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Artykuły w czasopismach na temat „DJIA index”

Autor: Grafiati

Data publikacji: 5 czerwca 2025

Data aktualizacji: 1 sierpnia 2025

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1

Platt, Harlan D., Licheng Cai, and Marjorie A. Platt. "Is the DJIA Index Biased?" Journal of Index Investing 4, no. 4 (2014): 43–52. http://dx.doi.org/10.3905/jii.2014.4.4.043.

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Iman, Shofal, Imron Mawardi, and Md Atiqur Rahman Sarker. "ANALYSIS OF INTERNATIONAL INDEX ON INDONESIAN SHARIA STOCK INDEX." Jurnal Ekonomi dan Bisnis Islam (Journal of Islamic Economics and Business) 6, no. 1 (2020): 60. http://dx.doi.org/10.20473/jebis.v6i1.10961.

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This study aims to determine the influence of long-term and short-term global stock index on the Indonesian Islamic stock index. The approach used is a quantitative approach and uses the Error Correction Model (ECM) method. ECM is an analytical model that can be used in time series data to estimate the effect of independent variables on long-term and short-term use variables. The sample used was taken from secondary data, namely global stock index data consisting of the DJIA, N225 and HSI indices, and the Indonesian sharia stock index in the form of the ISSI index in the period of January 2013

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3

Nurwulandari, Andini. "KURS IDR, KURS JPY, Indeks DJIA, serta Harga Minyak Dunia terhadap IDX pada Tahun 2017-2021." Journal of Management and Bussines (JOMB) 4, no. 1 (2022): 560–77. http://dx.doi.org/10.31539/jomb.v4i1.3711.

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This study aims to analyze the development of the index of the influence of the IDR exchange rate, JPY exchange rate, DJIA index, and world oil prices on IDX to find out how the development of stock price index to IDR, JPY exchange rate, DJIA index, and world oil prices to IDX in 2017-2021 . The research method used is descriptive quantitative. The analytical method used is a statistical method, namely multiple linear regression analysis. The results showed, based on the linear regression test, the equation was obtained, namely IDX t = -4040.77 -0.144IDR + 50.011JPY + 0.113DJIA + 0.237oil + 0.

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4

R, Abdul Azis. "Moderation of Dow Jones Industrial Average in the Dynamics of Indonesian Sharia Stock Index: Global Sharia Index and Macroeconomic Review." Jurnal Ilmiah Manajemen dan Bisnis 11, no. 1 (2025): 42. https://doi.org/10.22441/jimb.v11i1.32007.

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This research seeks to examine the impact of the Global Islamic Stock Index (Dow Jones Islamic Market US) and macroeconomic factors (Inflation, BI Rate, Exchange Rate, and Money Supply) on the Indonesian Sharia Stock Index, with the Dow Jones Industrial Average (DJIA) acting as a moderating variable. Employing a quantitative methodology, the study incorporates descriptive analysis and hypothesis testing using the SmartPLS application to assess estimation outcomes. Secondary data from 2014 to 2023, including monthly Inflation, BI Rate, Exchange Rate, and Money Supply figures, taken from the off

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5

Al Faridho Awwal, Muhammad, Ita Eviyanah, and Abdul Qoyum. "INTEGRASI PASAR MODAL ISLAM: STUDI DI LIMA NEGARA ASEAN DAN DJIA." Ekonomi Islam 13, no. 1 (2022): 52–64. http://dx.doi.org/10.22236/jei.v13i1.8073.

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This study aims to determine the short- and long-term relationship between the Islamic capital market in Southeast Asia and the DJIA. This study takes data from the Islamic capital markets of ASEAN-5 countries, namely the Jakarta Islamic Index (JII), FTSE Malaysia, FTSE SET Sharia Thailand, FTSE SGX Sharia Singapore and MSCI Philippines and DJIA. A total of 211 weekly observations of each index were observed from 04 January 2015, to 03 February 2019. Author have found that the Islamic capital market is integrated in all ASEAN-5 countries including the DJIA. This study also finds that the Malay

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6

Alawneh, Ateyah. "Investigation of Co-Integration between Standard and Poor Index and Dow Jones Index in the New York Financial Market." International Journal of Economics and Finance 10, no. 5 (2018): 197. http://dx.doi.org/10.5539/ijef.v10n5p197.

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The study investigates the co-integration between (the S&P 500 index)and (Dow Jones index) the DJIA by busing the method Engle-granger co-integration Test. The study use annual data from 1990 to 2016.The study examines the stability of the index of S&P 500 and DJIA using the E-views program through a unit root test. The study found that the indicators are unstable, but they become stable when taking the first difference. This condition integrates (the S&P 500 index) and (the DJIA index) during the long-term co-integration test. The analysis shows that there is a negative co-integra

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7

Biktimirov, Ernest N., and Yuanbin Xu. "Market reactions to changes in the Dow Jones industrial average index." International Journal of Managerial Finance 15, no. 5 (2019): 792–812. http://dx.doi.org/10.1108/ijmf-10-2017-0226.

