TIME-VARYING CORRELATIONS AND STOCK MARKET CO-MOVEMENTS: EVIDENCE FROM SOUTH AFRICA AND ITS MAJOR TRADING PARTNERS

2015 ◽  
Vol 15 (2) ◽  
pp. 37-48
Author(s):  
George Ogum
Keyword(s):  
South Africa ◽  
Stock Market ◽  
Time Varying ◽  
Trading Partners

scholarly journals The Assessment Of Market Risk Premium In South Africa

2010 ◽  
Vol 26 (6) ◽  
Author(s):  
Lumengo Bonga-Bonga
Keyword(s):  
South Africa ◽  
Stock Market ◽  
Stock Returns ◽  
South African ◽  
Risk Premium ◽  
Stock Exchange ◽  
Time Varying ◽  
The South ◽  
Stock Market Returns ◽  
Premium Model

<p class="MsoNormal" style="text-indent: 0in; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt;" lang="EN-GB">This paper makes use of time-varying parameter GARCH-M model to estimate the risk aversion parameter for the South African stock market. The paper further compares the forecasts performance of a time-varying risk premium model with that of a constant risk premium model in predicting stock market returns on the South African stock exchange. The findings of the paper show that risk premium is time varying and indicate that stock market in South Africa is vulnerable to external shocks. Moreover, the paper finds that the time-varying GARCH-M model outperforms the fixed parameter GARCH-M model in predicting stock returns when short-term forecast horizons are used. </span></p>

RESPONSE OF STOCK MARKET DURING COVID-19 AND 2008 FINANCIAL CRISIS: A COMPARATIVE EVIDENCE FROM BRICS NATIONS

2021 ◽  
pp. 1-24
Author(s):  
SANJEEV KUMAR ◽  
JASPREET KAUR ◽  
MOSAB I. TABASH ◽  
DANG K. TRAN ◽  
RAJ S DHANKAR
Keyword(s):  
South Africa ◽  
Financial Crisis ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
2008 Financial Crisis ◽  
First Case ◽  
Egarch Model ◽  
The 2008 Financial Crisis ◽  
The Impact

This study attempts to examine the response of stock markets amid the COVID-19 pandemic on prominent stock markets of the BRICS nation and compare it with the 2008 financial crisis by employing the GARCH and EGARCH model. First, average and variance of stock returns are tested for differences before and after the pandemic, t-test and F-test were applied. Further, OLS regression was applied to study the impact of COVID-19 on the standard deviation of returns using daily data of total cases, total deaths, and returns of the indices from the date on which the first case was reported till June 2020. Second, GARCH and EGARCH models are employed to compare the impact of COVID-19 and the 2008 financial crisis on the stock market volatility by using the data of respective stock indices for the period 2005–2020. The results suggest that the increasing number of COVID-19 cases and reported death cases hurt stock markets of the five countries except for South Africa in the latter case. The findings of the GARCH and EGARCH model indicate that for India and Russia, the financial crisis of 2008 has caused more stock volatility whereas stock markets of China, Brazil, and South Africa have been more volatile during the COVID-19 pandemic. The study has practical implications for investors, portfolio managers, institutional investors, regulatory institutions, and policymakers as it provides an understanding of stock market behavior in response to a major global crisis and helps them in taking decisions considering the risk of these events.

scholarly journals Predicting stock market movements with a time-varying consumption-aggregate wealth ratio

2019 ◽  
Vol 59 ◽  
pp. 458-467 ◽  
Author(s):  
Tsangyao Chang ◽  
Rangan Gupta ◽  
Anandamayee Majumdar ◽  
Christian Pierdzioch
Keyword(s):  
Stock Market ◽  
Time Varying ◽  
Aggregate Wealth

scholarly journals The Symmetric and Asymmetric Time-Varying Causality Relationships Between the COVID-19 Outbreak and the Stock Exchange: The Case of Selected Countries

Ekonomika ◽  
2021 ◽  
Vol 100 (2) ◽  
pp. 144-170
Author(s):  
Cuma Demirtaş ◽  
Munise Ilıkkan Özgür ◽  
Esra Soyu
Keyword(s):  
Mortality Rate ◽  
Stock Market ◽  
Stock Markets ◽  
Time Varying ◽  
Causality Test ◽  
Causality Tests ◽  
Bed Capacity ◽  
Case Rate ◽  
Asymmetric Causality ◽  
Second Wave

In this study, the effects of COVID-19 (mortality rate, case rate, and bed capacity) on the stock market was examined within the framework of the efficient market hypothesis. Unlike other studies in the literature, we used the variable of bed capacity besides the mortality rate and case rate variables. The relationship between the mentioned variables, using daily data between December 31 of 2019 and November 10 of 2020, has been analyzed with time-varying symmetric and asymmetric causality tests for China, Germany, the USA, and India. Considering that the responses to positive and negative shocks during the pandemic process may be different and that the results may change depending on time, time-varying symmetric and asymmetric causality tests were used. According to the time-varying symmetric causality test, stock markets in all countries were affected in the period when the cases first appeared. A causal relationship between COVID-19 and country stock markets was found. The results showed that the effects of the case rate and bed capacity on the stock market occurred around the same time in Germany and the United States; however, these dates differed in China and India. According to time-varying asymmetric causality test findings, the asymmetric effect of the pandemic on the stock market in countries emerged during the second wave. The findings showed that the period during which positive and negative information about the pandemic intensified coincided with the period during which the second wave occurred; besides, the results show the effect of this information on the stock market differed as positive and negative shocks.

scholarly journals Supply chain cost improvement opportunities through streamlining cross-border operations

2013 ◽  
Vol 3 (3) ◽  
pp. 28-34
Author(s):  
Jan Hendrik Havenga ◽  
J. van Eeden ◽  
Wessel Pienaar
Keyword(s):  
South Africa ◽  
Supply Chain ◽  
Cost Model ◽  
Road Transport ◽  
Demand Model ◽  
Logistics Cost ◽  
Cross Border ◽  
Cost Impact ◽  
Product Profile ◽  
Trading Partners

The Cross-Border Road Transport Agency (CBRTA) in South Africa aims to encourage and facilitate trade between South Africa and its neighbouring countries. The CBRTA sponsored a study by Stellenbosch University (SU) to determine the logistics cost impact of cross-border delays between South Africa and its major neighbouring trading partners, and prioritise opportunities for improvement. SU is the proprietor of both a comprehensive freight demand model and a logistics cost model for South Africa, which enable extractions and extensions of freight flows and related costs for specific purposes. Through the application of these models, the following information is identified and presented in this paper: South Africa’s most important border posts (based on traffic flows); a product profile for imports and exports through these border posts; the modal split (road and rail); the annual logistics costs incurred on the corridors feeding the border posts, as well as the additional costs incurred due to border delays. The research has proved that the streamlining of border-post operations that take a total supply chain view (i.e. of both border operations and those that could be moved from the border) is beneficial.

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