scholarly journals Measuring the Relationship between Crude Oil Price, Stock Market and Gold Price with Reference India

2021 ◽  
Vol 2 (1) ◽  
pp. 37-45
Author(s):  
Jaheer Mukthar KP ◽  
Sivasubramanian K ◽  
Raju V
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Gold Price ◽  
Oil Price ◽  
Financial Policy ◽  
Oil Consumption ◽  
Crude Oil Price ◽  
Financial Variables ◽  
Crude Oil Prices ◽  
The Relationship

India is one among the highly potential market for the oil consumption. When we are considering the industrial line, natural gas and oil industry, it portraits a great significant influence on the economic growth and development through the GDP and per capita flow of income. The year-wise statistics was collected for two decades from 2000 to 2019 and the everyday prices such as gold price, Nifty opinions and Crude oil prices are intended and taken the annual averages of it. The aim for selecting the data from the year 2000 to 2019 is very vital. It was selected to find out the influence of new financial policy 1991 after 10 years of its application. Moreover, the main implication of this work is to find the causal association among these financial variables. The price of gold is considered as 24 carat, the average price was taken for analysis. The ANOVA model has been applied to predict the relationship between the variables in order to find out the cause and effect.  It reveals the positive correlation between the variables. It is also revealed from the study that the price of gold had an exponential increase over a period of two decades and alongside the Nifty points also increased in the same period of time. On the whole, it is found from the data that the gold price is having the positive relation with Nifty points of the stock market and the crude oil price did not have any influence on the determination of gold price.

The optimal thermal causal path analysis on the relationship between international crude oil price and stock market

Kybernetes ◽  
2018 ◽  
Vol 47 (6) ◽  
pp. 1242-1261 ◽  
Author(s):  
Can Zhong Yao ◽  
Peng Cheng Kuang ◽  
Ji Nan Lin
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Markets ◽  
Oil Prices ◽  
Oil Price ◽  
Chinese Stock Market ◽  
Crude Oil Price ◽  
Content Type ◽  
Crude Oil Prices ◽  
Causal Path

Purpose The purpose of this study is to reveal the lead–lag structure between international crude oil price and stock markets. Design/methodology/approach The methods used for this study are as follows: empirical mode decomposition; shift-window-based Pearson coefficient and thermal causal path method. Findings The fluctuation characteristic of Chinese stock market before 2010 is very similar to international crude oil prices. After 2010, their fluctuation patterns are significantly different from each other. The two stock markets significantly led international crude oil prices, revealing varying lead–lag orders among stock markets. During 2000 and 2004, the stock markets significantly led international crude oil prices but they are less distinct from the lead–lag orders. After 2004, the effects changed so that the leading effect of Shanghai composite index remains no longer significant, and after 2012, S&P index just significantly lagged behind the international crude oil prices. Originality/value China and the US stock markets develop different pattens to handle the crude oil prices fluctuation after finance crisis in 1998.

scholarly journals THE IMPACT OF OIL PRICE ON STOCK MARKET:EMPIRICAL EVIDENCE FROM US

2021 ◽  
Vol 9 (1) ◽  
pp. 330-337
Author(s):  
Shanaz hakim , Tugut Tursoy,
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Negative Impact ◽  
Positive Impact ◽  
Oil Price ◽  
P Value ◽  
Crude Oil Price ◽  
Crude Oil Prices ◽  
Interactive Relationship ◽  
The Impact

The analysis of this research focuses on the interactive relationship among the fluctuation of crude oil prices, the real GDP and the stock market of United State. This empirical investigation uses data is in between 1990 and 2018 with the Vector Auto-regression (VAR) analysis, and multiple regressions with its assumption were used in order to analyses data.  Findings, oil price and economic growth are very important determinates of stock market in US because the p-value of this were less than the common alpha α =0.05. For instance, the crude oil price had positive impact on stock market because for each unit increasing of crude oil price, the stock market will increase by (0.276901) after holding all other variable constant. However, we find that GDP has negative impact on the participations of increasing the stock market.

scholarly journals Impact of Macro - Economic Factors on Indian Stock Market- A Research of BSE Sectoral Indices

