scholarly journals PEMODELAN REGRESI SEMIPARAMETRIK DENGAN PENDEKATAN DERET FOURIER (Studi Kasus: Pengaruh Indeks Dow Jones dan BI Rate Terhadap Indeks Harga Saham Gabungan

2020 ◽  
Vol 9 (1) ◽  
pp. 50-63
Author(s):  
Laili Rahma Khairunnisa ◽  
Alan Prahutama ◽  
Rukun Santoso
Keyword(s):  
Fourier Series ◽  
Stock Price ◽  
Price Index ◽  
Semiparametric Regression ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
K Value ◽  
Sample Data ◽  
Stock Price Index

The Composite Stock Price Index (CSPI) is a composite index all of types of shares listed on the stock exchange and their movements indicate conditions that occur in the capital market. CSPI is influenced by macroeconomic factors and foreign exchange index. Dow Jones Industrial Average has a linear relationship with CSPI and BI Rate has a repeated relationship with CSPI, so the method is used semiparametric regression with the Fourier series approach. Estimators in semiparametric regression with Fourier series approach were obtained by the Ordinary Least Square (OLS) method. This study uses monthly data which is divided into in sample data and out sample data. Semiparametric regression modelling with Fourier series approach is done by determining the optimal K value which results in a minimum General Cross Validation (GCV) value. In this study, semiparametric regression model with Fourier series approach formed by the optimal K value is 13 and GCV is 2826122. The results of the evaluation of the accuracy of the model performance and forecasting obtained the coefficient of determination is 0,9226, Mean Absolute Percentage Error (MAPE) data in sample 3,8154% and data out sample is 8,4782% which shows that the model obtained has a very accurate performance.Keywords: Composite Stock Price Index (CSPI), Semiparametric Regression, Fourier Series, OLS, GCV

scholarly journals ANALISIS FAKTOR PENENTU INDEKS HARGA SAHAM GABUNGAN DI INDONESIA

2019 ◽  
Vol 1 (4) ◽  
pp. 37
Author(s):  
Yulizar Fikri ◽  
Ali Anis
Keyword(s):  
Economic Growth ◽  
Foreign Exchange ◽  
Stock Price ◽  
Price Index ◽  
Time Series Data ◽  
Secondary Data ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Foreign Exchange Reserves ◽  
Stock Price Index

This study aims to determine the analysis of the determinants of the composite stock price index in Indonesia. The independent variables in this study are inflation as X1, foreign exchange reserves as X2, exchange rates as X3, and economic growth as X4, and the dependent variable of the composite stock price index as Y. The data used are secondary data in the formof time series data from 2010Q1 until 2019Q2, with data collection techniques, namely documentation from Bank Indonesia publications, the Central Statistics Agency, investing. comsite and library research. The research methods used are: (1) Multiple Linear Regression, (2) Classical Assumption Test (3) coefficient of determination. The results of this study indicate that:(1) inflation does not significantly influence the composite stock price index. (2) foreign exchange reserves have a significant positive effect on the composite stock price index. (3) the rupiah exchange rate has an influence on the composite stock price index and (4) economic growth hasno significant effect on the composite stock price index.

scholarly journals Analisis Pengaruh Variabel Makro Ekonomi terhadap Nilai Aktiva Bersih Reksadana Saham Syariah Periode 2015-2019

2021 ◽  
Vol 1 (2) ◽  
pp. 332-348
Author(s):  
Hani Nurrahmawati ◽  
Hasbi Assidiki Mauluddi ◽  
Endang Hatma Juniwati
Keyword(s):  
Exchange Rate ◽  
Mutual Funds ◽  
Stock Price ◽  
Price Index ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Asset Value ◽  
Net Asset Value ◽  
Net Assets ◽  
Stock Price Index

The title of this research is Analysis Influence of Macroeconomic to Net Asset Value of Islamic Mutual Fund Equity period 2015-2019. The purpose of this study is to determine the effect of partially and simultaneously variables of BI Rate, Inflation, Composite Stock Price Index and Exchange Rate on Net Asset Value of Sharia Mutual Funds in Indonesia in the period January 2015 - December 2019. The dependent variable is Net Asset Value of Sharia Mutual Funds, while the independent variables are BI Rate, Inflation, Composite Stock Price Index and Exchange Rate.Types of data used in this study are secondary data sourced from OJK, IHSG-IDX and BI published between 2015-2019. All of the data will be processed panel data which is a combination of time series data and cross section data. The results of this research showed that in the partial just variables of the BI Rate, Inflation, Composite Stock Price Index and Exchange Rate influenced to Net Assets Value of Islamic Mutual Funds in Indonesia, and simultaneous from variables of the BI Rate, Inflation, Composite Stock Price Index and Exchange Rate influenced to Net Assets Value of Islamic Mutual Funds in Indonesia and the value of Adjusted R-square coefficient of determination is 0.311175 means in togetherness variables of the BI Rate, Inflation, Composite Stock Price Index and Exchange Rate have a contribution influenced NAV of Islamic Mutual Funds in the amount of 31%, while the rest is 69% influenced by other variables that are not included into this research.

