A Comparative Study on the Behavior of Islamic and Conventional Stocks in the Presence of Oil Price, Gold Price, and Financial Risk Factors: Evidence from Dow Jones Indices

2019 ◽  
Vol 2 (2) ◽  
pp. 117-128
Author(s):  
Danish Iqbal Godil ◽  
Salman Sarwat ◽  
Muhammad Umer Quddoos ◽  
Muhammad Hanif Akhtar
Keyword(s):  
Time Series ◽  
Financial Risk ◽  
Time Series Data ◽  
Oil Prices ◽  
Gold Price ◽  
Oil Price ◽  
Series Data ◽  
Volatility Index ◽  
West Texas

The research aims to analyze the influence of the gold price, oil price and financial risk on Islamic and conventional securities on comparative as well as on individual bases. Monthly prices of oil and gold are extracted from the websites of West Texas Intermediate and World Gold Council, whereas time series data for financial risk is derived from the Volatility Index of S&P 500.  All these variables are found to be cointegrated at the first difference with both the Dow Jones indices, which means that gold, oil and financial risk have long term association with Islamic and conventional stocks. In order to find the direction and magnitude, this study applied the Newey-West HAC test, which also handles autocorrelation and heteroscedasticity issues in the time series data. The findings of the study suggest that gold prices are positively associated whereas oil prices and financial risk are negatively associated with both types of securities. Though the direction of the nexus is similar for Islamic and conventional stocks, but the magnitude differs especially in case of oil and financial risk. Nevertheless, it can be concluded that there is no diversification prospect between conventional and Islamic stocks under the influence of oil prices, financial risk, and gold prices.

Asymmetric impact of oil price shocks on selected macroeconomic variables: NARDL exposition

2020 ◽  
pp. 171-189
Author(s):  
Omoke Philip Chimobi ◽  
Uche Emmanuel
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Oil Prices ◽  
Oil Price ◽  
Series Data ◽  
Oil Price Shocks ◽  
Price Shocks ◽  
Macroeconomic Variables ◽  
Asymmetric Effects ◽  
Asymmetric Impact

The preoccupation of this study is to give empirical explanations to the existing relationship between oil price dynamics and some selected macroeconomic variables in Nigeria. Specifical-ly, it seeks to identify if the impacts of the changing oil prices on output, investment and un-employment is symmetric or asymmetric. Monthly time series data used in the research was subjected to a nonlinear analysis through the newly developed NARDL. To that effect, our findings reveal that changes in oil prices has asymmetric effects on the chosen macroeconomic variables. Our findings call for different policy formulations for up and down swings in oil prices

scholarly journals The Relations of Oil Price Change with Fear Gauges in Global Political and Economic Environment

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2982 ◽  
Author(s):  
Jeng-Bau Lin ◽  
Wei Tsai
Keyword(s):  
Structural Breaks ◽  
Structural Changes ◽  
Time Series Data ◽  
Price Change ◽  
Sampling Period ◽  
Oil Price ◽  
Series Data ◽  
Stock Market Volatility ◽  
Volatility Index

The oil price time series data can be affected by major global political and economic events, which would result in structural changes that could lead to biased estimations. By adopting the Bai and Perron model this paper found that there were six structural breaks in the Brent oil price due to major global events and that ARDL-ECM cointegration exists only between oil price and stock market volatility index (VIX) throughout the sampling period. However, cointegration relations were found between oil price and Crude Oil Volatility Index (OVX) in the second and fourth sub-periods, and also between oil price and VIX in the second, third, fourth, sixth, and seventh sub-periods. Furthermore, the cointegration relation coupled with correlation analysis indicates a long-term equilibrium positive (negative) relation between the two variables. Such relations existed between the price and the two fear gauges, respectively, only for some specific sub-periods, implying that OVX seemed to be better than VIX in predicting oil price changes. We suggest that the investors in the global oil market must pay attention to not only the impacts of major global political and economic events on oil price, but also the positive or negative correlations between oil price and fear gauge.