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Purpose The purpose of this paper is to examine changes in stock returns, liquidity, institutional ownership, analyst following and investor awareness for companies added to and deleted from the Dow Jones Industrial Average (DJIA) index. Previous studies report conflicting evidence regarding the market reactions to changes in the DJIA index membership. Design/methodology/approach This study uses the event-study methodology to calculate abnormal returns and trading volume around the announcement and effective days of DJIA index changes from 1929 to 2015. It also tests for significant changes in

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8

Borowski, Krzysztof. "Analysis of monthly rates of return in April on the example of selected world stock exchange indices." Equilibrium 11, no. 2 (2016): 307. http://dx.doi.org/10.12775/equil.2016.014.

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The article presents a study of the effectiveness of 22 selected stock indices with the use of the rates of return in the month of April. The portfolio replicating the stock index was bought at the closing prices on the last session in March, and sold at the closing prices on the last session in April. The presence of market inefficiency is demonstrated in cases of the following indices: All-Ord, AMEX, BUX, CAC40, DAX, DJIA, DJTA, DJUA, EOE, FTSE100, SMI, SP500, but for the following indices: B-Share, Bovespa, Buenos, Hang-Seng, MEX-IPC, Nasdaq, Nikkei, Russel, TSE and WIG, the obtained monthl

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9

Adira Prameswari Puteri and Nora Amelda Rizal. "Analisis Kausalitas Nilai Tukar Rupiah/USD, Dow Jones Industrial Average (DJIA), Nikkei225, Shanghai Index Composite (SSEC) Terhadap Indeks Harga Saham Gabungan (IHSG)." El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam 5, no. 5 (2024): 3619–28. http://dx.doi.org/10.47467/elmal.v5i5.1764.

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The COVID-19 pandemic has had a negative effect on global stock markets. In addition, the increase in the number of confirmed cases of COVID-19 further increased the volatility of the exchange rate. This study aims to determine whether there is a causal relationship between the Exchange Rate, the Dow Jones Industrial Average (DJIA), the Nikkei225 Index, and the Shanghai Stock Exchange Composite Index (SSEC) and the Composite Stock Price Index (CSPI). The research method used is the Augmented Dickey Fuller Unit Root Test, and Granger Causality. The results of the study using Granger Causality i

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10

Jumintang, Franciskus, and Kery Utami. "Analysis of efficient market anomaly on stock returns on Indonesia's composite stock price index and global stock price index." International Journal of Business Ecosystem & Strategy (2687-2293) 4, no. 1 (2022): 57–67. http://dx.doi.org/10.36096/ijbes.v4i1.309.

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Market anomaly is an occurring phenomenon in the market. Supposedly, an anomaly does not exist in markets that are considered efficient. An anomaly is an aberration in the efficient market theory where existing information does not reflect stock prices; therefore, investors can earn abnormal returns. This study examines how The Day Of The Week Effect and The Month Of The Year Effect affect stock returns on the Indonesian Stock Price Index and the Global Stock Price Index. Samples in this study are daily stock return data and return data on stocks of IHSG, DJIA, SSEC, and N225. The Generalized

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11

Santoso, Kevin, Tannia Tannia, Elkunny Dovir Siratan, Anastasia Erdina Renaganis, Jessie Jessie, and Handoko Handoko. "THE EFFECT OF THE GLOBAL STOCK EXCHANGE INDEX ON THE INDONESIA COMPOSITE INDEX (ICI) IN THE INDONESIA STOCK EXCHANGE FOR 2016-2021 PERIOD." Jurnal Muara Ilmu Ekonomi dan Bisnis 7, no. 1 (2023): 126–39. http://dx.doi.org/10.24912/jmieb.v7i1.22807.

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Faktor pergerakan indeks global sering dijadikan indikator oleh investor dalam mengambil keputusan bertransaksi di pasar modal Indonesia. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh indeks pasar saham global khususnya DJIA, FTSE 100, SSEC, dan Indeks Straits Times terhadap Indeks Harga Saham Gabungan (ICI) di Bursa Efek Indonesia. Penelitian ini merupakan penelitian kuantitatif dengan menggunakan data sekunder berupa time series harga penutupan akhir bulan dari setiap indeks pasar saham pada bulan Oktober 2016 sampai dengan September 2021. Hasil penelitian menunjukkan bahwa dal

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12

Shelly Midesia. "Pengaruh Dow Jones Industrial Average dan Indeks Hang Seng terhadap Indeks Harga Saham Gabungan pada Tahun 2021." Jurnal Penelitian Ekonomi Akuntansi (JENSI) 6, no. 2 (2022): 129–35. http://dx.doi.org/10.33059/jensi.v6i2.6740.

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The Jakarta Composite Index (IHSG) movement is indispensable for capital market investors in their decision-making steps. This study aims at determining the effect of the Dow Jones Industrial Average and Hang Seng Index on the Jakarta Composite Index. The data used in the research are the daily close prices of IHSG, DJIA, and HSI in 2021. Regression analysis was used for data analysis, using the SPSS data processing tool. The results indicate that DJIA and HSI partially and simultaneously affect the IHSG.

