Dow Jones Research Articles

Impact of Macroeconomic Variables on the Performance of the Indian stock market

This paper analyses the macroeconomic factors influencing performance of Indian stock market index NIFTY 50. The study is unique in nature as it employ both, primary and secondary to derive the conclusion. Initially, nine years monthly data of macroeconomic variables are regressed against monthly performance of NIFTY 50 index using logistic regression. In second stage the outcome of regression analysis is ratified with primary data collected through face to face interview of the stock market expert. The secondary data analysis confirm Dow jones index and exchange rate movement are the main determinants of NIFTY 50 index. However, expert opined that other factors like political stability, economic situation in developed and bilateral relations of India with other countries are also important to forecast the NIFTY 50 index movement. This is the first study in Indian context, to combine domestic and international factors to forecast NIFTY 50 index movement.

Dynamic Interdependence: Analysing BSE SENSEX and its Relationship with Global Stock Indices from 2018 to 2022

This comprehensive analysis delves into the intricate relationship between the Bombay Stock Exchange SENSEX (BSE SENSEX), India's leading stock market index, and popular international stock indices during three distinct research periods from 2018 to 2022. The study employs a combination of correlation analyses and multiple regression models to explore how SENSEX interacts with global counterparts, shedding light on the evolving dynamics of the Indian stock market. The five-year research period from 2018 to 2022 reveals that SENSEX displays a robust positive correlation with various international indices, including Nikkei 225, DAX, CAC40, S&P500, NASDAQ100, and DOW JONES. This suggests a substantial degree of co-movement with global markets, emphasizing the influence of external economic and financial factors on India's stock market. A multiple regression analysis further substantiates these relationships by indicating that international indices collectively have a significant impact on SENSEX's variations during this period.

Pengaruh Indeks Dow Jones, Suku Bunga The Fed, Dan Bitcoin terhadap IHSG

This research was conducted to examine the effect of the Dow Jones Index, The Fed Interest Rate, and Bitcoin on the Indonesian Composite Stock Price Index (IHSG). The data used is secondary data taken based on closing prices and monthly fluctuations from financial websites. The population is in the form of time series data for 58 months starting from 1 June 2018 to 31 March 2023 using a saturated sample. Data analysis in the study used the classical assumption test (multicollinearity, heteroscedasticity, autocorrelation, normality), multiple linear regression, determinant coefficient, and T test. The results showed that the Dow jones index had a positive effect on the JCI, The Fed's interest rate had a positive effect on the JCI, and Bitcoin has no effect on the JCI. The test results stated that the Dow Jones Index had a positive influence on the JCI, The Fed's Interest Rate had a positive influence on the JCI, and Bitcoin had no influence on the JCI.
 Keywords: Bitcoins; Dow Jones; IHSG; The Fed

The impact of containment measures and monetary and fiscal responses on US financial markets during the COVID-19 pandemic

This paper analyses the effects of containment measures and monetary and fiscal responses on US financial markets during the Covid-19 pandemic. More specifically, it applies fractional integration methods to analyse their impact on the daily S&P500, the US Treasury Bond Index (USTB), the S&P Green Bond Index (GREEN) and the Dow Jones (DJ) Islamic World Market Index (ISLAM) over the period 1/01/2020–10/03/2021. The results suggest that all four indices are highly persistent and exhibit orders of integration close to 1. A small degree of mean reversion is observed only for the S&P500 under the assumption of white noise errors and USTB with autocorrelated errors; therefore, market efficiency appears to hold in most cases. The mortality rate, surprisingly, seems to have affected stock and bond prices positively with autocorrelated errors. As for the policy responses, both the containment and fiscal measures had a rather limited impact, whilst there were significant announcement effects which lifted markets, especially in the case of monetary announcements. There is also evidence of a significant, positive response to changes in the effective Federal funds rate, which suggests that the financial industry, mainly benefiting from interest rises, plays a dominant role.