2019 ◽  
Vol 8 (2S7) ◽  
pp. 597-602
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Stock Prices ◽  
Gold Price ◽  
Oil Price ◽  
Economic Factors ◽  
Crude Oil Price ◽  
The Impact

Macro-Economic factors plays a major role in decision making. Evaluation of macroeconomic environment is required to examine the behaviour of stock prices, which further influences the investor’s investment behaviour. Even though some macro-economic factors are not directly related to the company or industry, but those factors has an impact on stock prices, further economic activity in the domestic and global level has its own impact on stock market. When economy of the country grows hastily, it leads to faster growth in the industry and vice versa. Financial market plays a central role in the performance of financial system of an economy. Stock market is a market where securities of listed companies are exchanged between different investors, it is very responsive market which, gives a stage to investors to invest their money in various securities. Market indices are the tools to measure the performance of various securities of stock market and Investors make use of those market indices to analyse performance of those industries in which, they prefer to invest. This study takes into account six macro-economic factors (Crude oil Price, Gold Price, Silver Price, Exchange Rate, Inflation and Interest Rate) to study & analyse the impact of these variables on selected sectoral indices at BSE, SENSEX, S&P BSE BANKEX, S&P BSE Oil and Gas, S&P BSE Capital Goods, S&P BSE Consumer Durables, S&P BSE Reality, S&P BSE PSU and S&P BSE Power. The study shows that gold price, exchange rate, consumer price index and interest rate are positively correlated with four indices but crude oil price and silver price have positively correlated with 3 indices. So from the result it is clear that investor need to take of all the variables for their investment decision and the investment banker also take care of these indicators before giving suggestion to their clients

scholarly journals Crude Oil Price Shock and the Nigerian Stock Market Performance in the Face of Covid-19 Pandemic Evidence from ARDL & Granger Causality Approach

2021 ◽  
pp. 35-45
Author(s):  
Hammayo Abubakar ◽  
Kamal Tasiu Abdullahi
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Capital Market ◽  
Market Performance ◽  
Oil Price ◽  
Crude Oil Price ◽  
Crude Oil Prices ◽  
Stock Market Performance ◽  
Oil Price Shock ◽  
Price Shock

The study examined empirically the linear relationship between crude oil price shock and the Nigerian stock market performance, with the main objective of ascertaining the impact of the recent sharp decline in crude oil prices on stock market performance in the face of the global socio-economic challenge posed by COVID-19 pandemic. It used monthly time series data from the central bank of Nigeria (CBN) website (www.cbn.gov.ng) from 2017-2020 This period was chosen to capture the effects of changes in oil price on the performance of the Nigerian stock market within the context of the global economic challenges due to the COVID-19 pandemic. The auto-regressive distributed lag ARDL approach has been applied in the model specification and data analysis for the study. The results of the ARDL in both the short and long run revealed that the recent crude oil price shock has a significant impact on stock market performance in Nigeria. The results of the granger causality test also reveal a unidirectional causality from crude oil price to stock market performance with a piece of evidence from the current decline of global crude oil prices from December 2019 to April 2020. The study, therefore, suggests the need for the Nigerian capital market to continue to pursue with vigor the implementation of the capital market master plan in the hope that a more developed capital market should be able to absorb external shocks such as those arising from crude oil price fluctuations.

Crude Oil Price and Food Security Related Variables in Malaysia

2016 ◽  
Vol 4 (2) ◽  
pp. 17-21
Author(s):  
Shri Dewi Applanaidu ◽  
Mukhriz Izraf Azman Aziz
Keyword(s):  
Food Security ◽  
Crude Oil ◽  
Price Index ◽  
Price Volatility ◽  
Food Price ◽  
Oil Price ◽  
Crude Oil Price ◽  
Price Changes ◽  
Oil Price Volatility ◽  
Crude Oil Prices