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13

Tse, Yiuman, Paramita Bandyopadhyay, and Yang-Pin Shen. "Intraday Price Discovery in the DJIA Index Markets." Journal of Business Finance & Accounting 33, no. 9-10 (2006): 1572–85. http://dx.doi.org/10.1111/j.1468-5957.2006.00639.x.

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14

Anagnoste, Sorin, and Petre Caraiani. "The Impact of Financial and Macroeconomic Shocks on the Entropy of Financial Markets." Entropy 21, no. 3 (2019): 316. http://dx.doi.org/10.3390/e21030316.

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We propose here a method to analyze whether financial and macroeconomic shocks influence the entropy of financial networks. We derive a measure of entropy using the correlation matrix of the stock market components of the DOW Jones Industrial Average (DJIA) index. Using VAR models in different specifications, we show that shocks in production or the DJIA index lead to an increase in the entropy of the financial markets.

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15

Susilo, Didik, Sugeng Wahyudi, and Irene Rini Demi Pangestuti. "Factors Affecting the Indonesia Stock Exchange: A Multi-Index Approach." International Journal of Financial Research 11, no. 2 (2020): 196. http://dx.doi.org/10.5430/ijfr.v11n2p196.

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This study examines the influence of world and regional capital market conditions on the Indonesian capital market (Indonesia Stock Exchange) condition. The DJIA (Dow Jones Industrial Average) index was used as a representative of the international capital market while the Hang Seng index and the Nikkei 225 index were used as a representative of regional capital market conditions. These two indices were chosen because the Japanese capital market was one of the most advanced capital markets in the world and the Hong Kong capital market, although not as big as Japan, still played an important ro

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16

Dahlia Pinem, M. B. Nani Ariani, and Desmintari. "Analysis of global stock index, inflation and interest rates on the Indonesia Stock Exchange joint stock price index." International Journal of Research in Business and Social Science (2147- 4478) 12, no. 3 (2023): 308–17. http://dx.doi.org/10.20525/ijrbs.v12i3.2560.

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This study examines the influence of global stock indices and macroeconomic conditions in Indonesia on the Jakarta Composite Index (JCI). The global stock indices analyzed in this study are the Dow Jones Industrial Average (DJIA), Nikkei 225 (N225), Shanghai Stock Exchange Composite (SSE), Strait Singapore index. The macroeconomic indicators that analyzed in this study are the inflation rate, the US dollar exchange rate against the Indonesian rupiah, and the BI rate. This study was conducted using secondary data. The research period was 3 years for 36 months from January 2018 to December 2020.

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17

Suwardi, Suwardi, and Agus Amri Mokoginta. "ANALYSIS OF THE EFFECT OF FTSE 100, NIKKEI 225, AND DOW JONES INDUSTRIAL AVERAGE ON COMPOSITE STOCK INDEX IN INDONESIA STOCK EXCHANGE." Dinasti International Journal of Economics, Finance & Accounting 1, no. 6 (2021): 1003–12. http://dx.doi.org/10.38035/dijefa.v1i6.723.

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This study aims to analyze the effect of FTSE 100, Nikkei 225, and Dow Jones Industrial Average on Composite Stock Index in Indonesia Stock Exchange (IDX). The research method used is a quantitative method with time series data type and secondary data obtained the Indonesia Stock Exchange (IDX) website and Bloomberg Data Terminal. The sampling technique used purposive sampling method with monthly data and research period from January 2015 to December 2019. The data analysis technique used is multiple linear regression with normality test, classic assumption test (multicollinearity test, autoco

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18

Qader Yaqub, Kamaran. "Effect of United States Monetary Policy and Macroeconomics on the Dow Jones Industrial Average Pre, during and Post Covid-19 Period." Journal of University of Raparin 12, no. 2 (2025): 675–707. https://doi.org/10.26750/vol(12).no(2).paper31.

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The impact of the US monetary policy and the US macroeconomic variables, on the stock market specifically in relation to the Dow Jones Industrial Average (DJIA), is a subject of ongoing debate. This paper seeks to investigate and examine the consequences of changes in monetary policy and some macroeconomic variables in the United States on the US stock market (only DJIA was selected) for the period of January 2017 to June 2023. By analyzing these relationships across different time frames, this research seeks to provide a comprehensive understanding of how various US monetary and US macroecono

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19

Lopes, António M., and Jóse A. Tenreiro Machado. "Dynamical Analysis of the Dow Jones Index Using Dimensionality Reduction and Visualization." Entropy 23, no. 5 (2021): 600. http://dx.doi.org/10.3390/e23050600.

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Time-series generated by complex systems (CS) are often characterized by phenomena such as chaoticity, fractality and memory effects, which pose difficulties in their analysis. The paper explores the dynamics of multidimensional data generated by a CS. The Dow Jones Industrial Average (DJIA) index is selected as a test-bed. The DJIA time-series is normalized and segmented into several time window vectors. These vectors are treated as objects that characterize the DJIA dynamical behavior. The objects are then compared by means of different distances to generate proper inputs to dimensionality r

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20

Prajapati, Mahendra. "COMPARATIVE ANALYSIS OF THE US STOCK MARKET PERFORMANCE: PRE AND POST COVID-19." Sachetas 2, no. 3 (2023): 43–48. http://dx.doi.org/10.55955/230004.

