Suchergebnisse

Bonds are chosen by investors as investment instruments because they have a fixed return in the form of interest or coupon bonds and yields with a low level of risk. The purpose of this study was to determine the relationship and influence of bond age, interest rates and inflation on bond yields. The methodology used in this study is quantitative research design. The sample of this study is conventional government bonds listed on the IDX in 2018 determined using the purposive sampling method. Data analysis method used in this research is quantitative data analysis to calculate and estimate quantitatively some independent variables on the dependent variable partially or simultaneously. The results in this study indicate that partially the age of bonds does not have a significant effect on government bond yields, partially the interest rate has a significant effect on government bond yields and partially inflation does not have a significant effect on government bond yields. While simultaneously the age of bonds, interest rates and inflation have a significant effect on the yield of government bonds listed on the IDX in 2018.

Abstract
This paper investigates the relationship between inflation and economic growth for South Africa and Ghana using quarterly empirical data collected from 2001 to 2016 applied to the quantile regression method. For our full sample estimates we find that inflation is positively related with growth in Ghana at high inflation levels whilst inflation in South Africa exerts its least adverse effects at high inflation levels. However, when particularly focusing on the post-crisis period, we find inflation exerts negative effects at all levels of inflation for both countries with inflation having its least adverse effects at high levels for Ghana and at moderate levels for South Arica. Based on these findings bear important implications for inflation targeting frameworks adopted by Central Banks in both countries.

Inflation occurs where there is an increase in the price of goods or services in general and continuously in a country. Uncontrolled inflation will have an impact on the decline of the Indonesian economy. Therefore, the prediction of future inflation levels is necessary for the government to develop economic policies in the future. Prediction of inflation levels can be done by studying historical past Consumer Price Index (CPI) data. Regression methods are often used to solve prediction problems. The problem of finding the optimal prediction model can be seen as an optimization problem. Genetic algorithms are often used to deal with optimization problems. Thus, this work proposed to use a genetic algorithm-based regression model for predicting inflation levels. The model was trained and evaluated using real CPI data which obtained from the Indonesian Central Bank. Based on the experiment, it is proved that the proposed model is effective in predicting the inflation level as it gains MSE of 0.1099.

The purpose of this paper is to make a quantitative contribution to the inflation versus price level targeting debate. It considers a policy-maker that can set policy either through an inflation targeting rule or a price level targeting rule to minimize a quadratic loss function using the actual projection model of the Bank of Canada (ToTEM). The paper finds that price level targeting dominates inflation targeting, although it can lead to much more volatile inflation depending on the weight assigned to output gap stabilization in the loss function. The price level targeting rule is also found to mimic the full-commitment solution quite well. There is, however, an important difference: the full-commitment solution does not require stationarity in the price-level. The paper then analyzes the extent to which the results are sensitive to Hansen and Sargent (2004) model uncertainty. The paper finds the price level targeting rule to be robust; its performance deteriorates slower than the inflation targeting rule and the absolute decline in performance is small in magnitude.