price index
Recently Published Documents


TOTAL DOCUMENTS

1971
(FIVE YEARS 649)

H-INDEX

41
(FIVE YEARS 6)

2022 ◽  
Vol 10 (4) ◽  
pp. 595-604
Author(s):  
Endah Fauziyah ◽  
Dwi Ispriyanti ◽  
Tarno Tarno

The Composite Stock Price Index (IHSG) is a value that describes the combined performance of all shares listed on the Indonesia Stock Exchange. JCI serves as a benchmark for investors in investing. The method used to predict future conditions based on past data is forecasting . Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) is amodel time series that can be used for forecasting. Financial data has high volatility which causes the variance of the residual model which is not constant (heteroscedasticity). ARCH / GARCH model is used to solve the heteroscedasticity problem in the model. If the data is heteroscedastic and asymmetric, then the model can be used Threshold Autoregressive Conditional Heteroskedasticity (TARCH). The data used are the Composite Stock Price Index (IHSG) for the January 2000 - April 2020 period and the dollar exchange rate data for the January 2000 - April 2020 period asvariables independent from the ARIMAX model. The best model used to predict the JCI from the results of this study is the ARIMAX (1,1,0) -TARCH (1,2) model with an AIC value of -0.819074. 


2022 ◽  
Vol 15 (1) ◽  
pp. 31
Author(s):  
Tetsuya Takaishi

This study investigates the time evolution of market efficiency in the Japanese stock markets, considering three indices: Tokyo Stock Price Index (TOPIX), Tokyo Stock Exchange Second Section Index, and TOPIX-Small. The Hurst exponent reveals that the Japanese markets are inefficient in their early stages and improve gradually. TOPIX and TOPIX-Small showed an anti-persistence around the year 2000, which still persists. The degree of multifractality varies over time and does not show that the Japanese markets are permanently efficient. The multifractal properties of the Japanese markets changed considerably around the year 2000; this may have been caused by the complete migration from the stock trading floor to the Tokyo Stock Exchange’s computer trading system and the financial system reform, also known as the “Japanese Big Bang”.


SISTEMASI ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 171
Author(s):  
Melisa Winda Pertiwi ◽  
Mira Kusmira ◽  
Rezkiani Rezkiani ◽  
Bambang Kelana Simpony ◽  
Yanti Apriyani ◽  
...  

Author(s):  
Agus Munandar ◽  
Aulia Safira ◽  
Edwin Wiguna

This article analyzes the impact of stock price efficiency on the Covid-19 event in 2020. As a capital market tool, shares are interpreted as evidence that a person has equity participation in a company or limited liability company. The emergence of the impact of Covid-19 on the price index is detrimental to the country's economy. State-Owned Enterprises (BUMN), which are the drivers of economic growth, has also been affected by the Covid-19 pandemic. This analysis needs to be carried out to find out the impact of Covid-19 on the stock price of IDX BUMN20 regarding the effects before and before the outbreak of the Covid-19 virus in Indonesia in 2020. The research method used is exploratory descriptive with a quantitative approach and the data collected is descriptive. Secondary data from the IDX and the Central Statistics Agency regarding the condition of economic growth and the SOE stock price index in 2020. Based on the results obtained, the first conclusion is that Indonesia's economic growth from 2019 was 5.02% and in 2020 was 2.07%, so that economic growth decreased from 2019 to 2020 by 2.95. Furthermore, the IDX BUMN20 stock index also fell to 18.39% throughout 2020.


