scholarly journals Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index

2018 ◽  
Vol III (III) ◽  
pp. 466-476
Author(s):  
Mustafa Afeef ◽  
Nazim Ali ◽  
Adnan Khan
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
External Factors ◽  
Forecasting Model ◽  
Stock Market Index ◽  
Short Term ◽  
Market Index ◽  
Arima Modeling

The stock market index can be forecasted in two ways --- either through taking those external factors that influence movements in the index or by basing ones predictions on the previous values of the index. The current study has used the method described later by employing the Box-Jenkins methodology --- a method famously used by most researchers while conducting ARIMA modeling--- by taking past figures of KSE 100 Index. Quarterly figures of the Index were, therefore, taken for 22 years from August 1995 to October 2017 that translated into 90 observations. Results revealed that the forecasting model used in the study did well in anticipating returns in the shortrun. The findings of the study can be consumed by investors, particularly short-term, in deciding when, and when not, to risk their hard-earned funds at Pakistan Stock Exchange.

scholarly journals Will the Stock Market Index Upsurge or Deflate? Making Calculated Predictions Using the Univariate Autoregressive Integrated Moving Average Technique

2018 ◽  
Vol III (IV) ◽  
pp. 413-426
Author(s):  
Mustafa Afeef ◽  
Nazim Ali ◽  
Adnan Khan
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Moving Average ◽  
Stock Market Index ◽  
Short Term ◽  
Average Technique ◽  
Autoregressive Integrated Moving Average ◽  
Past Behavior ◽  
Market Index ◽  
Arima Modeling

Movements in a stock market index may safely be considered one of the mostwatched out phenomena by investors in almost every economy. One method to forecast the index is to study all those external factors that directly affect it. Another way, however, is to base ones predictions on the past behavior of the variable of interest. This paper has employed the method described latter and has, therefore, made use of the ARIMA modeling. In this connection, the daily stock market index data of the Karachi Stock Exchange 100 index was taken for twenty years from 1997 to 2017 which translated into 4940 observations. The study revealed that the model was decently efficient in forecasting the KSE 100 Index, though only for the short-range. The upshot of this study may be utilized specifically by short term investors in deciding on when, and when not, to invest in the stock market.

scholarly journals Will the Stock Market Index Upsurge or Deflate? Making Calculated Predictions Using the Univariate Autoregressive Integrated Moving Average Technique

2018 ◽  
Vol III (IV) ◽  
pp. 413-426
Author(s):  
Mustafa Afeef ◽  
Nazim Ali ◽  
Adnan Khan
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Moving Average ◽  
Stock Market Index ◽  
Short Term ◽  
Average Technique ◽  
Autoregressive Integrated Moving Average ◽  
Past Behavior ◽  
Market Index ◽  
Arima Modeling

Movements in a stock market index may safely be considered one of the mostwatched out phenomena by investors in almost every economy. One method to forecast the index is to study all those external factors that directly affect it. Another way, however, is to base ones predictions on the past behavior of the variable of interest. This paper has employed the method described latter and has, therefore, made use of the ARIMA modeling. In this connection, the daily stock market index data of the Karachi Stock Exchange 100 index was taken for twenty years from 1997 to 2017 which translated into 4940 observations. The study revealed that the model was decently efficient in forecasting the KSE 100 Index, though only for the short-range. The upshot of this study may be utilized specifically by short term investors in deciding on when, and when not, to invest in the stock market.

scholarly journals Effects of changes in stock market index composition on stock returns: event study methodology on Zagreb Stock Exchange

2019 ◽  
Vol 5 (1) ◽  
pp. 43-54
Author(s):  
Tihana Škrinjarić
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Event Study ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Stock Market Index ◽  
Market Index ◽  
Study Methodology ◽  
Composition Changes ◽  
Event Study Methodology

AbstractThis paper observes the short-run effects of stock market index composition changes on stock returns on the Zagreb Stock Exchange (ZSE). In that way, event study methodology is employed in order to estimate abnormal returns and compare them amongst three subsets of stocks: those leaving the market index, those entering it, and constantly included stocks. The research included 14 regular and extraordinary revisions of the market index in the period from January 2nd, 2015 until March 21st, 2018. The results have confirmed two research hypotheses: stock exclusions from the market index have a negative effect on stock returns on the ZSE, which is consistent with the price pressure hypothesis; and there exist asymmetric effects of index composition changes on stock returns. This is the first study of this kind on the Croatian stock market, thus more questions need to be answered in future research.