The return volatility and shock transmission patterns of chosen S&P and Dow Jones sustainability indices and their conventional counterpart

PurposeThe purpose of this study is to investigate the dynamic return volatility connectedness among S&P, Dow Jones (DJ) sustainability indices and their conventional counterparts.Design/methodology/approachThis study uses time-series daily data for 10 S&P and DJ indices over the period of December 1, 2012 to December 8, 2021. The authors divide the data into three periods; over the whole sample, pre and during the Covid-19 pandemic. The study adopts the connectedness approach developed by Diebold and Yilmaz (2014).FindingsThe results reveal a high degree of connectedness between S&P and DJ indices and their relative sustainability indices over the whole sample, pre and during the Covid-19 pandemic, indicating that the sustainability indices converge toward their conventional peers. The results further show that the conventional S&P500, S&P Euro 50 and DJWI are the main transmitters of shocks, whereas the S&P400, S&P500 and S&P50 sustainability indices are the main receivers of shocks.Originality/valueThe study provides novel insights in terms of shock transmission of S&P and DJ sustainability indices and their conventional counterparts, where there is a lack of investigation of the connectedness between indices in this field.Practical implicationsThe study has significant implications for investors and portfolio managers to devise portfolio strategies to minimize risk and trace the cause, the direction and the magnitude of risk transmission among different indices. Also, the results help policymakers to manage diverse types of risks associated with S&P and DJ indices. Finally, faith-based and ethical investors would be able to predict the pairwise spillover connectedness between these indices.

Random walks and market efficiency tests: evidence on US, Chinese and European capital markets within the context of the global Covid-19 pandemic

Research background: Covid-19 has affected the global economy and has had an inevitable impact on capital markets. In the week of February 24?28, 2020, stock markets crashed. The index FTSE 100 decreased 13%, while the indices DJIA and S&P 500 fell 11?12%, the biggest drop since the 2007?2008 financial and economic crisis. It is therefore of interest to test the random walk hypothesis in developed capital markets, European and also non-European, in order to understand the different predictabilities between them.
 Purpose of the article: The aim is to analyze capital market efficiency, in its weak form, through the stock market indices of Belgium (index BEL 20), France (index CAC 40), Germany (index DAX 30), USA (index DOW JONES), Greece (index FTSE Athex 20), Spain (index IBEX 35), Ireland (index ISEQ), Portugal (index PSI 20) and China (index SSE) for the period from December 2019 to May 2020.
 Methods: Panel unit root tests of Breitung (2000), Levin et al. (2002) and Hadri (2002) were used to assess the time series stationarity. The test of Clemente et al. (1998) is used to detect structural breaks. The tests for the random walk hypothesis follows the variance ratio methodology proposed by Lo and MacKinlay (1988).
 Findings & Value added: In general, we found mixed confirmation about the EMH (efficient market hypothesis). Taking into account the conclusions of the rank variance test, the random walk hypothesis was rejected in the case of stock indices: Dow Jones, SSE and PSI 20, partially rejected in the case indices: BEL 20, CAC 40, FTSTE Athex 20 and DEX 30, but accepted for indices: IBEX 35 and ISEQ. The results also show that prices do not fully reflect the information available and that changes in prices are not independent and identically distributed. This situation has consequences for investors, since some returns can be expected, creating opportunities for arbitrage and for abnormal returns, contrary to the assumptions of random walk and information efficiency.

Analysis of the effect on inflation, interest rate, dow jones Islamic Malaysia Index and profitability on stock prices as selected as Indonesia Sharia Stock Index

Purpose - The purpose of this study was to analyze what influences the change in the ISSI price index. The analysis was based on the phenomena and hypotheses that occur in the capital market by examining whether there is an influence of inflation rates, interest rates, and the Dow Jones Islamic Malaysia Index as external factors, as well as profitability such as Return on Assets and Earning per Share as internal factors that have an influence on changes and fluctuations in the Sharia Stock Index.Method - The population in this study are all stocks that are encoded in the Indonesia Sharia Stock Index (ISSI) listed on the Indonesia Stock Exchange. Based on the Sharia Stock Exchange and the number of shares indexed by ISSI was 408 shares which shares were classified into 11 types of business. The study was conducted by analyzing multiple regression with t-test, significance test, F test, and classical assumption test.Result - Based on the research results of bank interest rates and the Dow Jones Islamic Malaysia Index which affect stock prices indexed as Indonesia Sharia Stock, the two variables are the external influence of the issuers of the shares. And the majority of these stock prices are strongly influenced by variable factors not examined.Implication - This research indicates that the factors that influence stock prices indexed as Islamic stocks in Indonesia, the analysis of the coefficient of determination is not significant at 0.6%, to find out other factors, other variables are needed for further research.Originality - This research is a continuation of previous research but uses different variables from previous researches, where the dependent variable is stock prices indexed as Indonesian Islamic stocks and the independent variable is the inflation rate, interest rate, and the Malaysian Islamic Dow Jones Index as factors.

