presenting a model to optimize liquidity measures in tehran stock exchange

Subject Areas : Journal of Investment Knowledge

Alireza Fatemi ¹ , Iraj Noravesh ² , Farhad Hanifi ³ , Mani Sharifi ⁴

1 - Student of Financial Management, Department of Management, UAE Branch, Islamic Azad University, Dubai, United Arab Emirates
2 - Professor, Department of Management, UAE Branch, Islamic Azad University, Dubai, United
3 - Associate Professor, Department of Commerce, Tehran Branch, Islamic Azad University, Tehran, Iran
4 - Assistant Professor, Department of Financial Management, Shahid Beheshti University, Tehran, Iran

Received: 2021-05-23 Accepted : 2021-05-31 Published : 2023-06-22

Keywords: Factor analysis, vikor 's numerical technique, liquidity measures, liquidity risk comparison,

Abstract :

liquidity is a fundamental aspect of stock market efficiency and in terms of methodology , most of the theories related to the structure of financial markets account for the implications of liquidity behavior more than other market characteristics . therefore , the central role of market liquidity in the form of prices , and reducing the costs and risks of sustainable development and stability of financial systems is important , so liquidity issue has attracted much attention in recent years in academic studies as well as in important publications . in this research , the criteria of each liquidity type are introduced and the relationship between them is studied . in fact , the main question of this research is what measure is the criterion for the selection of liquidity in tehran stock exchange . the purpose of this thesis is to evaluate and compare liquidity capability and design a model for explaining liquidity measures in tehran stock exchange with emphasis on 11 different measures . for this purpose , a sample of eight firms listed in tehran stock exchange ( tse ) during the period 1380 to 1389 were reviewed . to achieve the goal of this research , factor analysis - vikor 's numerical algorithm which is one of multi - criteria decision making methods is used .

References:

 

• Abdi, F., Ranaldo, A., 2017. A simple estimation of bid-ask spreads from daily close, high, and low prices. Rev. Financ. Stud. 30 (12), 4437–4480.


• Alhassan, A., & Naka, A.,2019. Corporate Future Investments and Stock Liquidity: Evidence from Emerging Markets. International Review of Economics & Finan


• Amihud, Y., Mendelson, H., Pedersen, L.H., 2006. Liquidity and asset prices. Found. Trendsa® Financ. 1 (4), 269–364.


• Anagnostidis, P., & Fontaine, P.,2019. Liquidity commonality and high frequency trading: Evidence from the French stock market. International Review of Financial Analysis, 101428.


• Bernstein, P.L., 1987. Liquidity, stock markets, and market makers. Financ. Manage. 54–62.


• Chan, K., Hameed, A., & Kang, W.,2013. Stock price synchronicity and liquidity. Journal of Financial Markets, 16(3), 414–438.


• Chen, L., Lesmond, D., Wei, J., 2007. Corporate yield spreads and bond liquidity. J. Finance 62, 119–149.


• Chordia, T., Roll, R., Subrahmanyam, A., 2000. Commonality in liquidity. J. financ. econ. 56, 3–28.


• Chordia, T., Roll, R., Subrahmanyam, A., 2001. Market liquidity and trading activity. J. Finance 56 (2), 501–530.


• Chordia, T., Roll, R., Subrahmanyam, A., 2002. Order imbalance, liquidity, and market returns. J. financ. econ. 65 (1), 111–130.


• Chordia, T., Sarkar, A., Subrahmanyam, A., 2004. An empirical analysis of stock and bond market liquidity. Rev. Financ. Stud. 18 (1), 85–129.


• Chordia, T., Subrahmanyam, A., 2004. Order imbalance and individual stock returns: theory and evidence. J. financ. econ. 72 (3), 485–518.


• Chung, K.H., Zhang, H., 2014. A simple approximation of intraday spreads using daily data. J. Financ. Mark. 17, 94–120.


• Cooper, S., Groth, K., Avera, W., 1985. Liquidity, exchange listing and common stock performance. J. Econ. Bus. 37, 19–33.


• Díaz and Navarro, 2002 Díaz, E. NavarroLa prima de liquidez en la Deuda del Estado Revista de Economía Aplicada, 10 (29)


• Díaz, A., & Escribano, A.,2020. Measuring the multi-faceted dimension of liquidity in financial markets: A literature review. Research in International Business and Finance, 101079


• Fong et al., 2017 Y. Fong, C.W. Holden, C.A. Trzcinka What are the best liquidity proxies for global research? Rev. Financ., 21 (4), pp. 1355-1401


• Fong, K.Y., Holden, C.W., Tobek, O., 2018. Are Volatility Over Volume Liquidityproxies Useful for Global or US Research? Working Paper. Available at SSRN:.


• Fong, K.Y., Holden, C.W., Trzcinka, C.A., 2017. What are the best liquidity proxies for global research? Rev. Financ. 21 (4), 1355–1401.


• Hasbrouck, J., 2009. Trading costs and returns for US equities: estimating effective costs from daily data. J. Finance 64, 1445–1477.


• Huberman, G., Halka, D., 2001. Systematic Liquidity. Columbia Business School.


• Lesmond, D.A., 2005. Liquidity of emerging markets. J. financ. econ. 77 (2), 411–452.


• Li, X., & Luo, D.,2019. Financial Constraints, Stock Liquidity, and Stock Returns. Journal of International Financial Markets, Institutions and Money, 101139


• Luo, J., Chen, L., & Liu, H.,2013. Distribution characteristics of stock market liquidity. Physica A: Statistical Mechanics and Its Applications, 392(23), 6004–6014


• Norvaišienė, R., & Stankevičienė, J. (2014). Impact of Companies’ Internal Factors on Stock Liquidity in Baltic Markets. Procedia - Social and Behavioral Sciences, 156, 543–547.


• Schestag et al., 2016 Schestag, P. Schuster, M. Uhrig-Homburg Measuring liquidity in bond markets Rev. Financ. Stud., 29 (5), pp. 1170-1219


• Vortelinos et al., 2018 I. Vortelinos, K. Gkillas, C. Konstantatos, G. Peppas The efficiency in liquidity measures during the US monetary announcement, Theor. Econ. Lett., 8 (01), p. 98