scholarly journals Penggunaan Metode Orthogonal GARCH untuk Meramalkan Matriks Kovarians Return Indeks Harga Saham Sektoral Di Bursa Efek Indonesia

2019 ◽  
Vol 12 (2) ◽  
pp. 30
Author(s):  
Robiyanto Robiyanto
Keyword(s):  
Risk Factor ◽  
Value At Risk ◽  
Stock Price ◽  
Stock Exchange ◽  
Principal Component ◽  
Jel Classification ◽  
Stock Index ◽  
Price Indices ◽  
Exchange Value ◽  
Autoregressive Conditional Heteroscedasticity

ABSTRACT   This study conducted a risk communality assessment on sectoral stock price indices in Indonesia Stock Exchange by using Orthogonal Generalized Autoregressive Conditional Heteroscedasticity (Orthogonal GARCH) method. Data used in this research is daily closing of sectoral stock price indices at Indonesia Stock Exchange which consisting of 10 sectoral price indices. Research period are during January 4, 2011 until July 17, 2017. Of 10 sectoral stock price indices which studied apparently there are two principal component influencing its conditional variance. The result of this research is that stock index of agriculture and mining sector have the same risk factor, while other sectoral stock price indices have the same risk factor. These findings imply that investment managers must differentiate risk factors for agricultural and mining sectors from other sectors.   Keywords : Orthogonal GARCH; Indonesia Stock Exchange; Value-at-Risk (VaR); Sectoral stock price indices; Covariance matrix   JEL Classification : C58; G11.  

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

In Search of Stock Market Proxy to Calculate Systematic Risk (Beta) of Stocks in Indonesia Stock Exchange

2020 ◽  
Vol 29 (2) ◽  
pp. 80-88
Author(s):  
Mochammad Chabachib
Keyword(s):  
Stock Market ◽  
Real World ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
The Other ◽  
Stock Index ◽  
Market Return ◽  
Stock Market Return ◽  
Stock Index Returns

The calculation of beta stock in Indonesia is still debatable to this day. Though many researchers who have used sophisticated methods mathematically, the assumptions applied in developing the methods are impossible to happen in the real world, such as the ability of stock market return the day after (lead) affects the market return today. This study was conducted to assess the stock price index in Indonesia Stock Exchange that can be used as a proxy of stock market in Indonesia. The results of this study showed that there was a gap between beta stocks counted with JCI return as a market proxy with beta stocks counted with index returns of LQ-45, SRI-KEHATI, PEFINDO-25, BISNIS-27, IDX-30 and KOMPAS-100. This study has also found that the beta counted by using KOMPAS-100 return produced the smallest standard error of the estimate (SEE) that it was more applicable compared to the other stock index returns.

scholarly journals KORELASI DINAMIS ANTARA PERGERAKAN HARGA MINYAK DUNIA DAN INDEKS HARGA SAHAM SEKTORAL DI BURSA EFEK INDONESIA

2020 ◽  
Vol 9 (3) ◽  
pp. 188
Author(s):  
Yunita Dewi Safitri ◽  
Robiyanto Robiyanto
Keyword(s):  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Secondary Data ◽  
Oil Prices ◽  
Dynamic Correlation ◽  
Analysis Technique ◽  
Static Approach ◽  
Stock Price Index ◽  
Autoregressive Conditional Heteroscedasticity

Changes in the situation that move very quickly on the commodity market have an impact on financial markets, one of which is the stock market in Indonesia. Therefore this study aims to examine the dynamic correlation between the movement of world oil prices and the Sectoral Stock Price Index listed on the Indonesia Stock Exchange (IDX). The data used is obtained from secondary data in the form of daily closing price data for world oil prices and Sectoral Stock Price Index from January 2017 to June 2020. The analysis technique used is Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH), due to previous studies mostly using a static approach. The results of this study show that the DCC-GARCH value between world oil prices (Brent and WTI) and Sectoral Stock Price Index tends to be very weak. A negative dynamic correlation was also found in the Consumer Goods Sector. This research can be a reference for investors who want to invest stocks in Indonesia by looking at the correlation between world oil prices and the Sectoral Stock Price Index.

