scholarly journals VOLATILITAS INDEKS KOMPOSIT PASAR MODAL ASEAN-3

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Anhar Fauzan Priyono
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Exchange Rate Regime ◽  
Composite Index ◽  
Stock Index ◽  
Movement Behavior ◽  
Stock Market Index ◽  
Monthly Basis ◽  
Volatility Model ◽  
Aggregate Investment

Rapid integration between domestic and world economy in the last decade has been a major issue. For Indonesia, the situation has been accelerated by the adoption of floating exchange rate regime in 1997, also with the development of Indonesia stock exchange. One notable financial variable that often exposed to external shocks is stock market index. This research will analyzed the behavior of 3 major stock market indices in ASEAN, those are Jakarta Composite Index (JCI), Kuala Lumpur stock index (KLSE), and Singapore stock index (STI). The employment of volatility model is chosen to figured the behavior of those 3 indices, and to analyze the aggregate investment in each stock market. Observation will be based upon monthly basis, from 2010 until 2015.The findings in this research are (i) similarity in the movement behavior of ASEAN-3 stock market indices, (ii) Indonesia stock market shows the highest aggregate investment return relative to Malaysia and Singapore, (iii) Singapore stock market shows the lowest aggregate investment risk relative to Indonesia and Malaysia, as the representation of more developed stock market.

META-ANALYSIS ON AMERICAN PRESIDENTIAL ELECTION - 2016 AND AMERICAN STOCK MARKET

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Farhan Ahmed ◽  
Salman Bahoo ◽  
Sohail Aslam ◽  
Muhammad Asif Qureshi
Keyword(s):  
Content Analysis ◽  
Stock Market ◽  
Event Study ◽  
Presidential Election ◽  
Republican Party ◽  
Stock Exchange ◽  
Meta Analysis ◽  
Composite Index ◽  
Stock Index ◽  
Political Event

This paper aims to analyze the efficient stock market hypothesis as responsive to American Presidential Election, 2016. The meta-analysis has been done combining content analysis and event study methodology. The all major newspapers, news channels, public polls, literature and five important indices as Dow Jones Industrial Average (DJIA), NASDAQ Stock Market Composit Indexe (NASDAQ-COMP), Standard & Poor's 500 Index (SPX-500), New York Stock Exchange Composite Index (NYSE-COMP) and Other U.S Indexes-Russell 2000 (RUT-2000) are critically examined and empirically analyzed. The findings from content analysis reflect that stunned winning of Mr Trump from Republican Party worked as shock for American stock market. From event study, findings confirmed that all the major indices reflected a decline on winning of Trump and losing of Ms. Clinton from Democratic. The results are supported empirically and practically through the political event like BREXIT that resulted in shock to Global stock index and loss of $2 Trillion.

scholarly journals The Stock Market Situation and Economic Growth – An Attempt to Assess the Dependence

2021 ◽  
Vol 4 (32) ◽  
pp. 117-128
Author(s):  
Michał Radke
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Pearson Correlation ◽  
Research Work ◽  
Calculated Data ◽  
Stock Index ◽  
Rate Of Return ◽  
Real Economy ◽  
Stock Market Index ◽  
Market Situation

The aim of the article: The main aim of the article is to analyze the relationship between the stock market situation and the real economy, measured by the strength of the correlation between the rate of return on the stock market and the rate of GDP growth in European capital markets. The next objective is to answer the question whether the stock market index changes are ahead of, and if so, by how much, GDP changes. The author’s hypothesis stipulates that the stock exchange situation precedes the change in economic activity and serves as its forecast. Methodology: The empirical research work was carried out on the basis of quarterly data value of the stock index and the GDP between 2010 and the first quarter of 2021 for 20 European countries. For indices and GDP, the quarterly dynamics of the rate of return and GDP were calculated. Data on the value of the stock exchange index was taken from the website www.stooq.pl, while data on GDP was taken from Eurostat. Subsequently, the analysis concerned the correlation relationships between the variables on the basis of the Pearson correlation coefficient. The correlation between the variables was calculated without delay, as well as with a delay of one, two or three quarters of the returns on stock indices. Results of the research: Changes in the value of the stock exchange index is in most cases positively correlated with the change in GDP and the correlation is pronounced, but it is low and moderate. The only market for which a significant correlation was observed, was the Polish market. At the same time, it can be stated that the rates of return on the stock exchange index precede a change in GDP by one or three quarters. No changes were observed for the analyzed countries for two quarters.

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 Daily Stock Movements Through the Lens of Event and News: Evidence from the Pakistan Stock Exchange

2021 ◽  
Author(s):  
Shahid Raza ◽  
Baiqing Sun ◽  
Pwint Kay Khine
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
News Daily ◽  
Stock Market Index ◽  
Daily Newspaper ◽  
Monthly Basis ◽  
Market Index ◽  
The Impact

This study will investigate different signals and events/news that determined the stock market's movements. As we know, many factors affect the stock market on a daily, weekly, and monthly basis, e.g., rate of interest, exchange rate, and oil prices, etc. Our research will investigate the impact of daily events/news in the KSE-100 index due to several policies announced and events/news in the country because the daily movements in the stock market can be determined only by different signals and events/news. Time series data is collected daily for particular reasons from "The News" (Daily Newspaper, Sunday edition) from 2010 to 2019. The results of this study show that political and global news affects the stock market index ferociously. For investors, the investment in blue chips is not less than a safe haven. When day-to-day transactions are concerned, there is always a higher panic attack than the herd behaviour in the stock exchange. Investors tend to make prompt responses to negative rather than positive news, which makes them risk averters. Our finding also confirmed that the ARCH/GARCH model is better than the simple OLS method concerning stock market upheaval.

