scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS HARGA SAHAM DI INDONESIA

2017 ◽  
Vol 4 (2) ◽  
pp. 94
Author(s):  
Daryono Soebagiyo ◽  
Endah Heni Prasetyowati
Keyword(s):  
Foreign Currency ◽  
Time Series Data ◽  
Stock Exchange ◽  
Rapid Development ◽  
Stock Index ◽  
Series Data ◽  
Partial Adjustment ◽  
Currency Exchange ◽  
Adjustment Model ◽  
Adaptive Expectation

Since 1998, Indonesia capital market experiencing rapid development, go public activity in stock exchange and stock trading activity getting crowded. People interest observes monetary factors such as money circulation, deposit interest, foreign currency exchange, and inflation that predicted affecting compound stock index in Jakarta stock exchange from 1998 to 2002. Time series data from 1998-2002 gained from published issues like financial statement Indonesian Bank, Body of Statistic Center, and other sources. This research using adaptive expectation model analysis tools, that is rationalization model proposed by Nerlove, as stock adjustment model or partial adjustment model (PAM). Use of this model bring advantage in short and long term analysis.

scholarly journals Faktor Makro Ekonomi Yang Mempengaruhi Pergerakan Harga Saham Pada Indeks Saham Syariah Indonesia (ISSI) di Bursa Efek Indonesia (BEI)

2015 ◽  
Vol 2 (11) ◽  
pp. 928
Author(s):  
Martien Rachmawati ◽  
Nisful Laila
Keyword(s):  
Exchange Rate ◽  
Interest Rates ◽  
Stock Price ◽  
Time Series Data ◽  
Stock Exchange ◽  
Stock Index ◽  
Series Data ◽  
Regression Result ◽  
Statistical Tool ◽  
Negative Effect

The capital market presence is such an important concern for many country because it relate to its function as economic booster through investation. This study aims to analyze macro economic factors that can affect the movement of stock price at Indonesia Sharia Stock Index in Indonesia Stock Exchange as the inflation factor, SBI interest rates and exchange rates. The method used in this research is quantitative approaches in which data is obtained from Indonesia Stock Exchange and Bank of Indonesia. The data used is the time series data starting from January 2012 to April 2015. The statistical tool used is multiple linear regression. Result showed that partially inflation is not significant and have a negative relation toward ISSI’s stock price, SBI interest rate is not significant and have a positive relation toward ISSI’s stock price, exchange rate significantly influence the stock price at Indonesia Sharia Stock Index (ISSI) and have a negative effect. Simultaneously, both variable inflation rate, SBIinterest rate and the exchange rate significantly influence the stock price’s movement at Indonesia Sharia Stock Index (ISSI).

Forecasting of Stock Price Using Autoregressive Integrated Moving Average Model

2019 ◽  
Vol 16 (8) ◽  
pp. 3519-3524
Author(s):  
Loh Chi Jiang ◽  
Preethi Subramanian
Keyword(s):  
New York ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Stock Exchange ◽  
Moving Average ◽  
Arima Model ◽  
Stock Index ◽  
Series Data ◽  
Autoregressive Integrated Moving Average

Finance sector is highly volatile where the stock prices fluctuate rapidly and it is usually challenging to forecast. The unstable conditions and rapid changes can drastically modify the monetary value of an organization or an individual. Hence, the prediction of stock prices continues to remain as one of the sizzling and vital topics in the applications of data mining in the finance sector. This forecasting is significant as it has the potential to reduce the losses that happen mainly due to erroneous intuitions and blind investment. Moreover, the prediction of stock prices endure to increase in complexity with accumulation of more and more historical data. This paper focuses on American Stock Market (New York Stock Exchange and NASDAQ Stock Exchange). Taking into account the complexity of the prediction, this research proposes Autoregressive Integrated Moving Average (ARIMA) model for estimating the value of future stock prices. ARIMA demonstrated better results for prediction as it can handle the time series data very well which is suitable for forecasting the future stock index.

Multi-Factor Fuzzy Time Series Model Based on Stock Volatility for Forecasting Taiwan Stock Index

2011 ◽  
Vol 211-212 ◽  
pp. 1119-1123 ◽  
Author(s):  
Ching Hsue Cheng ◽  
Jing Wei Liu ◽  
Tzu Hsuan Lin
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Stock Exchange ◽  
Time Series Model ◽  
Fuzzy Time Series ◽  
Stock Index ◽  
Series Data ◽  
Stock Volatility ◽  
Taiwan Stock Exchange ◽  
Proposed Model

Fuzzy time series have in recent years drawn many scholars' attention due to their ability can handle the time series data with incomplete, imprecise and ambiguous pattern. However, most traditional time series models employed only single variable (stock index) in forecasting, yet ignored some factors that would also affect the stock volatility. Therefore, this paper proposes a novel forecasting model using multi-factor fuzzy time series model to forecast TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock index). Multi-factor fuzzy time series model is composed of three main components: stock index, trading volume and interactions between two stock markets. In order to evaluate the performance of the proposed model, the transaction records of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock index) and NASDAQ(National Association of Securities Dealers Automated Quotations) from 2000/01/04 to 2003/12/31 are used as experimental dataset and the root mean square error (RMSE) as evaluation criterion. The results show that the proposed model outperforms the listing models in accuracy for forecasting Taiwan stock market.

