Liquidity in Iranian Stock Market, Predicting Market Depth Using Intraday Data

Document Type : applied

Author

Postdoctoral Researcher, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

Liquidity of an asset is a key concept in financial markets. Intuitively, liquidity can be interpreted as transacting an asset rapidly and at a low cost. Despite its importance, finding a precise measure for this concept is not an easy task. In this paper, by using tick-by-tick transaction and limit order book data, we calculate VNET measure of liquidity for 16 stocks in Iranian financial market.
This measure, introduced by Engle and Lang in 2001, measures the excess volume of buy and sell that leads to a specific price movement. The results show that the market depth for different stocks is time varying and the variation is significantly correlated with volatility. This is consistent with the prediction of asymmetric information models, in which higher volatility corresponds to higher probability of the presence of informed traders.
JEL: D82, G1 
How to cite this paper: Rahimian, S. (2016). Liquidity in Iranian Stock Market, Predicting Market Depth Using Intraday Data. Quarterly Journal of Risk Modeling and Financial Engineering, 1(1), 67–113. (In Persian)

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Amihud, Y., & Mendelson, H. (1986). Asset Pricing and the Bid-ask Spread. Journal of Financial Economics, 17(2), 223–249.
Amihud, Y. (2002). Illiquidity and Stock Returns: Cross Section and Time-series Effects. Journal of Financial Markets, 5(1), 31-56.
Anand, A., & Martell, T. (2001). Informed Limit Order Trading, Syracus University, New York.
Bernstein, P. L. (1987). Liquidity, Stock Markets, and Market Makers. Financial Management, 16(2), 54-62
Engle, J., Robert F., &Lange, J. (2001). PredictingVNET: A Model of the Dynamics of Market Depth. Journal of Financial Markets, 4(2), 113-142
Engle, R.,& Russell, J. (1997). Forecasting the Frequency of Changes in Quoted Foreign Exchange Prices with the Autoregressive Conditional Duration Model. Journal of Empirical Finance, 4(2), 187-212.
Fabre, J., & Frino, A. (2004). Commonality in liquidity: Evidence from the Australian Stock Exchange. Accounting and Finance, 44(3), 357-368.
Goyenko, R. Y., Holden, C. W., & Trzcinka, C.A. (2009). Do liquidity Measures Measure Liquidity? Journal of Financial Economics, 92(2), 153–181.
Handa, P., & Schwartz, R. (1996), Limit Order Trading. Journal of Finance, 51(5), 1835–1861.
Koksal, B. (2012). An Analysis of Intraday Patterns and Liquidity on the Istanbul Stock Exchange.Central Bank of the Republic of Turkey, Research and Monetary Policy Department Working paper, No. 12/26.
Kyle, A. S. (1985). Continuous Auctions and Insider Trading. Econometrica, 53(6), 1315-1335.
Lee, C.M. & Ready, M. J. (1991). Inferring Trade Direction from Intraday Data. The Journal of Finance, 46(2), 733-746.
Narayan, P. K., & Zheng, X. (2011).The Relationship between Liquidity and Returns on the Chinese Stock Market. Journal of Asian Economies, 22(3), 259-266.
Sarr, A., & Lybek, T. (2002). Measuring liquidity in Financial Markets. IMF Working Paper, WP/02/232.
Zheng, X., & Zhang, Z. (2006). Commonality in Liquidity in Emerging Markets: Evidence from the Chinese Stock Market. Durham Working Paper in Economics and Finance, No. 06/04.