Modelling of appropriate pattern in order to forecast systemic liquidity risk of corporate stocks in capital market of Iran, by using multivariate GARCH models and Markov switching approach

Subject Areas : Stock Exchange

Seied Hamid Reza  Sadat Shekarab ¹ (Department of Financial Management, Accounting and Financial Engineering, Research Sciences branch, Islamic Azad University, Tehran, Iran)
Fereydon  Ohadi ² (Department of Industrial Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran)
mohsen  Seighaly ³ (Department of Management and Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran)
Mirfaze  Fallah ⁴ (Department of Financial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran and member of Modern Financial Risk Research Group)

Received: 2022-04-12 Accepted : 2022-08-17 Published : 2023-06-22

Keywords: "Financial Crisis", "Systemic risk", "Liquidity risk", "systemic liquidity risk indicator(SLRI)", "multivariate GARCH models",

Abstract :

This research aims to model and present an appropriate pattern in order to forecast systemic liquidity risk of corporate stocks in capital market of Iran. For this purpose, 486 listed companies in Tehran stock exchange and OTC from 2011 to 2020 were sampled and then the companies were divided into four groups (portfolios) according to combination of indicators and types of activites of companies. Then by using types of multivariate GARCH models and comparing them, finanlly the VAR(1)-DBEKK(1,2) was selected as an optimum pattern . The results of research showed significant relationships among of liquidity shocks and volatilities with all of subsections, and consequently the main hypothesis based on “presence of systemic liquidity risk of corporate stocks in capital market of Iran” was accepted. In a way that the portfolios of company stocks with a “low level of liquidity- industry section” and “low level of liquidity- financial section” respectively had maximum and minimum liquidity shocks transmission of effects on future returns of the other portfolios, as well as the portfolio with a “high level of liquidity- financial section” had maximum volatility persistence and liquidity risk transmission to other portfolios.