scholarly journals Pengaruh Sistem Perbankan, Makroekonomi, Dinamika Pasar Keuangan terhadap Perkembangan Sukuk Korporasi

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Alyta Shabrina Zusryn ◽  
Rizqi Umar Al Hashfi ◽  
Ananta Hagabean Nasution
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Crude Oil ◽  
Oil Price ◽  
Crude Oil Price ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Interest Rate Spread

Tujuan pada penelitian ini adalah untuk mengetahui faktor-faktor yang berpengaruh terhadap perkembangan sukuk korporasi di Indonesia. Data yang digunakan adalah data bulanan tahun 2013-2016 variabel makroekonomi, crude oil price, kredit perbankan konvensional, interest rate spread, aset perbankan syariah, outstanding obligasi korporasi indonesia, nilai kapitalisasi pasar saham syariah, dan standar deviasi Jakarta Interbank Offered Rate (JIBOR). Pada penelitian ini menggunakan analisis data time series yaitu Autoregressive Distributed Lag (ARDL) yang merupakan pengembangan dan melengkapi kelemahan dari analisis Vector Autoregresive (VAR). Penelitian ini menunjukkan bahwa terdapat pengaruh positif harga minyak mentah dunia, perkembangan obligasi korporasi, dan aset perbankan syariah terhadap perkembangan sukuk korporasi. Selain itu, kapitalisasi pasar saham syariah, interest rate spread, dan volatilitas suku bunga pasar berdampak negatif terhadap perkembangan sukuk korporasi. Hasil tersebut menunjukkan adanya peningkatan permintaan dan penawaran pada sukuk korporasi di Indonesia. Penelitian ini menemukan adanya hubungan komplementer pada obligasi korporasi dan perbankan syariah pada perkembangan sukuk korporasi sehingga diharapkan adanya sinergi dan koordinasi para pemangku kepentingan yaitu pemerintah, pelaku industri, perusahaan dan pihak-pihak terkait

scholarly journals Impact of Crude Oil Price Changes on Household Consumption Expenditure in Oman (1990-2016)

2019 ◽  
Vol 4 (2) ◽  
pp. 97-104
Author(s):  
Abubakar El-Sidig A.A Mahdi
Keyword(s):  
Crude Oil ◽  
Household Consumption ◽  
Oil Price ◽  
Consumption Expenditure ◽  
Crude Oil Price ◽  
Price Changes ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Bound Test

Objective – The preceding three years (2014, 2015, and 2016) saw a drop in the price of oil which has impacted all parts of Omani macroeconomic life. This study aims to identify the association between oil price changes and aggregate household consumption expenditure in the Sultanate by analyzing the long term relationship between the variables of interest. Methodology/Technique – The (ARDL) Autoregressive Distributed Lag bound test of co-integration is used with 27 annual observations obtained between 1990 and 2016. Findings – The statistical results show that there is a long term, positive relationship between the two variables. Novelty – As Oman is heavily dependent on oil, any fluctuation in the price of oil will undoubtedly cause instability in the economy (macroeconomic variables) demonstrating the presence of a robust correlation between consumption and oil prices. The bound test of the ARDL approach demonstrates this relationship. This study is therefore useful for Muscat officials to identify ways to reduce the dependency on oil. Type of Paper: Empirical Keywords: Total Household Consumption Expenditure; Crude Oil Price; Autoregressive Distributed Lag (ARDL); Omani Economy. Reference to this paper should be made as follows: Abubakar El-Sidig A.A Mahdi. 2019. Impact of Crude Oil Price Changes on Household Consumption Expenditure in Oman (1990-2016), J. Bus. Econ. Review 4 (2): 97 – 104. https://doi.org/10.35609/jber.2019.4.2(4) JEL Classification: D1, D13, D19, E30.

scholarly journals MACROECONOMIC VARIABLES AND STOCK MARKET MOVEMENT IN NIGERIA (1988 – 2019)

2021 ◽  
Vol 8 (1) ◽  
pp. 86-95
Author(s):  
Olaolu O. ◽  
◽  
Nwankpa C. ◽  
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Inflation Rate ◽  
Equity Market ◽  
Oil Price ◽  
Portfolio Investment ◽  
Crude Oil Price ◽  
Foreign Portfolio Investment