scholarly journals Crash Diagnosis and Price Rebound Prediction in NYSE Composite Index Based on Visibility Graph and Time-Evolving Stock Correlation Network

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1612
Author(s):  
Yuxuan Xiu ◽  
Guanying Wang ◽  
Wai Kin Victor Chan
Keyword(s):  
Stock Market ◽  
Power Law ◽  
Stock Exchange ◽  
Composite Index ◽  
Detection Algorithm ◽  
Value Theory ◽  
Visibility Graph ◽  
Stock Index ◽  
Power Law Model ◽  
Market Crashes

This study proposes a framework to diagnose stock market crashes and predict the subsequent price rebounds. Based on the observation of anomalous changes in stock correlation networks during market crashes, we extend the log-periodic power-law model with a metric that is proposed to measure network anomalies. To calculate this metric, we design a prediction-guided anomaly detection algorithm based on the extreme value theory. Finally, we proposed a hybrid indicator to predict price rebounds of the stock index by combining the network anomaly metric and the visibility graph-based log-periodic power-law model. Experiments are conducted based on the New York Stock Exchange Composite Index from 4 January 1991 to 7 May 2021. It is shown that our proposed method outperforms the benchmark log-periodic power-law model on detecting the 12 major crashes and predicting the subsequent price rebounds by reducing the false alarm rate. This study sheds light on combining stock network analysis and financial time series modeling and highlights that anomalous changes of a stock network can be important criteria for detecting crashes and predicting recoveries of the stock market.

scholarly journals DPP: Deep predictor for price movement from candlestick charts

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252404
Author(s):  
Chih-Chieh Hung ◽  
Ying-Ju Chen
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Extensive Study ◽  
Stock Index ◽  
Stock Market Index ◽  
Price Movement ◽  
Market Prices ◽  
Taiwan Stock Exchange ◽  
Market Index ◽  
Political Events

Forecasting the stock market prices is complicated and challenging since the price movement is affected by many factors such as releasing market news about earnings and profits, international and domestic economic situation, political events, monetary policy, major abrupt affairs, etc. In this work, a novel framework: deep predictor for price movement (DPP) using candlestick charts in the stock historical data is proposed. This framework comprises three steps: 1. decomposing a given candlestick chart into sub-charts; 2. using CNN-autoencoder to acquire the best representation of sub-charts; 3. applying RNN to predict the price movements from a collection of sub-chart representations. An extensive study is operated to assess the performance of the DPP based models using the trading data of Taiwan Stock Exchange Capitalization Weighted Stock Index and a stock market index, Nikkei 225, for the Tokyo Stock Exchange. Three baseline models based on IEM, Prophet, and LSTM approaches are compared with the DPP based models.

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.

scholarly journals Realita Dinamika Pasar: Studi Intensif Distingsi Syariah Konvensional

2019 ◽  
Vol 3 (2) ◽  
pp. 190-202
Author(s):  
Yadi Nurhayadi ◽  
Daram Heriansyah ◽  
Eva Susanti ◽  
Siti Azizziah Azzahra
Keyword(s):  
Multivariate Analysis ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Index ◽  
Weak Correlation ◽  
Company Stock ◽  
Regression Correlation

The research confirm the differences between sharia company stock index and conventional company stock index as the issuer at The Indonesia Stock Exchange. This research is a continuation of a series of previous studies by Nurhayadi et al earlier on the comparison between the sharia market and the conventional market. The Data consist of Jakarta Stock Exchange (JSX) Composite Index (Indeks Harga Saham Gabungan (IHSG)), Jakarta Stock Exchange Liquid Index (LQ45), Jakarta Islamic Index (JII), Indonesia Sharia Stock Index (ISSI), ten companies of sharia issuer, and ten companies of conventional issuer. There are seven scenarios based on bivariate and multivariate analysis that conducted regression, correlation, and determination test to know whether conventional company influence on sharia company. The research scenarios cover five years data from January 2014 to December 2018. The result confirms that the fluctuation of conventional issuer's stocks is different from the fluctuation of sharia issuer's stocks. Conventional issuers have a weak correlation with sharia issuers. This condition implies that between the conventional market and the Islamic market there is no correlation.

scholarly journals ANALISIS PENGARUH INDEKS HARGA SAHAM GABUNGAN REGIONAL ASIA TERHADAP INDEKS HARGA SAHAM GABUNGAN INDONESIA

2018 ◽  
Vol 1 (2) ◽  
pp. 148
Author(s):  
Widodo Widodo
Keyword(s):  
South Korea ◽  
Significant Influence ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Index ◽  
Kuala Lumpur ◽  
Korea Strait ◽  
Independent Variables

ABSTRACTThe aims of this research is to analyze the influence of NIKKEI 225 Index (^N225), HANG SENG Index (^HSI), KOSPI Index (^KS11), Strait Times Index (^STI), and Kuala Lumpur Stock Exchange (^KLSE) simultaneously and partially in Jakarta Composite Index (^JKSE) during 2009 to 2017. Method of multiple linier regression with significant level 0,05 using STATA 10 program. The populations and samples was used this research is stock index on ASIA regional (NIKKEI 225 (Japan), HANG SENG Index (Hongkong), KOSPI (South Korea), Strait Times Index (Singapore), Kuala Lumpur Stock Exchange (Malaysia), and Jakarta Composite Index (Indonesia)) was conducted during January 2009 to May 2017. Results of this research simultaneously model for all independent variables are influence to dependent variable. However, parcially model ^N225, ^KS11 and ^KLSE variables positive and significant influence to ^JKSE variable. Whereas ^HSI and ^STI variable are not effect to ^JKSE variable during January 2009 to May 2017.Keywords: JKSE; N225; HSI; KS11; STI; KLSE.

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