Revisiting the growth effects of government bonds in the emerging capital market.

2019 ◽  
Vol 3 (1) ◽  
pp. 32-38
Author(s):  
Temitayo O. Olaniyan ◽  
Samuel O. Ekundayo
Keyword(s):  
Method Of Moments ◽  
Capital Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Annual Reports ◽  
Series Data ◽  
Government Bonds ◽  
Market Growth ◽  
The Public ◽  
Generalised Method Of Moments

We revisited the effects of government bonds for the growth on the Nigerian capital market. Utilising time-series data obtained from the Nigeria Stock Exchange (NSE) annual reports for the period from 2010 to 2017, this study through the Generalised Method of Moments (GMM) regression estimator found that the value and the number of listed government bonds’ positively and significantly affect capital market growth in Nigeria. Furthermore, low capitalisation of government bonds negatively affects the growth of the market. The null hypothesis of the Hansen J-statistics is accepted; hence this implies that the IVs used in the GMM model is valid. We concluded that government bonds have positive and significant effects on the growth of the Nigerian capital market, thus government bonds have made the NSE All-Share Index grow over the period under investigation. Following the findings from the study, it was recommended, inter alia, that there should be more issuance of government bonds to the public and further to enhance the efficiency of the capital markets, both primary and secondary, while the funds raised from the capital market through government issuance should be channelled towards Nigeria’s productive sectors to promote an all-inclusive growth in the Nigerian economy.

scholarly journals Factors affecting beta in manufacturing companies in Indonesia Stock Exchange

2020 ◽  
Vol 1 (4) ◽  
pp. 259-268
Author(s):  
Retnoning Ambarwati
Keyword(s):  
Time Series Data ◽  
Stock Exchange ◽  
Least Square ◽  
Series Data ◽  
Manufacturing Companies ◽  
Financial Leverage ◽  
Online Data ◽  
Dividend Payout ◽  
Asset Growth ◽  
Asset Size

This research has want to know and prove the effect of dividend payout, asset growth, asset size, liquidity, financial leverage, earning variability and accounting beta to beta of stock simultaneously and partially in manufacturing companies at Jakarta Stock Exchange.  This research use secondary data which is collected based on time series data and cross section include 12 manufacturing company stocks as the sample. The data is collected from the online data of Jakarta Stock Exchange in YPKP, Indonesia Capital Market Directory, JSX Statistic, and Business News. The model of this research is estimated by Generalized Least Square (GLS) with Fixed Effect Model and Dummy Variable to estimate the effect of some financial variables specifically towards Beta of Stock. The result show that all of the variables in this research consistent with the theory as expected. The coefficient direction of asset growth, financial leverage, earning variability and accounting beta shows positive, while the coefficient direction of dividend payout, asset size, liquidity shows oppositely. Simultaneously all variables influence beta of stock, in the other side partially shows that asset growth, earning variability, asset size, and liquidity, have significant effect to beta, whereas dividend payout ratio, financial leverage and accounting beta do not have significant effect. One of the implications of this research is that the study of beta of stock should be more comprehensively, not only contains micro variables but also the macro variables as well include dimension of social economy and politic

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.

scholarly journals On the volatility of sensex

2012 ◽  
Vol 1 (1) ◽  
pp. 10-22
Author(s):  
Nateson C ◽  
Suganya D
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
The Other ◽  
Stock Index ◽  
Series Data ◽  
Closing Time ◽  
Market Activity ◽  
Year 2000 ◽  
Daily Returns

The present study seeks to analyse Volatility of popular stock index SENSEX. The present study is based on the closing time series data of SENSEX covering the period from 3rd January 2000, to 30th June 2011. The year 2008 has recorded higher Volatility compared to the other years of the study. Volatility fell in the year 2009 from the high of 2008. The years after were comparatively calmer. In the year 2000, the Volatility was higher signifying enhance market activity. The overall daily Volatility for SENSEX was approximately 1.70 % while the annualized value was approximately 25%-26%. Events Reported around Daily Returns in Excess of +/-5%have also been identified.