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The financial markets have been significantly impacted by the global COVID-19 epidemic due to international lockdowns and decreased demand, which has further exacerbated the economic situation, including a decline in crude oil prices. The country has experienced economic consequences as a result of the coronavirus and subsequent lockdown measures. The Dow Jones Industrial Average (DJIA) is a price-weighted stock market index that tracks 30 major companies listed on US stock exchanges. While the DJIA is a widely recognized equity index, some professionals argue that it may not provide a compreh

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21

Urbański, Stanisław. "The Cost of Capital for Investment in the Warsaw Stock Exchange Indexes – Versus Djia." Folia Oeconomica Stetinensia 21, no. 1 (2021): 122–43. http://dx.doi.org/10.2478/foli-2021-0009.

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Abstract Research background and purpose: The CAPM, Fama-French and modified Fama-French models were used to estimate the cost of the capital of the DJIA and selected Polish stock indexes were used. The estimated cost of capital was the cost of the portfolio of corporate investment projects estimated by market returns. Research methodology: The model tests were run on 276 monthly returns of stocks listed on the markets in the years 1995–2019. The bootstrap method to estimate the confidence interval of the cost of capital was used. Results: The highest and positive cost of capital median was fo

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22

Mahmudah, Faizatul. "PENGARUH VARIABEL MAKROEKONOMI DAN BEBERAPA SAHAM GLOBAL TERHADAP INDEKS HARGA SAHAM GABUNGAN 2015-2019." EKOMBIS: JURNAL FAKULTAS EKONOMI 7, no. 2 (2021): 1. http://dx.doi.org/10.35308/ekombis.v7i2.3903.

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This study aims to explain the effect of the Dow Jones Industrial Average Index (DJIA). Kuala Lumpur Composite Index (KLSI), Shanghai Stock Composite Index (SSEC), inflation, interest rates, exchange rates,(Exchange rate), to the Composite Stock Price Index (IHSG). Using the Multiple Linear Regression analysis methods, with monthly samples from January 2015 to December 2019 which is resulted in 60 research samples. The test results using the Multiple Linear Regression method show that the DJIAI, KLCI has a positive and significant effect, the SSEC index and the BI rate have a negative and sign

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23

Handayani, Wiwik, and Safitri Oktavia. "Effect of Rupiah Exchange Rate, GDP Growth, and Dow Jones Index on Composite Stock Price Index in Indonesia Stock Exchange." Journal of Accounting and Strategic Finance 1, no. 01 (2018): 23–32. http://dx.doi.org/10.33005/jasf.v1i01.24.

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 A capital market is a meeting place for stock sellers and buyers with the aim of getting maximum profits. To get these benefits, investors need information about the stock price index. Factors that influence the Stock Price Index are important information for investors. The composite stock price index (CSPI) is one of the main indicators that reflects the performance of the capital market whether it is experiencing an increase or is experiencing a decline. These factors include the rupiah exchange rate, GDP growth, and the Dow Jones index. This study aims to prove and analyze the effect

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24

Mahfudz, Muhammad Baharudin, and Nurhadi Nurhadi. "Pengaruh Indeks DJIA, Harga Minyak Dunia, Tingkat Inflasi, dan Nilai Tukar Rupiah terhadap ISSI." Al-Kharaj : Jurnal Ekonomi, Keuangan & Bisnis Syariah 3, no. 2 (2021): 254–69. http://dx.doi.org/10.47467/alkharaj.v3i2.370.

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Indonesia is a country where the majority of the population is Muslim, so information about the Sharia Stock Index has an important role in understanding the dynamics of the capital market in Indonesia. This study aims to determine the simultaneous and partial influence of Dow Jones Industrial Average (DJIA), World Oil Price, Inflation Rate, and Rupiah Exchange Rate on Indonesia Sharia Stock Index (ISSI). This study uses secondary data in the form of a summary of monthly index reports obtained from financial websites. The population in this study is a time series data that amounts to 60 months

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25

Noviyani, Safiinatul Jannah, and Rusdi Hidayat Nugroho. "Pengaruh Indeks Dow Jones Industrial Average (DJIA), Tingkat Inflasi, Bi 7-Day Repo Rate, dan Kurs USD/IDR terhadap Indeks Saham Syariah IndonesiA (ISSI) di Bursa Efek Indonesia (BEI)." Al-Kharaj : Jurnal Ekonomi, Keuangan & Bisnis Syariah 5, no. 1 (2022): 93–107. http://dx.doi.org/10.47467/alkharaj.v5i1.1130.