Forecasting Islamic equity indices alpha

PurposeThis paper aims to investigate whether Islamic and conventional equity indices offer some alpha. These indices are expected to offer no alpha being value-weighted, passive and unmanaged.Design/methodology/approachThis paper used monthly data from 1996 to 2016 of four Dow Jones (DJ) and one financial times stock exchange (FTSE) Islamic equity indices and five conventional Morgan Stanley Capital International (MSCI) equity indices. This study used a simple ordinary least square (OLS) rolling window regressions to generate the alphas and risk loadings when adjusting for prominent pricing factor models.FindingsThe findings from OLS regressions suggest that DJ Islamic indices of Japan, Europe and World generate significant alphas, whereas, MSCI conventional indices of Asia/Pacific, USA and World generate significant alpha when risk-adjusted for pricing factor models. However, in 36-month rolling window regressions, all Islamic indices generate significant alpha and factor loading. The magnitude of alpha and factor loading changes over time.Research limitations/implicationsThe finding shows that the Shari’ah-compliant investment fund’s alpha must be adjusted with the respective benchmark index alpha to measure the fund manager’s skill performance quantitatively.Originality/valueTo the best of the author’s knowledge, this is the first study that investigates and compares the Islamic, as well as conventional indices for abnormal returns, which are adjusted for both Fama–French five and q-theory-based four assets pricing risk factors and as a benchmark for Shari’ah-compliant fund’s performance.

Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?

The paper examines the relative performance of Stochastic Volatility (SV) and GARCH(1,1) models fitted to twenty plus years of daily data for three indices. As a benchmark, I use the realized volatility (RV) for the S&P 500, DOW JONES and STOXX50 indices, sampled at 5-minute intervals, taken from the Oxford Man Realised Library. Both models demonstrate comparable performance and are correlated to a similar extent with the RV estimates, when measured by OLS. However, a crude variant of Corsi’s (2009) Heterogenous Auto-Regressive (HAR) model, applied to squared demeaned daily returns on the indices, appears to predict the daily RV of the series, better than either of the two base models. The base SV model was then enhanced by adding a regression matrix including the first and second moments of the demeaned return series. Similarly, the GARCH(1,1) model was augmented by adding a vector of demeaned squared returns to the mean equation. The augmented SV model showed a marginal improvement in explanatory power. This leads to the question of whether we need either of the two standard volatility models, if the simple expedient of using lagged squared demeaned daily returns provides a better RV predictor, at least in the context of the indices in the sample. The paper thus explores whether simple rules of thumb match the volatility forecasting capabilities of more sophisticated models.

A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index

The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag nonlinear autoregressive distributed lag (NARDL) framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from Federal Reserve Bank of St Louis (FRED), commencing in January 2000 and terminating in February 2019, and a corresponding monthly DOW JONES index adjusted-price series obtained from Yahoo Finance. Both series are adjusted for monthly USA CPI values to create real series. The results of the analysis suggest that movements in the lagged real levels of monthly WTI crude oil prices have very significant effects on the behaviour of the DOW JONES Index. They also suggest that negative movements have larger impacts than positive movements in WTI prices, and that long-term multiplier effects take about 9 to 12 months to take effect.

Pengaruh Perubahan Nilai Tukar Rupiah, Tingkat Inflasi, dan Indeks Bursa Internasional Terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia (BEI)

This research aimed to know how the effect of Rupiah Exchange Rate, inflation rate, and international Exchange Index towards Composite Stock Price Index (CSPI). The independent variables of this study are Rupiah Exchange Rate (X1), Inflation rate (X2), Dow Jones index (X3), Nikkei 225 index (X4), and Hang Seng index (X5). The Sample was based on monthly time series data from January 2014 to December 2018, with documentation data collection technique from Bank Indonesia and Yahoofinance.com publication. Analytical techniques used were linier regression, classical Assumtions, determination coeffisient test (R2), for hypothesis test used F-test and t-test with significance level of 5%. The results of this indicate that the value of cooficient of determination (R2) 0,901 which means independent variables affect the dependent variable 89,2% and the rest is 10,8% influenced by other variables outside this study. The result of t-test shows that the Rupiah Exchange Rate and Nikkei 225 index have not significant and negative effect on Composite Stock Price Index (CSPI), Inflation rate have significant and negative effect on Composite Stock Price Index (CSPI), Dow Jones index and Hang Seng Index have significant and positive effect on Composite Stock Price Index (CSPI). Keywords: composite stock price index (cspi), rupiah exchange rate, inflation rate, dow jones index, nikkei 225 index, and hang seng index

When is a MAX not the MAX? How news resolves information uncertainty

A well-known asset pricing anomaly, the “MAX” effect, measured by the maximum daily return in the past month, depicts stocks’ lottery-like features and investor gambling behaviour. Using the comprehensive stock-level Dow Jones (DJNS) news database between 1979 and 2016, we consider in a empirical setting how the presence of news reports affects these lottery-type stocks. We find an augmented negative relationship between MAX stocks without news and expected returns, whereby MAX with news coverage generates return momentum. The differing future return relationships between MAX stocks with and without news appears to be best explained by information uncertainty mitigation upon news arrival. Overall, our findings suggest that news plays a role in resolving information uncertainty in the stock market.