2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Yi Sun ◽  
Hua Li

This study takes 8 cities in Shaanxi province as the research object and uses the multilayer linear model specifically for nested structure data to introduce the urban macroexplanatory variables on the basis of individual level of residents and influence the willingness of urban residents to pay for forest ecological services. The factors are analyzed in multiple layers to find out the prediction effect on ecological payment, and on this basis, corresponding countermeasures and suggestions are put forward. The results show that regional differences have a significant impact on residents’ willingness to pay for forest ecological services; individual characteristics and regional characteristics can independently have a significant impact on residents’ willingness to pay; after introducing macrolevel variables, individual-level environmental awareness and per capita income, five variables, such as education level, place of residence, and age, have significant predictive effects on residents’ willingness to pay; among them, the interaction between consumer price index and environmental awareness is the largest, followed by the interaction between consumer price index and age. Per capita social security is the interaction between expenditure and environmental awareness. Finally, that is the interaction between the per capita social security expenditure and age and the interaction between the average salary of employees and the monthly per capita income.


Economies ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 17
Author(s):  
Hersugondo Hersugondo ◽  
Imam Ghozali ◽  
Eka Handriani ◽  
Trimono Trimono ◽  
Imang Dapit Pamungkas

This study aimed to predict the JKII (Jakarta Islamic Index) price as a price index of sharia stocks and predict the loss risk. This study uses geometric Brownian motion (GBM) and Value at Risk (VaR; with the Monte Carlo Simulation approach) on the daily closing price of JKII from 1 August 2020–13 August 2021 to predict the price and loss risk of JKII at 16 August 2021–23 August 2021. The findings of this study were very accurate for predicting the JKII price with a MAPE value of 2.03%. Then, using VaR with a Monte Carlo Simulation approach, the loss risk prediction for 16 August 2021 (one-day trading period after 13 August 2021) at the 90%, 95%, and 99% confidence levels was 2.40%, 3.07%, and 4.27%, respectively. Most Indonesian Muslims have financial assets in the form of Islamic investments as they offer higher returns within a relatively short time. The movement of all Islamic stock prices traded on the Indonesian stock market can be seen through the Islamic stock price index, namely the JKII (Jakarta Islamic Index). Therefore, the focus of this study was predicting the price and loss risk of JKII as an index of Islamic stock prices in Indonesia. This study extends the previous literature to determine the prediction of JKII price and the loss risk through GBM and VaR using a Monte Carlo simulation approach.


2021 ◽  
Vol 27 (4) ◽  
pp. 21-40
Author(s):  
Young-Sun Song ◽  
Hye-Young Shin ◽  
Chang-Moo Lee
Keyword(s):  

2021 ◽  
Vol 2 (1) ◽  
pp. 1-7
Author(s):  
Syintya Febriyanti ◽  
Wahyu Aji Pradana ◽  
Juliana Saputra Muhammad ◽  
Edy Widodo

The Consumer Price Index (CPI) is an indicator that is often used to measure the inflation rate in an area, or can be interpreted as a comparison between the prices of a commodity package from a group of goods or services consumed by households over a certain period time. The spread of COVID-19 throughout the world affects the economy in Indonesia, especially Yogyakarta. Forecasting CPI data during the COVID-19 pandemic has the benefit of being an illustration of data collection in the CPI of D.I Yogyakarta Province in the predicted period. This is useful as a comparison with the original data at the time of data collection and publication, as well as a consideration in making policies and improving the economy. Researchers use the Double Exponential Smoothing (DES) method to predict the CPI of Yogyakarta D.I Province, which aims to determine the best forecasting model and forecasting results. This method is rarely used in research on CPI data forecasting in Yogyakarta. The data in this study are monthly data from March 2020 to August 2021. The highest CPI in Yogyakarta occurred in August 2021 at 107.21 or 107.2, while the lowest CPI in Yogyakarta occurred in April 2020 at 105.15 or 105.2. The average CPI in Yogyakarta per month is 106.1. The Mean Absolute Percentage Error (MAPE) value obtained from the DES method is 0.1308443%, so that the accuracy of the model is 99.869%. Forecasting with the DES method is quite well used in forecasting the CPI data of Yogyakarta in September 2020 - November 2021. The results of CPI forecasting in Yogyakarta using the DES method were 107.2602, 107.3104, and 107.3606 from September-November.


Sign in / Sign up

Export Citation Format

Share Document