scholarly journals The long-Run and Short-Run Analysis between Stock Market Index and Macroeconomic Variables in Jordan: Bounds Tests Approach

2019 ◽  
Vol 12 (4) ◽  
pp. 50
Author(s):  
Raed Walid Al-Smadi ◽  
Muthana Mohammad Omoush
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
Stock Market Index ◽  
Macroeconomic Variables ◽  
Market Index ◽  
Long Run ◽  
Equilibrium Relationship ◽  
Short Run

This paper investigates the long-run and short-run relationship between stock market index and the macroeconomic variables in Jordan. Annual time series data for the 1978–2017 periods and the ARDL bounding test are used. The results identify long-run equilibrium relationship between stock market index and the macroeconomic variables in Jordan. Jordanian policy makers have to pay more attention to the current regulation in the Amman Stock Exchange(ASE) and manage it well, thus ultimately helping financial development.

Forecasting the Time Volatility of Emerging Asian Stock Market Index

2007 ◽  
Vol 3 (2) ◽  
pp. 38-51 ◽  
Author(s):  
M. Selvam ◽  
M. Raja ◽  
P. Yazh Mozhi
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Market Volatility ◽  
Stock Market Index ◽  
Market Index ◽  
Asian Market ◽  
Current Price ◽  
One Year ◽  
Almost All ◽  
Derivatives Markets

Volatility is the measure of how far the current price of an asset deviates from its average past prices. Greater the deviation, greater the volatility. It indicates the strength or conviction behind a price movement. Stock market volatility is the function of the arrival of positive and negative market information. Pricing of securities is supposed to be dependent on the volatility of each asset. Matured / developed markets continue to provide over long period of time high returns with low volatility. Emerging markets, except India and China exhibit low returns. The exponential growth in the Asian derivatives markets necessitated the need to test whether the Asian market indices are more volatile or not. The study finds an evidence of time varying volatility, which exhibits clustering, high persistence and predictability for almost all the Asian market indices in the sample. With this background the present paper investigates the dynamic behavior of stock returns of ten market indices from Asian countries, using symmetric GARCH (1,1) model for a period of one year from January 2006 to December 2006.

scholarly journals GLOBALISASI PASAR MODAL DUNIA DAN PENGARUHNYA TERHADAP PASAR MODAL INDONESIA

2017 ◽  
Vol 1 (1) ◽  
pp. 10
Author(s):  
R Adisetiawan
Keyword(s):  
Stock Market ◽  
Capital Markets ◽  
Capital Market ◽  
Stock Exchange ◽  
Global Market ◽  
Stock Market Index ◽  
Causality Test ◽  
Global Capital ◽  
Market Index ◽  
Cointegration Tests

This study aims to prove causality, cointegration and the influence of global capital markets with a market capital of Indonesia for the period 2001-2016 with a Granger causality test statistics, cointegration tests and Multiple Regression testing. These results prove that the 99% confidence interval occurred a long term relationship (cointegration) and the significant influence of global market indices with the Indonesia capital market index (CSPI) in Indonesia Stock Exchange (IDX) for the period 2001 to 2016, it indicates that Indonesia's economy has been integrated with global capital markets with varying levels of integration, but is causally there is only one country that has a causal relationship with the Indonesian stock market index (CSPI), the Taiwan stock market index (TWSE).Keywords: Capital Market Integration

scholarly journals The Effect of Macroeconomic Variables on the Stock Market Index of the Tehran Stock Exchange

2016 ◽  
Vol 71 ◽  
pp. 17-24
Author(s):  
Mohsen Mehrara ◽  
Yazdan Gudarzi Farahani ◽  
Farzan Faninam ◽  
Abbas Rezazadeh Karsalari
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Price Index ◽  
Government Expenditure ◽  
Maximum Level ◽  
Stock Market Index ◽  
Macroeconomic Variables ◽  
Market Index ◽  
The Government ◽  
Positive Effect

