The dynamics and determinants of liquidity connectedness across financial asset markets

The Dynamic Volatility Connectedness of Major Environmental, Social, and Governance (ESG) Stock Indices: Evidence Based on DCC-GARCH Model

“…The rapid development of ESG theme has sparked interest from both investment professionals and academics, this study takes motivation from the ongoing research initiatives that explores ESG indices and comprehend how they vary from the conventional indices. Numerous studies have been conducted on the theme of investment contagion and connectivity and how volatility spreads and contagions across conventional assets like stocks, commodities, currencies among others (Akhtaruzzaman & Shamsuddin, 2016 ; Liew et al, 2022 ; Malik & Umar, 2019 ; Singh et al, 2021 ; Tiwari et al, 2018 ; Umar et al, 2019 ; Yang et al, 2021 ). But there is there is paucity of research investigations on ESG connectedness.…”

Equity super sectors connectedness and its determinants: evidence from the Johannesburg Stock Exchange.

“…Hence, the state of fundamentals may nonetheless explain why some economies are susceptible to crises while others are not. An economy is at risk, for instance, if contagion spreads due to liquidity problems (Liew, Lim & Goh 2022), because of its low number of international reserves in comparison to its short-term liabilities denominated in foreign currencies. The findings in the Forbes and Rigobon (2000) study align with the above definition.…”

“…First the rolling window approach will need to determine the width of the rolling window which often times is an arbitrary figure with little or no statistical background (Liew, Lim & Goh 2022). Second, the rolling window analysis has the tendency to lose some number of observations, which is often equal to the width size and lastly, the rolling-window approach does not allow the identification of data points that contribute to a spike or a dip in the connectedness index within a specific window (Antonakakis & Gabauer, 2017;Antonakakis et al 2018;Gabauer & Gupta, 2018;Korobilis & Yilmaz, 2018).…”

“…In addition, the results showed that macroeconomic conditions such as the term spread and interest rate are important, especially at the middle and lower quantiles, while crude oil market uncertainties intensify the return spillover at the left tail. The outcome of the results indicates a positive decision making particularly with regards to the stability of the system of return connectedness within the clean energy and dirty energy markets during extreme occurrences Liew, Lim and Goh (2022). estimated the total liquidity connectedness of stock, bond, money and foreign exchange markets in Malaysia, thereafter they investigated the determinants on liquidity connectedness using the ordinary least squared with heteroscedasticity and autocorrelation corrected errors with monetary policy uncertainty index, implied volatility of the Chicago Board of Options, the TED spread measured as the difference between the 3-month U.S Treasury bill rate and the 3-months U.S dollar London Interbank Overnight Rate, the West Texas Intermediate crude oil price index and the global real economic activity index…”

“…The choice of daily data is because it allows to detect immediate response to new event (Shen, Jiang, Ma, Wang and Zhou 2020). Further monthly data on (South Africa Volatility Index (SAVI), Domestic Asset Market Return (DAMR), Economic Policy Uncertainty (EPU), Trade Openness (TO), Manufacturing Output and macroeconomic variables such as Money Supply (M2) would be obtained from Statistics SA and SA Reserve Bank for the purpose of objective four.FollowingShahzad, Kayani, Raza, Shah and Yahyee (2018) andLiew, Lim and Goh (2022), monthly average of the daily sectorial total volatility connectedness index would be generated and employed as the dependent variable for objective 4, denoted as 𝐺 𝑡 𝐶𝑜𝑛 𝑇 in equation 3.7.1.7.The choice of this data period is that the data covers not only the 2017 to 2019 U.S-China trade war, but also covers the global financial crisis periods such as 2008/2009 financial crisis, European debt crisis of 2009/2012 and the COVID-19 pandemic, which allows the study to compare the risk contagion behaviours triggered by these events in the South African economic sectors. The daily returns of each super sector would be computed from their price indices following(Zhang, Zhuang, Wang and Lu.…”