scholarly journals Faktor-Faktor Yang Mempengaruhi Pergerakan Indeks Harga Saham Sektoral Pertanian di Bursa Efek Indonesia Periode 2014-2018

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Chikal Galih ◽  
Lies Sulistyowati
Keyword(s):  
Stock Price ◽  
Stock Return ◽  
Price Index ◽  
Composite Index ◽  
Least Square ◽  
Public Companies ◽  
Ordinary Least Square ◽  
Stock Investment ◽  
Index Stock ◽  
Stock Price Index

Indeks Harga Saham Gabungan (IHSG) adalah salah satu indikator perkembangan investasi saham di Indonesia, di mana ada indeks sektor yang mewakili perusahaan publik, salah satu indeks sektoral adalah Indeks Harga Saham Sektoral (IHSS) Pertanian. Fenomena yang terjadi pada periode 2014-2018 adalah tingkat pengembalian investasi di IHSS Pertanian menjadi yang terburuk dibandingkan dengan IHSG dan sektor lainnya sebesar -33,47%. Tujuan dari penelitian ini adalah untuk mengidentifikasi faktor-faktor yang mempengaruhi pergerakan IHSS Pertanian periode 2014 hingga 2018 secara bulanan. Analisis yang digunakan adalah analisis Ordinary Least Square (OLS) untuk mengidentifikasi faktor-faktor yang mempengaruhi pergerakan IHSS Pertanian. Hasil penelitian menunjukkan bahwa inflasi, nilai tukar USD/IDR, suku bunga bank sentral, IHSG, harga minyak kelapa sawit, dan harga emas berpengaruh signifikan terhadap pergerakan IHSS Pertanian dengan nilai pengaruh 88,6%.Kata Kunci: Indeks Harga Saham Sektoral Pertanian, Return Saham, Makroekonomi, Ordinary Least Square (OLS)AbstractJakarta Composite Index (IHSG) is an indicator of the development of stock investment in Indonesia, where there are indices of sectors that represent public companies, one of the sectoral indices is the Sectoral Stock Price Index (IHSS) of Agriculture. The phenomenon that occurred in the 2014-2018 period was the level of investment return in the IHSS of Agriculture being the worst compared to the IHSG and other sectors by -33.47%. The purpose of this study is to identify the factors that influence the movement of IHSS of Agriculture for the period of 2014 up to 2018 on monthly base. The analysis used is Ordinary Least Square (OLS) analysis to identify the factors that influence the movement of IHSS of Agriculture. The results showed that inflation, USD/IDR exchange rate, central bank interest rate, IHSG, palm oil prices, and gold prices significantly influence the movement of IHSS of Agriculture with an influence value of 88.6%. Keywords: Agricultural Sectoral Stock Price Index, Stock Return, Macroeconomics, Ordinary Least Square (OLS).

scholarly journals Pengaruh Inflasi, Suku Bunga Sbi Dan Jumlah Uang Beredar Terhadap Indeks Harga Saham Gabungan (IHSG) Dengan Model Arch-Garch

2021 ◽  
Vol 3 (3) ◽  
pp. 688
Author(s):  
Ernest Theodore Febrianto Sitompul ◽  
Ignatius Roni Setyawan
Keyword(s):  
Interest Rates ◽  
Money Supply ◽  
Stock Price ◽  
Price Index ◽  
Hypothesis Test ◽  
Composite Index ◽  
Garch Model ◽  
Coefficient Of Determination ◽  
Analysis Method ◽  
Stock Price Index