This paper examines the relationship between stock market index and macroeconomic policies (Fiscal and Monetary) on Iran's economy using quarterly data in the period 1999-2013. This study employed cointegration test and vector autoregressive models (VAR) to examine relationships between the stock market index and the macroeconomic variables. The empirical results reveal that a positive money shock can increase stocks return. According to impulse responses, the government expenditure had a slight impact on stocks return in the short term. But the government expenditure has a positive effect on exchange index in long run. Also the effect of taxes on the stock's price index is negative, so that it reaches its maximum level after the third lag and then alleviates. The GDP shock has positive effect on the stock's price index. Increase in production level leads to increase in earnings and profitability, leading to a positive response from stocks index. Therefore the results showed that the macroeconomic variables such as inflation, exchange rate and GDP have significant effects on Tehran exchange price index. So the hypothesis that the improving economic factors can have a useful role in the booming capital market is confirmed. Also the effect of fiscal policy factors such as tax revenues and government expenditures is more than monetary policy factors on stock returns.

scholarly journals Quantitative relationship between corruption and development of the Tunisian stock market

2018 ◽  
Vol 7 (2) ◽  
pp. 39-47
Author(s):  
Ibtissem Missaoui ◽  
Mohsen Brahmi ◽  
Jaleleddine BenRajeb
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Quantitative Relationship ◽  
Stock Market Index ◽  
Private Companies ◽  
Stock Market Development ◽  
Market Index ◽  
The Government ◽  
The Impact ◽  
Positive Effect

The aim of this article is to seek especially the impact of corruption on the bond and stock market development. For the methodology/approach, the authors analyze a sample of 20 listed Tunisian firms from the Stock Exchange and Financial market, covering the period from 2006 to 2016 by using pooling cross section techniques. The results find a significant positive effect of the level of corruption on the stock market index and the logarithm of capitalization. This is consistent with the view that corruption accelerates the economic growth by speeding up transactions and allowing private companies to overcome the inefficiencies imposed by the government. Furthermore, the results find a negative association is not significant with the dependent variable of traded value as a percentage of the number of listed companies.

scholarly journals Prediksi Indeks BEI dengan Ensemble Convolutional Neural Network dan Long Short-Term Memory

2021 ◽  
Vol 5 (3) ◽  
pp. 456-465
Author(s):  
Harya Widiputra ◽  
Adele Mailangkay ◽  
Elliana Gautama
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Time Series Data ◽  
Short Term Memory ◽  
Series Data ◽  
Stock Market Index ◽  
Short Term ◽  
Term Memory ◽  
Market Index ◽  
Long Short Term Memory

The Indonesian Stock Exchange (IDX) stock market index is one of the main indicators commonly used as a reference for national economic conditions. The value of the stock market index is often being used by investment companies and individual investors to help making investment decisions. Therefore, the ability to predict the stock market index value is a critical need. In the fields of statistics and probability theory as well as machine learning, various methods have been developed to predict the value of the stock market index with a good accuracy. However, previous research results have found that no one method is superior to other methods. This study proposes an ensemble model based on deep learning architecture, namely Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM), called the CNN-LSTM. To be able to predict financial time series data, CNN-LSTM takes feature from CNN for extraction of important features from time series data, which are then integrated with LSTM feature that is reliable in processing time series data. Results of experiments on the proposed CNN-LSTM model confirm that the hybrid model effectively provides better predictive accuracy than the stand-alone time series data forecasting models, such as CNN and LSTM.  

scholarly journals Modeling stock market volatility in Croatia

2021 ◽  
Vol 34 (2) ◽  
pp. 431-442
Author(s):  
Hrvoje Jošić ◽  
Berislav Žmuk
Keyword(s):  
Stock Market ◽  
Degrees Of Freedom ◽  
Stock Exchange ◽  
Error Distribution ◽  
Stock Market Volatility ◽  
Stock Market Index ◽  
The Past ◽  
Market Index ◽  
Generalized Error Distribution ◽  
Error Distributions

Purpose: In this paper, the volatility of the Croatian stock market index CROBEX is investigated using the GARCH(1,1) model. Methodology: The novelty provided by this paper is the estimation of the GARCH(1,1) model by using three conditional error distributions (normal (Gaussian) distribution, Student’s-distribution with fixed degrees of freedom and generalized error distribution (GED) with fixed parameters). Results: The findings obtained in the research are in the line with previous research in this field (Erjavec & Cota, 2007; Sajter & Ćorić, 2009). The volatility of CROBEX returns is positively correlated with the volume of trade on the Zagreb Stock Exchange and movements on the main European and American stock markets. The movement of S&P 500 stock market index returns is transmitted from the previous day, providing signals for the direction of change of CROBEX index returns in the present. Conclusion: Therefore, this paper provides evidence that investors in Croatia strongly rely on the past information received from the American S&P500 stock market index. Furthermore, there seems to exist the co-movement between CROBEX and main European indexes on the same trading day.

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