scholarly journals MENINGKATKAN KINERJA KEUANGAN RETURN ON EQUITY (ROE) MELALUI RASIO STRUKTUR MODAL DEBT TO ASSET RATIO (DAR) DAN DEBT TO EQUITY RATIO (DER) PADA PT BANK MANDIRI TBK YANG TERDAFTAR DI BURSA EFEK INDONESIA

2021 ◽  
Vol 12 (1) ◽  
pp. 52-65
Author(s):  
Armalinda Armalinda
Keyword(s):  
Financial Performance ◽  
Quantitative Research ◽  
Time Series Data ◽  
Stock Exchange ◽  
Statistical Tests ◽  
Financial Statements ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Return On Equity ◽  
Equity Ratio

This study aims to determine how much influence the Debt to Assets Ratio (DAR) and Debt to Equity Ratio (DER) have on the Return on Equity (ROE) of PT Bank Mandiri Tbk which are listed on the Indonesia Stock Exchange. The research design used in this research is associative/quantitative research. The population in this study is the annual financial statements of PT. Bank Mandiri Tbk for the period 2012-2019, while the sample was taken using time series data, namely the annual financial statements of PT. Bank Mandiri Tbk for the period 2012-2019 which consists of balance statements, income statements, and cash flow from funding activities from 2012 to 2019. The result of the coefficient of determination (R Square) is 0.813. This figure means that 0.813 or 81.3% of the diversity of data from financial performance data can be explained by the two independent variables, namely the Debt to Asset Ratio and the Debt to Equity Ratio. While the rest (1-0.813 = 0.817) or 18.7% is explained by other factors outside the study. The results of statistical tests show that the Asset Ratio and Debt to Equity Ratio together (simultaneously) have an effect on financial performance (Return on Equity).

scholarly journals The dynamic relationship between stock returns and trading volumes in Nepalese stock market

2020 ◽  
Vol 23 (2) ◽  
pp. 161-172
Author(s):  
Prem Lal Adhikari
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Trading Volume ◽  
Time Series Data ◽  
Stock Exchange ◽  
Causal Effect ◽  
Empirical Relationship ◽  
Insurance Companies ◽  
Series Data ◽  
Dynamic Relationship

 In finance, the relationship between stock returns and trading volume has been the subject of extensive research over the past years. The main motivation for these studies is the central role that trading volume plays in the pricing of financial assets when new information comes in. As being interrelated and interdependent subjects, a study regarding the trading volume and stock returns seem to be vital. It is a well-researched area in developed markets. However, very few pieces of literature are available regarding the Nepalese stock market that explores the association between trading volume and stock return. Realizing this fact, this paper aims to examine the empirical relationship between trading volume and stock returns in the Nepalese stock market using time series data. The study sample is comprised of 49 stocks traded on the Nepal Stock Exchange (NEPSE) from mid-July 2011 to mid-July 2018. This study examines the Granger Causality relationship between stock returns and trading volume using the bivariate VAR model used by de Medeiros and Van Doornik (2008). The study found that the overall Nepalese stock market does not have a causal relationship between trading volume and return on the stock. In the case of sector-wise study, there is a unidirectional causality running from trading volume to stock returns in commercial banks and stock returns to trading volume in finance companies, hydropower companies, and insurance companies. There is no indication of any causal effect in the development bank, hotel, and other sectors. This study also finds that there is no evidence of bidirectional causality relationships in any sector of the Nepalese stock market.

scholarly journals Peran Grup Afiliasi dalam Memoderasi Pengaruh Hutang terhadap Nilai Perusahaan pada Perusahaan Property & Real Estate yang terdaftar di Bursa Efek Indonesia

FORUM EKONOMI ◽  
2017 ◽  
Vol 19 (1) ◽  
pp. 58
Author(s):  
Fina Maulidyani ◽  
Set Asmapane ◽  
Ledy Setiawati
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Stock Exchange ◽  
Debt Financing ◽  
Series Data ◽  
Simple Linear Regression ◽  
Group Affiliation ◽  
A Company ◽  
Positive Effect

The objective of this research is to examine empirically the effect of Debt on Firm’s Value and the ability of Group Affiliation to moderate the effect of Debt toward Firm’s Value by using an approach simple linear regression and Moderated Regression Analysis (MRA). This research uses time series data in 2011 – 2015 for company's finance data that got from Indonesia Stock Exchange. Election Procedure sample uses purposive sampling and the result are existed 35 companies that fulfill criterion. The results show that Debt has positive effect on Firm’s Value, while Group Affiliation act as a moderating variable can reduce the effect of Debt toward Firm’s Value. The higher capability of group affiliation to take control of a company, the lower debt financing that company has.Keywords:     Debt Financing, Firm’s Value, Group Affiliation

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