Impact of exchange rate and oil price on the yield of sovereign bond and sukuk: Evidence from Malaysian capital market

2017 ◽  
Vol 5 (4) ◽  
pp. 27
Author(s):  
Huda Arshad ◽  
Ruhaini Muda ◽  
Ismah Osman
Keyword(s):  
Exchange Rate ◽  
Capital Market ◽  
Time Series Data ◽  
Oil Prices ◽  
Oil Price ◽  
Series Data ◽  
Sovereign Bond ◽  
Long Run ◽  
Short Run ◽  
The Impact

This study analyses the impact of exchange rate and oil prices on the yield of sovereign bond and sukuk for Malaysian capital market. This study aims to ascertain the effect of weakening Malaysian Ringgit and declining of crude oil price on the fixed income investors in the emerging capital market. This study utilises daily time series data of Malaysian exchange rate, oil price and the yield of Malaysian sovereign bond and sukuk from year 2006 until 2015. The findings show that the weakening of exchange rate and oil prices contribute different impacts in the short and long run. In the short run, the exchange rate and oil prices does not have a direct relation with the yield of sovereign bond and sukuk. However, in the long run, the result reveals that there is a significant relationship between exchange rate and oil prices on the yield of sovereign bond and sukuk. It is evident that only a unidirectional causality relation is present between exchange rate and oil price towards selected yield of Malaysian sovereign bond and sukuk. This study provides numerical and empirical insights on issues relating to capital market that supports public authorities and private institutions on their decision and policymaking process.

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

Welfare Use in Japan: Trends and Determinants

2007 ◽  
pp. 88
Author(s):  
Wataru Suzuki ◽  
Yanfei Zhou
Keyword(s):  
Time Series ◽  
Longitudinal Data ◽  
Time Series Data ◽  
Positive Impact ◽  
Series Data ◽  
Negative Effects ◽  
Long Time ◽  
Welfare Use ◽  
The Impact

This article represents the first step in filling a large gap in knowledge concerning why Public Assistance (PA) use recently rose so fast in Japan. Specifically, we try to address this problem not only by performing a Blanchard and Quah decomposition on long-term monthly time series data (1960:04-2006:10), but also by estimating prefecturelevel longitudinal data. Two interesting findings emerge from the time series analysis. The first is that permanent shock imposes a continuously positive impact on the PA rate and is the main driving factor behind the recent increase in welfare use. The second finding is that the impact of temporary shock will last for a long time. The rate of the use of welfare is quite rigid because even if the PA rate rises due to temporary shocks, it takes about 8 or 9 years for it to regain its normal level. On the other hand, estimations of prefecture-level longitudinal data indicate that the Financial Capability Index (FCI) of the local government2 and minimum wage both impose negative effects on the PA rate. We also find that the rapid aging of Japan's population presents a permanent shock in practice, which makes it the most prominent contribution to surging welfare use.

Prediction and Analysis of Gold Prices using Ensemble Machine Learning Algorithms

2021 ◽  
Vol 9 (VI) ◽  
pp. 4367-4374
Author(s):  
Gudipally Chandrashakar
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Time Series Data ◽  
Gold Price ◽  
Machine Learning Algorithms ◽  
Series Data ◽  
Gradient Boosting ◽  
Support Vector ◽  
Average Value ◽  
Ensemble Machine Learning

In this article, we used historical time series data up to the current day gold price. In this study of predicting gold price, we consider few correlating factors like silver price, copper price, standard, and poor’s 500 value, dollar-rupee exchange rate, Dow Jones Industrial Average Value. Considering the prices of every correlating factor and gold price data where dates ranging from 2008 January to 2021 February. Few algorithms of machine learning are used to analyze the time-series data are Random Forest Regression, Support Vector Regressor, Linear Regressor, ExtraTrees Regressor and Gradient boosting Regression. While seeing the results the Extra Tree Regressor algorithm gives the predicted value of gold prices more accurately.

scholarly journals The Effect of Inflation, US Dollar Exchange Rates, Interest Rates, and World Oil Prices on Gold Price Fluctuations in Indonesia 2014 – 2019