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Indonesia is one of the largest Muslim countries in the world that makes sharia investments in the capital market with efforts to develop the Islamic financial sector. Several factors that influence stock price fluctuations include global indices and macroeconomic variables. This study aims to determine the simultaneous and partial effect of the Dow Jones Industrial Average (DJIA), Inflation Rate, BI 7-Day Repo Rate, and USD/IDR Exchange Rate on the Indonesian Sharia Stock Index (ISSI). This study uses secondary data in the form of monthly index summary reports obtained from financial websites

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26

Fangsawinata, Hendro, Ratna Septiyanti, and Agus Zahron Idris. "The effect of the US Dollar Index and foreign stock indexes on Jakarta Composite Index (JKSE)." Asian Journal of Economics and Business Management 2, no. 1 (2023): 378–89. http://dx.doi.org/10.53402/ajebm.v2i1.272.

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Many theories explain that the Jakarta Composite Index (JKSE) can be influenced by stock indices or currencies of other countries. With the recent events of the war between Russia and Ukraine, this might be the perfect opportunity to prove that statement. The purpose of this study is to see whether the United States Dollar Index, Dow Jones Industrial Average (DJIA), NASDAQ 100 Index, Shanghai Composite Index (SSEC), Nikkei 225 Index (N225), Australian All Ordinaries Index (AORD), FTSE Index 100, against the Jakarta Composite Index (JKSE). This study uses the documentation method with secondary

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27

Nuraeni, Risky, and Jihad Lukis Panjawa. "Analisis pengaruh indeks saham asing terhadap indeks harga saham gabungan dengan pendekatan Error Correction Model." Journal of Economics Research and Policy Studies 1, no. 1 (2021): 25–39. http://dx.doi.org/10.53088/jerps.v1i1.37.

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The Composite Stock Price Index (IHSG) is a composite index of many shares listed on the stock exchange and their movements show conditions that occur in the capital market. JCI is confident of macroeconomic factors and foreign exchange indexes. The purpose of this study was to analyze the effect of the Dow Jones Index, the Straits Time Index, the Hang Seng Index, the Nikkei 225 Index, and the FTSE 100 Index on the composite price index. The research method used is the Error Correction Model (ECM). In the short term, the DJIA and FTSE 100 variables have a positive effect on the JCI, the STI an

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Wulandari, Rosita, Adhitya Putri Pratiwi, Nopagia Nopagia, and Suripto Suripto. "Empirical Test of Composite Stock Price Index: Regional Stock Index." JABI (Jurnal Akuntansi Berkelanjutan Indonesia) 6, no. 1 (2023): 21–36. http://dx.doi.org/10.32493/jabi.v6i1.y2023.p21-36.

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The Composite Stock Price Index (JCI) is an indicator of price movements of all shares on the Indonesia Stock Exchange where one of the factors that can influence the movement of the JCI in Indonesia is the Global Stock Index. This study aims to determine the effect of the Global Stock Index on the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange, and to analyze the Global Stock Index which has a dominant influence on the JCI. The object of this research was conducted on 5 global stock indices that are located close to and which have a major influence on the world economy on

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Simabur, Yusuf, and Joan Marta. "PENGARUH VARIABEL MAKROEKONOMI DAN KONDISI PASAR MODAL INTERNASIONAL TERHADAP INDEKS HARGA SAHAM GABUNGAN." Ecosains: Jurnal Ilmiah Ekonomi dan Pembangunan 3, no. 2 (2014): 147. http://dx.doi.org/10.24036/ecosains.10961157.00.

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This study aims to analyze the effect of macroeconomic variables and international capital market conditions on the stock price index, namely: Effect of macroeconomic variables and the International Capital Markets Index against JCI in short-term. Short- term and long term research is descriptive and associative. The type of data in this study is secondary data from the years 2004-2013 in the form of time series data obtained from the IDX Statistics and Bank Indonesia publications. The analytical method used is the Error Correction Model.Hasil study are (1) BI Rate, Exchange Rate and STI have

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Wahyudi, Heru, and Figa Ramani. "Pengaruh Jangka Pendek dan Jangka Panjang Saham Global terhadap Indeks Harga Saham Gabungan (IHSG) Periode 2015:M01 - 2020:M12." Reviu Akuntansi, Manajemen, dan Bisnis 2, no. 1 (2022): 15–25. http://dx.doi.org/10.35912/rambis.v2i1.1421.

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Abstract: Purpose: This study aims to analyze the external and internal factors that affect the movement of the Composite Stock Price Index (IHSG) in Indonesia in the short and long term. External influences of global stock indices are DJIA, NIKKEI225 and SSEC, as well as the exchange rate (USD/IDR). The most influential internal influence is inflation. Research methodology: This study uses the ECM (Error Correction Model) method. ECM aims to determine the long-term and short-term effects of variables that affect the JCI in Indonesia. In addition, this study uses monthly time series data from

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Setyawan, Ignatius Roni, Rorlen Rorlen, and Margarita Ekadjaja. "KOINTEGRASI BURSA EFEK INDONESIA DENGAN BURSA EFEK AMERIKA SERIKAT, JEPANG, HONGKONG, DAN MALAYSIA." Jurnal Muara Ilmu Ekonomi dan Bisnis 5, no. 2 (2021): 335. http://dx.doi.org/10.24912/jmieb.v5i2.11838.

