Does the South African Reserve Bank follow a nonlinear interest rate reaction function?

2013 ◽  
Vol 35 ◽  
pp. 272-282 ◽  
Author(s):  
Yosra Baaziz ◽  
Moez Labidi ◽  
Amine Lahiani
Keyword(s):  
Interest Rate ◽  
South African ◽  
Reaction Function ◽  
The South ◽  
Reserve Bank

Is the monetary policy behaviour of the South African Reserve Bank nonlinear

2021 ◽  
Vol 24 (2) ◽  
pp. 193
Author(s):  
Imhotep Paul Alagidede ◽  
Abdul Aziz Iddrisu
Keyword(s):  
Monetary Policy ◽  
South African ◽  
The South ◽  
Reserve Bank

scholarly journals An explanatory model of South African yellow maize futures prices

2012 ◽  
Vol 9 (3) ◽  
pp. 204-216
Author(s):  
S. Van Tonder ◽  
J.H. Van Rooyen
Keyword(s):  
South African ◽  
Goodness Of Fit ◽  
Information Service ◽  
Global Market ◽  
Futures Prices ◽  
The South ◽  
Weather Index ◽  
Significance Level ◽  
Ex Post ◽  
Reserve Bank

This study attempts to identify the important variables that may affect yellow maize futures prices in the South African derivatives market. Data was obtained from the South African Futures Exchange, a division of the Johannesburg Securities Exchange. Weekly data on the rand-dollar exchange rates were obtained from the South African Reserve Bank (SARB). Monthly data regarding import volumes, export volumes, maize consumption and maize stocks in South Africa are available from South African Grain Information Service (SAGIS). Fifteen variables that may be used to forecast futures prices were identified from theory and similar studies. A correlation matrix of these variables with maize futures prices was determined at the 5% significance level. After applying various statistical analyses to test for autocorrelations, stationarity etc., only four variables were left with which to model the futures prices. The R2 of the remaining variables was only 12.21%, indicating a low goodness of fit. Applying the regression model to the ex-post prices clearly indicated that these variables that were identified do not adequately explain the movement in the futures prices. The primary reasons for the low accuracy of the model may be due to the use of the weather index for SA alone (a small contributor in a global market) and the linearity assumption underlying the selected dependant and independent variables may also be unrealistic. Further research is therefore needed to identify more appropriate variables with which to model yellow maize futures prices.

scholarly journals A modelling process of short-term interest rate risk management for the South African commercial banking sector

2011 ◽  
Vol 9 (1) ◽  
pp. 628-637
Author(s):  
Jiaqi Sun ◽  
J.H. Van Rooyen
Keyword(s):  
Interest Rate ◽  
South African ◽  
Inflation Targeting ◽  
Banking Sector ◽  
Empirical Finding ◽  
Interest Rate Risk ◽  
Commercial Banking ◽  
The South ◽  
Short Term ◽  
Rate Risk

This study focuses on banking book interest rate risk (IRR) management, more specifically short-term IRR management (SIRR). This type of risk is partly induced by the inflation targeting policy of the South African Reserve Bank (SARB). As a result, inflation leads to an uncertain interest rate cycle and a period of uncertain interest rate levels as it relates to lending and borrowing activities in the South African commercial banking sector. This study highlights what causes short-term interest rate risk and how the banks may forecast and manage the SIRR with reference to the inflation targeting policy. The banking industry manages a high volume of fund transactions and portfolios of investments. The banks are intricately involved in the financial markets and are therefore exposed to a large number of risk factors. A sound banking system is an important prerequisite for a country’s future economic development. One key empirical finding of this research is that 50 per cent of the South African banks agree that loans that cannot undergo immediate rate adjustments are exposed to the repo-rate adjustment after the Monetary Policy Committee (MPC) meeting. Banks surveyed see the need for the development of a short-term interest rate risk (SIRR) management process to better control such repo-rate risk. The next key empirical finding is that interest rate risk is still managed via traditional repricing gap and sensitivity analysis which is not ideal for risk management due to inherent weaknesses (such as not quantifying capital risk exposure). This agrees with the Pricewaterhousecoopers Balance Sheet Management benchmark survey

scholarly journals The South African Reserve Bank

1921 ◽  
Vol 31 (122) ◽  
pp. 172
Author(s):  
Henry Strakosch
Keyword(s):  
South African ◽  
The South ◽  
Reserve Bank

scholarly journals The Determinants of Interest Rate Spreads in South Africa: A Cointegration Approach

2015 ◽  
Vol 7 (2(J)) ◽  
pp. 101-108
Author(s):  
Ferdinand Niyimbanira ◽  
Sanderson Sabie Kuyeli . ◽  
Koleka Rangaza .
Keyword(s):  
South Africa ◽  
Interest Rate ◽  
South African ◽  
Policy Implications ◽  
Future Research ◽  
The South ◽  
Reserve Requirements ◽  
Explanatory Variables ◽  
Interest Rate Spreads ◽  
The Interest Rate

This study empirically identifies the determinants of interest rate spreads (IRS) in South Africa over the period 1990 to 2012. The study uses the Johansen Cointegration Approach and Vector ErrorCorrection techniques to identify the variables in explaining the interest rate spreads in South Africa. It considers the inflation rate, reserve requirements, Treasury bill, discount rate, money supply (M2) and gross domestic product per capita variables as they explain the movement of interest rate spreads. A significant short-run relationship between IRS and its explanatory variables was observed. These macroeconomic variables are significant in explaining the behavior of the South African IRS in the longrun. This paper has focused on illuminating on how the interest rate spreads are impacted by both exogenous and endogenous variables. If controlled, these variables are most likely to have the largest effects on reducing such spreads. In addition, it suggests that the reduction in the reserve requirements prescribed by the South African Reserve Bank would help to reduce the interest rate spreads. Based on the results of the study, policy implications and suggestion for future research are made.

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