2020 ◽  
Vol 1 (3) ◽  
pp. 155-171
Author(s):  
Ummi Kalsum ◽  
Randy Hidayat ◽  
Sheila Oktaviani
Keyword(s):  
Exchange Rates ◽  
Interest Rates ◽  
Time Series Data ◽  
Multiple Linear Regression Model ◽  
Oil Prices ◽  
Gold Price ◽  
Series Data ◽  
Price Fluctuations ◽  
Insignificant Effect ◽  
Us Dollar

This study aims to determine the effect of inflation, US dollar exchange rates, interest rates, and world oil prices on fluctuations in gold prices in Indonesia in 2014 - 2019. This research is a type of explanatory research with a quantitative approach. The data used are monthly time series data for 2014 - 2019 with a sample of 72 samples. The multiple linear regression model is used as an analysis technique in this study. The results of this study indicate that simultaneously (F test) inflation, USD exchange rates, interest rates, and world oil prices have a significant effect on gold price fluctuations in Indonesia. Partially (t-test) shows that the USD exchange rate has a significant positive effect on gold price fluctuations in Indonesia. Inflation and interest rates have a negative and insignificant effect on fluctuations in gold prices in Indonesia. Meanwhile, world oil prices have a positive and insignificant effect on gold price fluctuations in Indonesia.

scholarly journals Minimum time required to detect population trends: the need for long-term monitoring programs

2017 ◽  
Author(s):  
Easton R White
Keyword(s):  
Time Series ◽  
Statistical Power ◽  
Time Series Data ◽  
Conservation Status ◽  
Monitoring Program ◽  
Minimum Time ◽  
Series Data ◽  
Series Length ◽  
Time Required

Long-term time series are necessary to better understand population dynamics, assess species' conservation status, and make management decisions. However, population data are often expensive, requiring a lot of time and resources. When is a population time series long enough to address a question of interest? We determine the minimum time series length required to detect significant increases or decreases in population abundance. To address this question, we use simulation methods and examine 878 populations of vertebrate species. Here we show that 15-20 years of continuous monitoring are required in order to achieve a high level of statistical power. For both simulations and the time series data, the minimum time required depends on trend strength, population variability, and temporal autocorrelation. These results point to the importance of sampling populations over long periods of time. We argue that statistical power needs to be considered in monitoring program design and evaluation. Time series less than 15-20 years are likely underpowered and potentially misleading.

scholarly journals PENGARUH ZIS (ZAKAT, INFAK, SEDEKAH) DAN ZAKAT FITRAH TERHADAP PENURUNAN KEMISKINAN DI INDONESIA PERIODE 1998 - 2010

Media Ekonomi ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 83
Author(s):  
Jumadin Lapopo
Keyword(s):  
Time Series ◽  
Developing Countries ◽  
Regression Analysis ◽  
Poverty Reduction ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Analysis Model ◽  
Independent Variables

<p>Poverty is being a problem in all developing countries including Indonesia. Among goverment programs, poverty has become the center offattention in policy at both of the regional and national levels. Looking at thephenomenon of poverty, Islam present with solution to reduce poverty through Zakat. This study aims to analyze the effect of ZIS and Zakat Fitrah against poverty in Indonesia in 1998 until 2010, data used in this study is secondary data and uses time series data, for the dependent variabel is poverty and for independent variables are ZIS and Zakat Fitrah. The analysis tools used in this study is to use multiple regression analysis model and the assumptions of classical test using the software Eviews-4. In this study also concluded that the ZIS variables significantly affect to the reduction of poverty in Indonesia although the effect is very small. In the variable Zakat Fitrah not significantly affect poverty reduction in Indonesia because of the nature of Zakat Fitrah is for consumption and not for long-term needs. The results of this study can be used for the management of zakat to be able to develop the management and to get a better system for distribution of zakat so that the main purpose of zakat can be achieved to reduce poverty.<br />Keywords : Poverty, Zakat Fitrah, ZIS.</p>

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