scholarly journals The Impact of Corona Virus Disease 2019 (COVID-19) on Indonesia Property Stock Index

2021 ◽  
Vol 4 (2) ◽  
pp. 85-96
Author(s):  
Kevin Ronaldo Gotama ◽  
Njo Anastasia
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Virus Disease ◽  
Sampling Technique ◽  
Stock Index ◽  
Event Analysis ◽  
Corona Virus ◽  
Before And After ◽  
The Impact

A promising investment in the property sector is due to appreciation in property value. As an economic instrument, the stock market, inseparable from different environmental factors, was triggered by incident in Wuhan, Hubei Province, China, an outbreak of acute respiratory tract infection 2 (SARS-CoV-2) in December 2019 and then spread across China. This study is a comparative study on the stock index of the property sector on the stock exchange of countries affected by the Corona Virus Disease 2019 (COVID-19) case, with a purposive sampling technique according to certain criteria for sample selection. The event analysis was performed by analyzing market reaction; with COVID-19 incident effect as one of the event tests, the stock price index. The findings of the study indicate that there is an index response to the incident of COVID-19. The reflected reaction shows in the abnormal return and trade volume activity before and after the incident. Thus, this study is expected to be taken into consideration for stock investors regarding the impact of the Corona Virus Disease 2019 (COVID-19) pandemic on stock prices, by providing an overview of changes in stock prices during the monitoring period, so that they can make investment decisions in the period before and after incident.

scholarly journals Application of Genetic Algorithm and Personal Informatics in Stock Market

2018 ◽  
Vol 2 (2) ◽  
pp. 68 ◽  
Author(s):  
Khulood Albeladi ◽  
Salha Abdullah
Keyword(s):  
Genetic Algorithms ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Index ◽  
Target Market ◽  
Technical Data ◽  
Personal Informatics ◽  
Informatics System ◽  
Input Variables

The financial market is extremely attractive since it moves trillion dollars per year. Many investors have been exploring ways to predict future prices by using different types of algorithms that use fundamental analysis and technical analysis. Many professional speculators or amateurs had been analysing the price movement of some financial assets using these algorithms. The use of genetic algorithms, neural networks, genetic programming combined with these tools in an attempt to find a profitable solution is very common. This study presents a prototype that utilizes genetic algorithms (GAs) and personal informatics system (PI) for short-term stock index forecast. The prototype works according to the following steps. Firstly, a collection of input variables is defined through technical data analysis. Secondly, GA is applied to determine an optimal set of input variables for a one-day forecast.  The data is gathered from the Saudi Stock Exchange as being the target market. Thirdly, PI is utilised to create a smart environment, which enables visualisation of stock prices. The outcome indicates that this approach of forecasting the stock price is positive. The highest accuracy obtained is 64.67% and the lowest one is 48.06%.

Time Series Analysis Using ARCH Models: A Case Analysis of Australian Stock Index

2017 ◽  
Vol 3 (1) ◽  
pp. 74-80 ◽  
Author(s):  
Prabhat Mittal
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Stochastic Processes ◽  
Stock Price ◽  
Stock Exchange ◽  
Case Analysis ◽  
Stock Index ◽  
Arch Model ◽  
Arch Models ◽  
New Class

Australian All Ordinaries Stock Index has been in the headline since 1997 for its tear jerking effect on the stock exchange. Present work attempts to develop a realistic time-series model to explain the behavior of the stock price data during 2 January 1997 to 29 December 2006 collected from www.yahoofinance.com. To begin with residual analysis reveals that assumption of constant one period ahead forecast variance does not hold true. Accordingly, a new class of stochastic processes, called Autoregressive Conditional Heteroscedastic (ARCH) is studied. To this end, Computer programs on Ms-Excel have been used to fit the ARCH model.

scholarly journals Analisa Korelasi Return Indeks – Indeks Saham terhadap Indeks Harga Saham Gabungan pada Bursa Efek Indonesia

2015 ◽  
Vol 6 (2) ◽  
pp. 330 ◽  
Author(s):  
Mulyono Mulyono
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Index ◽  
Stock Trading ◽  
Close Relationship ◽  
Coefficient Corrélation ◽  
Stock Price Index

