike the existing literature, we do not find a U-Shaped pattern in returns, and no statistically significant difference in returns is found throughout the trading hours. To examine the behavior of informed traders, we examine midsize trades and, consistent with the predictions of Barclay and Warner’s (1993) stealth-trading hypothesis, we find that they have higher price impact compared to other trade sizes. However, our findings do not support the intraday stealth trading pattern, as insiders prefer to trade in low and medium trade size to avoid revealing their information. This may be due to the low liquidity of the TSE.
Conclusion: Our findings are relevant for both policy-makers and traders. From the policy perspective, trading halts imposed by the regulatory body may have implications for trading behavior at the time of market open. Further, traders can use our findings to better understand the intra-daily behavior of the TSE and hence, execute large orders more efficiently.

Keywords


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