The goal of this study was to analyse empirically the effect on the stock market movement of five selected macro-economic variables, including the exchange rate, inflation rate, interest rate, crude oil price, and foreign portfolio investment. For the movement of the stock market, stock market capitalizations were used as a reference. Information from the annual time series covering the period between 1988 and 2019 was used. The analysis started with examining stochastic characteristics of each time series by testing their stationarity using Augmented Dickey Fuller (ADF) test. The findings show that only equity market capitalization and crude oil price was found stationary at level, while the other time series were found stationary at first difference. The bounds cointegration test procedure indicates that the variables have long-run equilibrium relationship amongst themselves. Analysis from the study showed that foreign exchange rate, interest rate, inflation rate, crude oil, and foreign portfolio investment are all significant in determining the performance of equity market capitalisation. They were all found to have a significant effect on stock market movement in Nigeria. Based on these findings, the study recommended that there is need to formulate sustainable macro-economic policies to curtail depreciation of the Naira, high inflation, and interest rate while attracting long-term foreign portfolio investors into Nigeria. Aggressive diversification of the economy should be made from its mono-cultural dependence on oil whose price over which Nigeria has no control.

scholarly journals Do Crude Oil Price Changes Affect Economic Welfare? Empirical Evidence from Ghana

2020 ◽  
Vol 20 (1) ◽  
pp. 51-58
Author(s):  
K. Kamasa
Keyword(s):  
Crude Oil ◽  
Oil Price ◽  
Series Data ◽  
Economic Welfare ◽  
Crude Oil Price ◽  
Price Changes ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
The Impact

Abstract This paper sought to explore the impact of crude oil price changes on economic welfare in Ghana. The paper employed the Autoregressive distributed lag (ARDL) estimation technique on an annual time series data spanning 1983 – 2017. The findings revealed that crude oil price changes have a negative and significant impact on economic welfare in the short and long run, albeit marginal. In terms of covariates, the findings revealed that trade openness and gross fixed capital formation have positive and significant impact whilst interest rate have negative impact on economic welfare in both the short and long run. Foreign direct investment had a positive effect, albeit insignificant. The paper recommends among others, the hedging of prices with respect to imported crude oil so as to manage the risks associated with crude oil price changes on economic welfare.   Keywords: Economic Welfare; Crude Oil Prices Changes; Autoregressive Distributed Lag; Ghana

Forecasting Crude Oil price using Artificial Neural Network model

2021 ◽  
pp. 321-326
Author(s):  
Sivaprakash J. ◽  
Manu K. S.
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Crude Oil ◽  
Back Propagation ◽  
Oil Prices ◽  
Oil Price ◽  
Back Propagation Algorithm ◽  
Crude Oil Price ◽  
Propagation Algorithm ◽  
Crude Oil Prices

In the advanced global economy, crude oil is a commodity that plays a major role in every economy. As Crude oil is highly traded commodity it is essential for the investors, analysts, economists to forecast the future spot price of the crude oil appropriately. In the last year the crude oil faced a historic fall during the pandemic and reached all time low, but will this situation last? There was analysis such as fundamental analysis, technical analysis and time series analyses which were carried out for predicting the movement of the oil prices but the accuracy in such prediction is still a question. Thus, it is necessary to identify better methods to forecast the crude oil prices. This study is an empirical study to forecast crude oil prices using the neural networks. This study consists of 13 input variables with one target variable. The data are divided in the ratio 70:30. The 70% data is used for training the network and 30% is used for testing. The feed forward and back propagation algorithm are used to predict the crude oil price. The neural network proved to be efficient in forecasting in the modern era. A simple neural network performs better than the time series models. The study found that back propagation algorithm performs better while predicting the crude oil price. Hence, ANN can be used by the investors, forecasters and for future researchers.

scholarly journals Exploring relationship between crude oil price volatility and stock indices movement using wavelet analysis: evidence from India and China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shekhar Mishra ◽  
Sathya Swaroop Debasish
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Crude Oil ◽  
Equity Market ◽  
Oil Price ◽  
Discrete Wavelet ◽  
Crude Oil Price ◽  
Content Type ◽  
India And China

Purpose This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China. Design/methodology/approach The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables. Findings The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market. Originality/value To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.

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