The purpose of this study was to determine the effect of inflation, interest rates certificates of Bank Indonesia and the money supply on the composite stock price index (CSPI) with the Arch-Garch model. The analytical method used in this study is multiple regression analysis method with the Arch-Garch model which was carried out with Eviews 9.0. One of the requirements for conducting multiple analysis tests is to test the classical assumptions. This is necessary so that the resulting regression equation is good. Then test the hypothesis, test the coefficient of determination and z test. The results of this study indicate that the Inflation variable has an effect on the Jakarta Composite Index (JCI) in the period January 2014 – December 2018. The interest rates certificates of Bank Indonesia an effect on the Jakarta Composite Index (JCI) in the period January 2014 – December 2018. The Money Supply has an effect. against the Composite Stock Price Index (JCI) in the period January 2014 – December 2018.Tujuan dari penelitian ini adalah untuk mengetahui pengaruh inflasi, suku bunga SBI dan jumlah uang beredar teradap indeks harga saham gabungan (IHSG) dengan model Arch-Garch. Metode analisis yang digunakan dalam penelitian ini adalah metode analisis regresi berganda dengan model Arch-Garch yang dilakukan dengan Eviews 9.0. Salah satu syarat untuk melakukan uji analisis berganda perlu dilakukan uji asumsi klasik. Hal ini diperlukan agar persamaan regresi yang dihasilkan baik. Kemudian dilakukan uji hipotesis, uji koefisien determinasi dan uji z. Hasil dari penelitian ini menunjukkan bahwa variable Inflasi berpengaruh terhadap Indeks Harga Saham Gabungan (IHSG) pada periode Januari 2014 – Desember 2018. Suku Bunga SBI memiliki pengaruh terhadap Indeks Harga Saham Gabungan (IHSG) pada periode Januari 2014 – Desember 2018. Jumlah Uang Beredar berpengaruh terhadap Indeks Harga Saham Gabungan (IHSG) pada periode Januari 2014 – Desember 2018.

scholarly journals Forecasting Analysis of Share Price Index in Construction Companies Registered in Indonesia Stock Exchange 2015-2019

2021 ◽  
Vol 5 (1) ◽  
pp. 42-63
Author(s):  
Karnila Ali
Keyword(s):  
Stock Price ◽  
Average Method ◽  
Price Index ◽  
Stock Exchange ◽  
Moving Average ◽  
Share Price ◽  
Series Data ◽  
Percentage Error ◽  
Construction Companies ◽  
Stock Price Index

Stock is one of the investment instruments that many investors choose, both short and long term. Meanwhile, the stock price index is an essential indicator for investors deciding whether to buy, sell, or hold the stock. This study aims to determine what methods are suitable for predicting the Stock Price Index of Construction Companies Listed on the Indonesia Stock Exchange in 2015-2019. By selecting a model that matches the existing time series data, to evaluate the results of the forecasting, the researcher uses a measure of accuracy with Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Deviation (MSD). This type of research is a quantitative study with a research population of 16 companies listed on the Indonesia Stock Exchange. Only four samples were used that fit the specified criteria, and only five years of research were conducted, namely in 2015 to 2019. data can be seen from historical data or actual data and tested using Minitab software version 19. The results showed that Double Exponential Smoothing (Holt's) and Double Moving Average Method could be used to forecast the Construction Company Stock Price Index. Obtaining the smallest error value of the four construction companies, namely WSKT company with MAPE = 7.3, MAD = 148.8, and MSD = 40506.0 for the Holt'sand MAPE method = 5.3, MAD = 110.1, and MSD = 22006.9 for the Double Moving Average method.

scholarly journals ARIMA Model Selection for Composite Stock Price Index in Indonesia Stock Exchange

2019 ◽  
Vol 2 (1) ◽  
pp. p31
Author(s):  
Zul Amry ◽  
Budi Halomoan Siregar
Keyword(s):  
Stock Price ◽  
Price Index ◽  
Mean Squared Error ◽  
Stock Exchange ◽  
Arima Model ◽  
Composite Index ◽  
Information Criterion ◽  
Absolute Error ◽  
Percentage Error ◽  
Stock Price Index

Composite Stock Price Index (CSPI) can be used as a reflection of the national economic condition of a country because it is an indicator to know the development the capital market in a country. Therefore, the movement in the future needs to be forecast. This study aims to build a model for the time series forecasting of Indonesia Composite Index (ICI) using the ARIMA model. The data used is the monthly data of ICI in Indonesia Stock Exchange (IDX) from January 2000 until December 2017 as many as 216 data. The method used in this research is the Box-Jenkins method. The autocorrelation (ACF) and partial autocorrelation function (PACF) are used for stationary test and model identification. The maximum estimated likelihood is used to estimate the parameter model. In addition, to select a model then used Akaike’s Information Criterion (AIC). Ljung-Box Q statistics are used for diagnostic tests. In addition, to show the accuracy of the model, we use Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) and the most appropriate model is ARIMA (0, 1, 1).

scholarly journals Estimasi permintaan indeks harga saham gabungan di Indonesia

2020 ◽  
Vol 8 (2) ◽  
pp. 65-76
Author(s):  
Ade Nugraha Paer ◽  
Syamsurijal Tan ◽  
Emilia Emilia
Keyword(s):  
Exchange Rate ◽  
Interest Rates ◽  
Money Supply ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Least Square ◽  
Stock Price Index ◽  
The Exchange Rate ◽  
Index Exchange