Stock market generally has the stock price index that measures the performance of stock trading, the Indonesia Stock Exchange has a stock price index that is widely known as Jakarta Composite Index (IHSG). During its development, the Indonesia Stock Exchange has many alternative indexes that measure the performance of stock trading. Research that is to be conducted on the correlation between return of the stock index listed in Indonesia Stock Exchange and return of Jakarta Composite Index. Return stock index listed on the Indonesia Stock Exchange, namely, LQ45 Index, Jakarta Islamic Index (JII), KOMPAS100 Index, BISNIS-27 Index, PEFINDO25 Index and SRI-KEHATI Index, has a close relationship with the return Jakarta Composite,Index which is a reflection of the movement of all existing stock in the market. Return of stocks index that have the highest coefficient correlation is KOMPAS100 In dex, which have return index coefficient correlation is 0.949, thus KOMPAS100 Index that consisting of 100 stocks, based on the results of the study can be used as an alternative investment to get a return that is at least equal or close to the yield given by Jakarta Composite Index(IHSG) that consists of 445 stocks

scholarly journals LQ45 Stock Index Prediction using k-Nearest Neighbors Regression

2019 ◽  
Vol 8 (3) ◽  
pp. 2388-2391 ◽  
Keyword(s):  
Capital Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Numerical Data ◽  
Nearest Neighbors ◽  
Stock Index ◽  
K Nearest Neighbors ◽  
Stock Price Prediction ◽  
The Capital Market

The capital market is an organized financial system consisting of commercial banks, intermediary institutions in the financial sector and all outstanding securities. One of the benefits of the capital market is creating opportunities for the community to participate in economic activities, especially in investing. In daily stock trading activities, stock prices tend to have fluctuated. Therefore, stock price prediction is needed to help investors make decisions when they want to buy or sell their shares. One asset for investment is shares. One of the stock price indices that attracts many investors is the LQ45 stock index on the Indonesian stock exchange. One of the algorithms that can be used to predict is the k-Nearest Neighbors (kNN) algorithm. In the previous study, kNN had a higher accuracy than the moving average method of 14.7%. This study uses kNN regression method because it predicts numerical data. The results of the research in making the LQ45 stock index prediction application have been successfully built. The highest accuracy achieved reaches 91.81% by WSKT share.

scholarly journals PERBANDINGAN SAHAM BERBASIS SYARIAH DENGAN SAHAM KONVENSIONAL SEBAGAI ANALISA KELAYAKAN INVESTASI BAGI INVESTOR MUSLIM

2016 ◽  
Vol 3 (2) ◽  
pp. 101
Author(s):  
Muthoharoh Muthoharoh ◽  
Sutapa Sutapa
Keyword(s):  
Stock Price ◽  
Sampling Method ◽  
Stock Exchange ◽  
Statistical Tests ◽  
Analytical Techniques ◽  
Stock Index ◽  
Investment Activity ◽  
Spss Software ◽  
Better Than

The phenomenon of the lack of confidence Indonesian investors to invest more effort to control the country’s wealth as his own one of them due to lack of knowledge . Including for Indonesian Muslim businessmen , is an alternative investment of choice muamalah . But in this investment activity , there are still concerns the Muslimsagainst the perception of potential investors speculation or gharar . Therefore, the Indonesia Stock Exchange ( IDX ) follow up these concerns by launching Islamic products including Islamic stocks are grouped in two Islamic Indices , Jakarta Islamic Index ( JII ) in 2000 and Indonesia Sharia Stock Index ( ISSI ) in 2011 . The purpose of this study is to analyze and provide empirical evidence that the rate of return and risk performance of Islamic stocks better than conventional stocks . The population is all listed companies that issued shares listed on the Indonesia Sharia Stock Index ( ISSI ) for a group of Islamic stocks and Stock Price Index (CSPI ) for conventional stock group . The sampling method used was purposive sampling method in order to obtain 207 samples . Analytical techniques used include : the classical assumption of normality , descriptive statistical tests , and hypothesis testing are processed using SPSS software version 16 . The results showed that there are significant differences in the performance of stocks in which the conventional stock sharia Islamic stocks have performed much better than the conventional stock .

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