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Penelitian ini bertujuan untuk menganalisis kointegrasi bursa efek di negara Amerika Serikat, Jepang, Hongkong, Malaysia, dan Indonesia dari tahun 2008-2020 dengan menggunakan model Vector Autoregressive Model. Penelitian ini dilakukan pada rentang waktu selama 156 bulan, di mana data yang diamati pasca krisis global di dunia (2008-2014) dan saat kemajuan ekonomi Cina yang berdampak pada perang dagang dengan USA (2014-2020). Berdasarkan hasil olah data dengan menggunakan aplikasi eviews 9.0 ditemukan adanya kointegrasi antara bursa efek di negara Amerika Serikat, Jepang, Hongkong, Malaysia, da

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Dini, Dini Rahmayanti. "Analisis indikator makro ekonomi terhadap Jakarta Islamic Index." Journal of Economics Research and Policy Studies 1, no. 2 (2021): 117–31. http://dx.doi.org/10.53088/jerps.v1i2.234.

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Stock price fluctuations in various sectors continue to show a decline because of the Covid-19 pandemic. This is because of its nature, which is strongly influenced by external changes or fundamental information. Here, the ability of investors to understand will influence investors' decisions to invest. This study aims to determine the effect of macroeconomic indicators on the Jakarta Islamic Index, the observation period 2015-2021, using monthly time series data. Macro indicators used in analyzing the stock of the Jakarta Islamic Index are inflation, interest rates, industrial production grow

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Artha, Algia, and R. A. Sista Paramita. "Pengaruh Makroekonomi dan Indeks Global terhadap Indeks Harga Saham Gabungan Selama Pandemi COVID-19 di Indonesia." Jurnal Ilmu Manajemen 9, no. 2 (2021): 681. http://dx.doi.org/10.26740/jim.v9n2.p681-697.

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The COVID-19 pandemic has affected many sectors, one of which is the capital market. The Coronavirus has claimed lives and can shake the order of life of a country. From an economic point of view, almost all countries experience a recession, a reduction in economic activity, increased unemployment, and a decline in people's purchasing power. This research examines the effect of the BI interest rate, exchange rate, inflation, SSEC index, KLSE index, SET index, and DJIA index on the Composite Stock Price Index. The research population is daily data during the COVID-19 pandemic in Indonesia from

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Wu, Maoguo, and Yanyuan Wang. "Risk Analysis of World Major Stock Index Before and After the 2008 Financial Crisis – Based on GARCH-VaR Approach." International Journal of Financial Research 9, no. 2 (2018): 39. http://dx.doi.org/10.5430/ijfr.v9n2p39.

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In 2008, the U.S. subprime mortgage crisis overwhelmed the global financial system, which sparked drastic fluctuation of world stock index. Subsequently, the risk of investment in global stock markets has augmented considerably. Applying the VaR approach based on GARCH model, this paper attempts to thoroughly investigate the volatility of S&P 500, NASDAQ, DJIA, GDAXI and CSI 300. For the purpose of comparison, data are divided into 2 parts: before the 2008 financial crisis and after the 2008 financial crisis. Thus, the paper elaborates impacts of the 2008 financial crisis on global stock i

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Santosa, Perdana Wahyu, and Salsabila Roselli. "The Effect of Macroeconomic Indicators, Crude Oil Prices, and the Dow Jones Index on the Jakarta Composite Index." Jurnal Orientasi Bisnis dan Entrepreneurship (JOBS) 4, no. 1 (2023): 57–68. http://dx.doi.org/10.33476/jobs.v4i1.3624.

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This research aims to analyze the influence of macroeconomic factors, such as Exchange Rate, BI Rate, Inflation, Gross Domestic Product, Crude Oil Price, and Dow Jones Industrial Average Index (DJIA) on the Jakarta Composite Index (JCI) for the 2014-2018 period. The analytical method used is the Error Correction Model (ECM) with a significant level of 5% with E-views 10 software. The results of partial research show that in the short and long term, the Exchange Rate and Oil Price significantly negatively affect the JCI and BI Rate in the short term and have a significant negative relationship

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Pindiga, Sushma Niveni. "Time-Series Forecasting: Predicting Stock Index Using Arima and Facebooks Prophet Model." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 4832–39. http://dx.doi.org/10.22214/ijraset.2022.45073.

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Abstract: The DJIA is a New York Stock Exchange volatility index that incorporates the 30 maximum widespread shares inside the U.S stock market. Since the stock market is based totally on threats and speculations, forecasting the DJIA index helps us know the trends of 30 companies indexed. As a result, it helps investors of these 30 companies to be cautious. But forecasting these stock indexes could be challenging to assess as they were affected by various causes, making the prediction inaccurate. Throughout the paper, specific modifications had been accomplished at the version to increase the

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Lesmana, Alvin. "The Effect of the World Exchange Indexes (DJIA, SSEC and NIKKEI 225) on the Indonesia Stock Exchange Index (IDX)." Journal of Asian Multicultural Research for Economy and Management Study 3, no. 1 (2022): 1–9. http://dx.doi.org/10.47616/jamrems.v3i1.230.