The purpose of this study is (a) to see the development of the composite stock price index, exchange rate, inflation, interest rates, and the money supply in Indonesia. (b) analyze the effect of the exchange rate, inflation, interest rate, and money supply on the composite stock price index in Indonesia. The method used in this study is a quantitative descriptive method with multiple linear regression analysis tools using the Ordinary Least Square (OLS) method. The data used is in the form of a time series. The results of this study average the development of the composite stock price index by 0.22 percent, the exchange rate by 2.57 percent, inflation by -0.90 percent, interest rates by -2.73 percent, and the Money Supply by 0.06 percent. Based on the results of the analysis conducted, exchange rates and interest rates have a negative and significant effect on the composite stock price index, inflation and the money supply have a positive and significant effect on the composite stock price index. Keywords: Composite stock price index, Exchange rate, Inflation, Interest rates, Money supply.

scholarly journals Pengaruh PDB, Inflasi, Tingkat Suku Bunga dan Nilai Tukar Rupiah terhadap Indeks Harga Saham JAKPROP yang Terdaftar di Bursa Efek Indonesia

2019 ◽  
Vol 1 (1) ◽  
pp. 100
Author(s):  
Chendra Gunawan ◽  
Carunia Mulya Firdausy
Keyword(s):  
Exchange Rate ◽  
Real Estate ◽  
Interest Rates ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Least Square ◽  
Share Prices ◽  
Real Estate Sector ◽  
Stock Price Index

This research aims to find out and analyze the effects of variable GDP, Inflation, Interest rates, Exchange rate on share prices of listed property sector in Indonesia Stock Exchange. The object population in this study is a company incorporated in the listed Property & Real Estate Index sector (JAKPROP) in Indonesia Stock Exchange (BEI) from 2008 to 2017. This study uses Ordinary Least Square analysis to determine the effect of independent variables on the Property & Real Estate Index sector JAKPROP. Based on t test, GDP is significant, Inflation is not significant and BI Interest rate is significant effect, while the variable Exchange rate have a significant effect on property and Real Estate sector stock price index. Results simultaneously with the F test showed that all the independent variable significantly influenced on the stock price index Property & Real Estate sector. So, the result is the independen variable GDP, Bi-rate & Exchange-rate has an influence effect on the stock price index of listed Property & Real Estate sector JAKPROP in Indonesia Stock Exchange. 

PENGARUH KURS RUPIAH, INFLASI,BI RATE, FED RATE, DAN SHANGHAI STOCK EXCHANGE COMPOSITE (SSEC) TERHADAP INDEKS HARGA SAHAM SEKTOR PROPERTI, REAL ESTAT, DAN KONSTRUKSI BANGUNAN (Studi Kasus pada Bursa Efek IndonesiaPeriode 2014-2018)

2019 ◽  
Vol 2 (2) ◽  
pp. 92
Author(s):  
Arthit Jayanti Hardiman ◽  
Sri Widiyati Widiyati ◽  
Moch. Abdul Kodir
Keyword(s):  
Exchange Rate ◽  
Real Estate ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Building Construction ◽  
Coefficient Of Determination ◽  
Stock Price Index ◽  
Research Show

This research aims to analyze the influence of the rupiah exchange rate, inflation, BI rate, FED rate, and SSEC onThe Stock Price Index of Property, Real Estate and Building Constructionon Indonesia Stock Exchange during 2014-2018. This research used secondary data. The sampling methodused total sampling, so the sample is the entire population or all of companies listed in property, real estate, and building construction sector on Indonesia Stock Exchange during 2014-2018. The research statistical model used multiple linear regression analysis model processed by software SPSS 25. The equation of this regression model estimation on this research: IHSSP = 339.651 – 0.019KU -837.814IN + 460.140BR + 141.072FR + 0.023IS + ℯ. The F testresult of this research show the rupiah exchange rate, inflation, the BI rate, the FED rate, and SSEChave significant simultaneously influence on the Sector Stock Price Index of Property, Real Estate, and Building Construction. Then the t test result of this research show the rupiah exchange rate has significant partially influence, so H1 was accepted. Inflation has significant partially influence, so H2 was accepted. BI rate has not significant partially influence, so that H3 was rejected. FED rate has not significant partially influence, so H4 was rejected. SSEC has significant partially influence, so H5 was accepted on the Sector Stock Price Index of Property, Real Estate, and Building Construction. The coefficient of determination is 0.826., so the ability variation of the independent variables (rupiah exchange rate, inflation, BI rate, FED rate, and SSEC) in explaining the variation of the dependent variable (Sector Stock Price Index of Property, Real Estate, and Building Construction) was 82.6%, while the rest was explained by other independet variable soutside this research

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