The Interaction between the Stock Market and Macroeconomic Policy Variables in South Africa

Ntshangase, Khanyisa; Mingiri, Kapingura Forget; Palesa, Makhetha-Kosi

doi:10.1080/09765239.2016.11907815

Cited by 10 publications

(8 citation statements)

References 1 publication

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“…Where ΔY t = Y t −Y t−1 ;Y t−1 = Y t−1 −Y t−2 ; Δ is the difference operator; α is the constant; β is the coefficient on-time trend t ; ρ represents the number of lag, empirically determined using the Schwarz information criterion (SIC); and e t is the error term with zero mean and variance. The coefficient term Y t−1 is later included in testing the coefficient’s significance ( MacKinnon et al, 1999 ; Ntshangase et al, 2016 ; Naseem et al, 2019 ). The augmenting process is completed with the possible removal of autocorrelation among error terms.…”

Section: Methodsmentioning

confidence: 99%

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

2021

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The rapid worldwide spread of COVID-19 forced many countries to enforce complete lockdown and strict quarantine policies. The strict lockdown and quarantine affect the psychological state of people toward cryptocurrency. The current research aims to examine the effect of COVID-19 on Bitcoin prices concerning cumulative deaths and confirmed cases. The research comprises daily data from January 20, 2020, to April 30, 2020, during the initial worldwide breakout of COVID-19. This research employed the augmented Dickey-Fuller test to check the stationarity of data, the co-integration test for the interdependency of variables, and the vector error correction model for identifying the direction and long or short-run relationship between Bitcoin prices and COVID-19. The research results show that Bitcoin prices are negatively significant and related to COVID-19 in the short-run. A unidirectional relationship between Bitcoin prices and cumulative deaths is also observed. Investors and the public’s psychological state were positively significant to Bitcoin prices in the long-term because of cashless transactions, unbanked, and less risky virus traveling. The second reason behind the positive psychological relation is un-centralization and easy-to-make payments by Bitcoin. This study’s finding provides timely evidence to decision-makers on Bitcoin price volatility and its impacts on the public’s psychological states regarding COVID-19.

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Section: Methodsmentioning

confidence: 99%

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

2021

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“…However, this study with a set of modified micro and macroeconomic variables and 2016 data needs to be replicated in Nigeria with a view to ascertaining position. Ntshangase, Mingiri and Palesa (2016) empirically explore the relationship between the stock market and macroeconomic variables in South African from 1994 to 2012. The independent variables of interest are inflation, interest rate, money supply, exchange rate and government expenditure.…”

Section: Money Supply and Stock Returnsmentioning

confidence: 99%

Effects of Macroeconomic Factors on Stock Returns in Nigeria

Ayuba¹,

Balago²,

Dagwom³

2018

IJFA

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Purpose: This study set out to examine the effects of macroeconomic factors on stock returns for top twenty-five most capitalized quoted equity firms in Nigeria. Emerging markets have different structure and institutional characteristics from developed stock markets, and in view of the fact that investors are interested in getting more insights into the activities of blue chip companies, it is imperative to find out whether stock returns in Nigeria respond differently to effects of macroeconomic factors or not. Hence, the study investigated the effects of inflation rate, interest rate and money supply on stock returns of selected quoted firms in Nigeria from 2007 – 2016. Methodology: The population comprises top twenty-five most capitalized quoted equity firms, out of which twenty-one companies represent the sample of the study. The study adopted ex-post facto research design. The study used secondary data obtained from the audited accounts of the sampled firms, Central Bank of Nigeria Statistical Bulletin and the Nigerian Stock Exchange database and website. Analysis of data was carried out using panel data regression. Findings: The panel regression results indicate significant negative effects between inflation rate, money supply and stock returns of selected quoted companies in Nigeria, while insignificant negative effect is revealed between interest rate and stock returns in Nigeria. Unique contribution to theory, practice and policy: The study recommends among others, taking note of the systematic risks revealed by inflation rate, interest rate and money supply when structuring portfolios and diversification strategies; and intensifying capital market sensitization campaigns by the Securities and Exchange Commission. Keywords: Inflation rate, interest rate, money supply and stock returns.

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“…This research is also employed the ADF test for unit root by the following equation:

where

;

is difference operator;

is constant,

is coefficient on-time trend

represents that the number of lags is empirically determined using Schwarz information criteria (SIC), and

is an error term with zero mean and variance. The coefficient term

is included later for testing the significance of coefficient [ 35 , 36 , 37 ]. The augmenting process is completed with the possible removal of autocorrelation among error terms.…”

Section: Methodsmentioning

confidence: 99%

The Causes of Occupational Accidents and Injuries in Romanian Firms: An Application of the Johansen Cointegration and Granger Causality Test

Ivaşcu

Sarfraz

Mohsin

et al. 2021

IJERPH

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Organizational risks are present in any activity, so it is important to manage them properly. The jobs are dynamic and involve a series of processes and activities. The entire human resource is exposed to several risks. If these risks are approached correctly, the organizational capacity to achieve its objectives and vision will increase considerably. This paper aims to investigate the relationships between work accidents (fatal and non-fatal) and the causes that contribute to their occurrence (causes dependent on the executor, causes dependent on the means of production, workload-dependent causes, and work-dependent causes—the work environment). The augmented Dickey–Fuller (ADF) test is employed to check the data stationarity series, while the Johansen test determines the cointegration relation of variables. The data have been collected from Romanian organizations. The vector error correction model (VECM) and Granger causality test are applied for speed of adjustment, nature, and direction of variables’ relationship. This research demonstrated that both data series are free from the unit-root problem at first difference. The lag length criterions select the third lag for model fitness, and Johansen cointegration declares that variables are cointegrated for the long term. The vector error correction model shows the speed of adjustment from the short to the long run is 83.35% and 42.60% for work and fatal accidents. The study results show that fatal accidents have a series relationship with selected cases for the short run and have a long-run relationship with the means of production. Fatal accidents are directly related to means of production. Fatal accidents are not designed by executors, workload-dependent causes, or work environments in the short run. Fatal accidents are directly related to the means of production and sudden incidents happening in the long run. Fatal accidents are considered by executors, workload-dependent causes, or work environments in the short run. In the long run, fatal accidents are directly related to the means of production and sudden incidents happening.

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The Interaction between the Stock Market and Macroeconomic Policy Variables in South Africa

Cited by 10 publications

References 1 publication

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

Effects of Macroeconomic Factors on Stock Returns in Nigeria

The Causes of Occupational Accidents and Injuries in Romanian Firms: An Application of the Johansen Cointegration and Granger Causality Test

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