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This study aims to determine the effect of the Dow Jones Industrial Average (DJIA), Shanghai Stock Exchange Composite (SSEC) and Nikkei 225 Indexes on the movement of the Indonesian Stock Exchange Index (IDX) for the period of November 2016 – November 2021. This study uses non-participant observation methods and the whole population in that time period is used as a sample. Data analysis techniques include descriptive statistics, classical assumption test. The results of the multiple linear regression analysis showed that the DJIA and Nikkei 225 indexes partially had a positive effect on the ID

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Hseu, Mei-Maun, Huimin Chung, and Erh-Yin Sun. "Price Discovery across the Stock Index Futures and the ETF Markets: Intra-Day Evidence from the S&P 500, Nasdaq-100 and DJIA Indices." Review of Pacific Basin Financial Markets and Policies 10, no. 02 (2007): 215–36. http://dx.doi.org/10.1142/s0219091507001045.

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This paper investigates the intra-day price dynamics of the S&P 500, Nasdaq-100 and DJIA indices for the periods both before and after the Nasdaq market crash which occurred between March 2000 and March 2001. We explore the relative price efficiencies of the three indices in the spot, futures, E-mini futures and ETF markets, and find that a cointegrating relationship existed between the three indices during the period after the crash. This would seem to imply that in the aftermath of the crash, the three indices shared common macroeconomic fundamentals. We find that where there is some dis

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Arafat. A, Lathif, Williya Meta, and Meilisa Meilisa. "COMPARISON OF VECTOR AUTOREGRESSIVE (VAR) AND VECTOR ERROR CORRECTION MODELS (VECM) FOR THE COMPOSITE STOCK PRICE INDEX (JCI) IN INDONESIA." TRANSEKONOMIKA: AKUNTANSI, BISNIS DAN KEUANGAN 4, no. 6 (2024): 1011–25. http://dx.doi.org/10.55047/transekonomika.v4i6.754.

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The capital market has a major role for economic development which is able to encourage capital formation and sustain economic growth. Financial liberalisation between countries in the world will make capital markets in each country interconnected. If there is a large movement in the global stock index, it will also have an impact on the JCI in Indonesia. In addition to global indices, macroeconomics is also seen as capable of influencing capital markets. Inflation and interest rates are macroeconomic components that can be used. The purpose of this research is to be able to see the relationsh

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Andi, Hermanto, Marsuki, and Iswanto Anwar Anas. "Analysis of Volatility and Factors Influence LQ45 Index and its Impact to Economic Growth in Indonesia." International Journal of Innovative Science and Research Technology 8, no. 1 (2023): 2300–2303. https://doi.org/10.5281/zenodo.7643241.

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The results of the tests conducted, it is known that the LQ45 index data is long, the research period from 1999 to 2021 all data has data which is stationary, and high volatility. Inflation did not have a direct effect on the LQ45 index during the period research from 1999 to 2021. The exchange rate does not directly affect the LQ45 index during the period research from 1999 to 2021. The Fed Rate has a direct effect on the LQ45 index during the period research from 1999 to 2021. The DJIA index has a direct effect on the LQ45 index during the period research from 1999 to 2021. The LQ45 index ha

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Dedy, Dedy, Aloysius Hari Kristianto, and Rissa Ayustia. "Pengaruh Indeks Bursa Amerika, dan Bank Indonesia – 7 Days (Reverse) Repo Rate terhadap Indeks LQ45." JURNAL MANEKSI 9, no. 2 (2021): 402–9. http://dx.doi.org/10.31959/jm.v9i2.517.

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This study aims to determine the effect of the American stock exchange index (DJIA) and the effect of Bank Infonesia – 7 Days (Reverse) Repo Rate or known as BI7dRR on one of the stock indices in Indonesia that has comapnies with high liquidity, namely the LQ45 stock index. The period used as testing data is data derived from the publication of the movement of the Dow Jones Industrial Average and LQ45 stock index and percentage data from Bank Indonesia – 7 Days (Reverse) Repo Rate (BI7dRR) in 2016 – 2019. Data source of this study is a secondary data source obtained through the official stock

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Smirnov, Valery, Denis Osipov, Vladimir Gurdzhiyan, Irina Soshko, Mikhail Alexandrov, and Vladimir Ivanov. "Analysis of the Russian finance connectivity." SHS Web of Conferences 106 (2021): 01014. http://dx.doi.org/10.1051/shsconf/202110601014.