PENGARUH VARIABEL MAKROEKONOMI DAN INDEKS SAHAM INTERNASIONAL TERHADAP INDEKS SAHAM JAKARTA ISLAMIC INDEX (JII)

This study investigate the effect of macroeconomic variables and international stock index on the stock index Jakarta Islamic Index (JII) using monthly data over period January 2013 to December, 2018. Macroeconomic variables used in this study are inflation, exchange rate, international crude oil price, World Gold Price and for the international stock index using Dow Jones Islamic Market. The study employs the eror correction model (ECM). The empirical result reveal that there is co-integration between the four macroeconomic variables, one international stock index and stock index in Jakarta Islamic Index indicating long run equilibirium relationship. Furhther, the result reveal that with significancy 0,5% only exchange rate, international crude oil price, world gold price had significant effect on Jakarta Islamic Index while inflation and Dow jones Islamic Market did not have a significant effect on Jakarta Islamic Index.Keywords: The stock Index, the Jakarta Islamic Index, the macroeconomic variables

The asymmetric effects of oil price on sectoral Islamic stocks: New evidence from quantile-on-quantile regression approach

This study extends the existing literature by examining the impact of oil prices on the Dow Jones (DJ) Islamic index and sectoral stock indices. In particular, enhanced empirical estimations are used to provide an in-depth understanding of the sensitivity of stock indices towards oil price fluctuation. Quantile unit root test and quantile cointegration tests are used to examine the integrating properties of the underlying variables. Moreover, we use Quantile-on-Quantile (QQ) approach to examine the impact across diverse quantiles of explanatory and outcome variables. Findings of the QQ estimate indicates that lower (upper) quantiles of oil prices negatively affect the upper (lower) quantiles of the DJ Islamic index. In addition, either upper or lower quantiles of both markets indicate a positive relationship. The findings for financial sector, healthcare sector, consumer goods, consumer services, oil & gas sector, utility sector, and industrial sector are consistent with the findings of DJ Islamic index. Finally, for basic material, technology and telecommunication sectors, a positive relationship is found across different quantiles. This study provides policy implications based on the findings of these enhanced methodologies.

Volatility Modelling and Dynamic Linkages between Pakistani and Leading Foreign Stock Markets: A Multivariate GARCH Analysis

It is essential for financial institutions and academicians to understand volatility spillover and financial market returns. However, previous studies examined the effects of direct spillover only and ignored those of the newly emerging stock markets. Therefore, this study attempts to estimate the time-varying volatility of Pakistani and leading foreign stock markets. It also tries to explore the direct and indirect volatility spillover effect between Pakistani and eight leading foreign stock markets. Daily data were used from nine international equity markets (KSE 100, NIKKEI 225, HIS, S&P 500, NASDAQ 100, DOW JONES, GADXI, FTSE 350 and DFMGI) for the period between 2005 and 2016. The univariate GARCH and GJR models were employed for analysing volatility, and the multivariate GARCH Diagonal BEKK model was used to explore direct and indirect volatility spillover effects. In order to analyse the volatility spillover effect during and after the global financial crisis period, the data were categorised into two periods: between 2005 and 2009 and between 2010 and 2016. The Chow break-point test was also employed to identify structural breaks in return series due to global financial crises. Direct and indirect spillover effects were found between KSE100, S&P 500, NASDAQ 100, DOW JONES and DFMGI. Keywords: Volatility, Spillover, Equity Market, Financial Crisis and GARCH

When Is a Max Not the Max? How News Resolves Information Uncertainty

A well-known asset pricing anomaly, the effect, measured by the maximum daily return in the past month, depicts stocks' lottery-like features and investor gambling behaviour. Using the comprehensive stock-level Dow Jones (DJNS) news database between 1979 and 2016, we consider in a empirical setting how the presence of news reports affects these lottery-type stocks. We find an augmented negative relationship between MAX stocks without news and expected returns, whereby MAX with news coverage generates return momentum. The differing future return relationships between MAX stocks with and without news appears to be best explained by information uncertainty mitigation upon news arrival. Overall, our findings suggest that news plays a role in resolving information uncertainty in the stock market.