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As a result of evaluation of growth rates of major commodity prices and Russian share quotes there is discovered dominating dynamics of shares of Rosneft and Urals oil futures. Assessment of dynamics of RTSI, IMOEX, S&P500, WTI futures, USD/RUB showed IMOEX breakdown from RTSI. RTSI remained with the WTI futures, while IMOEX joined S&P500 trend. As a result of neural network analysis of importance of global indices growth rates there is determined a condition of achievement of their maximum value – minimum growth rate of RTSI and maximum rate of FTSE100 growth. Cluster analysis of the

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Sihombing,, Pardomuan, and Rizal ,. "PENGARUH INDEKS SAHAM GLOBAL DAN KONDISI MAKRO INDONESIA TERHADAP INDEKS HARGA SAHAM GABUNGAN BURSA EFEK INDONESIA." Media Ekonomi 22, no. 2 (2014): 133. http://dx.doi.org/10.25105/me.v22i2.3171.

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<p>The objective of this research is to examine the effect of global stock indices and marco economic condition of Indonesia to Jakarta Stock Exchange Composite Index (JCI). The global stock indices that had been analyzed in this research are Dow Jones Industrial Average (DJIA), Nikkei 225 (N225), Shanghai Stock Exchange Composite (SSE), Financial Times Stock Exchange 100 (FTSE 100), and Hang Seng Index (HSI). The macro economic indicator that had been analyzed in this research are exchange rate United States dollar to Indonesian rupiah, inflation and BI rate. This research was conducted

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Ulu, Yasemin. "Volatility Distribution of the DJSTOXXE50 Index." Applied Economics and Finance 7, no. 6 (2020): 101. http://dx.doi.org/10.11114/aef.v7i6.5065.

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In this paper using data from 1995-2005 on 5-minute intraday returns, we construct a model free estimate of the daily realized volatility for the DJSTOXXE50 index. We compute the unconditional volatility distribution of the DJSTOXXE50 index by a nonparametric kernel estimation method. Our results indicate that the unconditional volatility distribution of the DJSTOXXE50 returns are leptokurtic and highly skewed to the right. The logarithmic standard deviations seem to be approximately Gaussian. Our results are inline with previous research for individual DJIA equity return volatility and for Ja

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Tetik, Metin, and Ercan Ozen. "Overreaction Hypothesis and Reaction of Borsa Istanbul to Dow-Jones." Business and Economic Research 6, no. 2 (2016): 412. http://dx.doi.org/10.5296/ber.v6i2.10353.

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The aim of this study is to investigate whether or not there are any over-reactions to the positive and negative events of the Borsa Istanbul 100 index (BIST-100) in relation to the Dow Jones Industrial index (DJIA). The daily stock indexes between January 2010 and June 2016 are used in this research. The research finding showed that BIST-100 reacts in the same way as DJIA up to 3.31% and the reaction decreases and was lost between 30 and 60 days against the positive changes. In case of adverse events the BIST 100 shows abnormal decline in protecting the efficient market hypothesis is valid fo

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Khan, Khalid Mumtaz, Waiza Rehman, and Osman Bin Saif. "Predicting key reversal points through Fibonacci retracements." Journal of Management Info 9, no. 3 (2022): 299–310. http://dx.doi.org/10.31580/jmi.v9i3.2638.

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Anticipation of the key reversal points in trading markets is of key interest to the portfolio managers, investors, researchers, technical Analysts. These points trigger investment or divestment for investors’ holdings within the financial markets. Many techniques are used to anticipate these points. Use of Fibonacci numbers has gained significant importance in this context. The tools like ‘Fibonacci Retracements’ are available to investors; however, another important determinant in the value of an investment is the ‘timings’ within a certain time frame. This study aims to understand whether s

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Andriyana, Yudhie, Yollanda Nalita, Bertho Tantular, I. Gede Nyoman Mindra Jaya, and Annisa Nur Falah. "Global gold prices forecasting using Bayesian nonparametric quantile generalized additive model." International Journal of Data and Network Science 7, no. 3 (2023): 1033–44. http://dx.doi.org/10.5267/j.ijdns.2023.6.002.

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Gold is one of the most attractive commodities and popular investments. Investment experts often recommend investing in gold because gold is one of the safest investments. It is a stable classic hedge, although the conditions of currency volatility or global markets are depreciated. However, the gold price fluctuations can be influenced by some other factors, such as the USD Index, which reflect and measure the strength of the US Dollar currency, and the Index of Dow Jones Industrial Average (DJIA) or a reflection of the political and economic conditions of the stock market. In this study, we

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Batool, Komal, Ubaida Fatima, and Mirza Faizan Ahmed. "Trend Prediction of DJIA index based on News Extraction from Yahoo Finance." International Journal of Computer Applications 186, no. 64 (2025): 42–46. https://doi.org/10.5120/ijca2025924379.

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Tse, Yiuman. "Price discovery and volatility spillovers in the DJIA index and futures markets." Journal of Futures Markets 19, no. 8 (1999): 911–30. http://dx.doi.org/10.1002/(sici)1096-9934(199912)19:8<911::aid-fut4>3.0.co;2-q.

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Emmert-Streib, Frank, and Matthias Dehmer. "Identifying critical financial networks of the DJIA: Toward a network-based index." Complexity 16, no. 1 (2010): 24–33. http://dx.doi.org/10.1002/cplx.20315.

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