A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index

The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from FRED, commencing in January 2000 and terminating in February 2019, and a corresponding monthly DOW JONES index adjusted-price series obtained from Yahoo Finance. Both series are adjusted for monthly USA CPI values to create real series. The results of the analysis suggest that movements in the lagged real levels of monthly WTI crude oil prices have very significant effects on the behaviour of the DOW JONES Index. They also suggest that negative movements have larger impacts than positive movements in WTI prices, and that long-term multiplier effects take about 9 to 12 months to take effect.

PENGARUH LAJU PERTUMBUHAN INFLASI, HARGA MINYAK DUNIA DAN DOW JONES INDUSTRIAL AVERAGE TERHADAP INDEKS HARGA SAHAM GABUNGAN YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2007-2011

This research attempts to influence the inflation growth, the oil price dow jones industrial average to Composite Stock Price Index which is registred in indonesian stock exchange in the period of 2007-2011. The population in this research was the whole index in indonesian stock exchange (ISE). The sample was taken based on sampling purpodive. The data analysis technique used double linier regression. The dependent variable in this research was the growth of Composite Stock Price Index, while the independent variable was the inflation growth, the oil price and dow jones industrial average. The results of this research showed that the almost dependent variable used had effects for the growth of Composite Stock Price Index. The inflation rate growth variable did not have effects on Composite Stock Price Index growth, while the oil price rate variable and dow jones industrial average had effects on Composite Stock Price Index growth. Simultaneously, the independent variables examinedhere had effects on Composite Stock Price Index growth.

A hybrid financial trading support system using multi-category classifiers and random forest

This study presents a decision support system for algorithmic trading in the financial market that uses a new hybrid approach for making automatic trading decision. The hybrid approach integrates weighted multicategory generalized eigenvalue support vector machine (WMGEPSVM) and random forest (RF) algorithms (named RF-WMGEPSVM) to generate “Buy/Hold/Sell” signals. The WMGEPSVM technique has an advantage of handling the unbalanced data set effectively. The input variables are generated from a number of technical indicators and oscillators that are widely used in industry by professional financial experts. Selection of relevant input variables can enhance the predictive capability of the prediction algorithms. RF technique is employed to discover the optimal feature subset from a large set of technical indicators. The proposed hybrid system is tested using “walk forward” approach for its capability of taking an automatic trading decision on daily data of five index futures, viz., NASDAQ, DOW JONES, S&P 500, NIFTY 50 and NIFTY BANK. RF-WMGEPSVM achieves the notable improvement over the buy/hold strategy and other predictive models contemplated in this study. It is also observed that combining WMGEPSVM with RF further improves the results. Empirical results confirm the effectiveness of RF-WMGEPSVM in the real market scenarios having bullish, bearish or flat trend.

Tracing dynamic linkages and spillover effect between Pakistani and leading foreign stock markets

This study traces the degree of integration and volatility spillover effect between the Pakistani and leading foreign stock markets by analyzing the Meteor shower hypothesis. Daily data are used from nine worldly equity markets (KSE 100, NIKKEI 225, HIS, S&P 500, NASDAQ 100, DOW JONES, GADXI, FTSE 350 and DFMGI) for the period of 2005 to 2014. First, we used the whole data set and after that we split data set into two subsets, First subset of data contains the era of global financial crisis of 2008 from 2005 to 2009 and Second subset is after global financial crisis time period from 2010 to 2014 (The global crisis prevailed till end of 2009). By following the Hamao et al. (1990) technique the univariate GARCH type models are employed to explore the dynamic linkages between Pakistani and leading foreign stock markets. The results from whole data set illustrate that there is mixed co-movements between leading foreign stock markets and Pakistani stock market. The results from both subsets provide an evidence that there is a unidirectional mean and volatility spillover effect from S&P 500, NASDAQ 100, DJI and DFMGI to KSE 100. Also we found bidirectional spillover effect between DFMGI and KSE 100 from both subsets of data. We concluded that there is only one indirect linkage through which may the information transmitted to KSE 100. This linkage is developed due to the co-movement among KSE 100, DFMGI and NASDAQ 100 in crisis period. This integration between these markets may provide a sign of indirect linkage. It also exhibits the volatility in Pakistan stock market returns is instigated through direct effects as well as indirect effects. Our study brings important conclusions for financial institutions, portfolio managers, market players and academician to diagnose the nature and level of linkages between the financial markets.