Objective - This study analyzes the dynamic relationship between crude oil price and food security related variables (crude palm oil price, exchange rate, food import, food price index, food production index, income per capita and government development expenditure) in Malaysia using a Vector Auto Regressive (VAR) model. Methodology/Technique - The data covered the period of 1980-2014. Impulse response functions (IRFs) was applied to examine what will be the results of crude oil price changes to the variables in the model. To explore the impact of variation in crude oil prices on the selected food security related variables forecast error variance decomposition (VDC) was employed. Findings - Findings from IRFs suggest there are positive effects of oil price changes on food import and food price index. The VDC analyses suggest that crude oil price changes have relatively largest impact on real crude palm oil price, food import and food price index. This study would suggest to revisiting the formulation of food price policy by including appropriate weight of crude oil price volatility. In terms of crude oil palm price determination, the volatility of crude oil prices should be taken into account. Overdependence on food imports also needs to be reduced. Novelty - As the largest response of crude oil price volatility on related food security variables food vouchers can be implemented. Food vouchers have advantages compared to direct cash transfers since it can be targeted and can be restricted to certain types of products and group of people. Hence, it can act as a better aid compared cash transfers. Type of Paper - Empirical Keywords: Crude oil price, Food security related variables, IRF, VAR, VDC

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 A Research on Markov Model and Hidden Markov Model in Crude Oil Price Forecasting for PETRONAS Malaysia

2019 ◽  
Vol 8 (12S2) ◽  
pp. 121-125 ◽  
Keyword(s):  
Markov Model ◽  
Crude Oil ◽  
Hidden Markov Model ◽  
Structural Equation ◽  
Hidden Markov ◽  
Oil Price ◽  
Price Forecasting ◽  
Crude Oil Price ◽  
Crude Oil Prices ◽  
Accurate Forecast

Crude oil price forecasting is an essential component of sustainable development of many countries as crude oil is an unavoidable product that exists on earth. In this paper, a model based on a hidden Markov model and Markov model for crude oil price forecasting was developed, and their relative performance was compared. Path analysis of Structural Equation Modelling was employed to model the effects of forecasted prices and the actual crude oil price to get the most accurate forecast. The key variables used to develop the models were monthly crude oil prices s from PETRONAS Malaysia. It was found that the hidden Markov model was more accurate than the Markov model in forecasting the crude oil price. The findings of this study show that the hidden Markov model is a potentially promising method of crude oil price forecasting that merit further study.

scholarly journals Data Size Requirement for Forecasting Daily Crude Oil Price with Neural Networks

2019 ◽  
Vol 66 (3) ◽  
pp. 363-388
Author(s):  
Serkan Aras ◽  
Manel Hamdi
Keyword(s):  
Neural Networks ◽  
Crude Oil ◽  
Significant Interaction ◽  
Statistical Tests ◽  
Oil Price ◽  
Training Data ◽  
Forecasting Model ◽  
Crude Oil Price ◽  
Crude Oil Prices ◽  
Selection Of

When the literature regarding applications of neural networks is investigated, it appears that a substantial issue is what size the training data should be when modelling a time series through neural networks. The aim of this paper is to determine the size of training data to be used to construct a forecasting model via a multiple-breakpoint test and compare its performance with two general methods, namely, using all available data and using just two years of data. Furthermore, the importance of the selection of the final neural network model is investigated in detail. The results obtained from daily crude oil prices indicate that the data from the last structural change lead to simpler architectures of neural networks and have an advantage in reaching more accurate forecasts in terms of MAE value. In addition, the statistical tests show that there is a statistically significant interaction between data size and stopping rule.

scholarly journals PENGARUH NILAI TUKAR DAN HARGA MINYAK MENTAH DUNIA TERHADAP RETURN SAHAM PT. INDOMOBIL SUKSES INTERNASIONAL TBK. DAN PT. ASTRA INTERNASIONAL TBK. TAHUN 2006-2016

2017 ◽  
Vol 1 (2) ◽  
pp. 61
Author(s):  
Arif Fadlilah ◽  
Sri Hermuningsih
Keyword(s):  
Exchange Rates ◽  
Crude Oil ◽  
Stock Prices ◽  
Stock Return ◽  
T Test ◽  
Oil Price ◽  
Crude Oils ◽  
Crude Oil Price ◽  
F Test ◽  
Crude Oil Prices

This research is meant to find out the influence of exchange rates and crude oil price either simultaneous or partial to the stock return at PT. Indomobil Sukses Internasional Tbk. and PT Astra Internasional Tbk. The data which is applied in this research is the automotive companies’ stock prices, Rupiah exchange rates, and crude oil price from 2006 to 2016. The multiple linear regressions are applied as the analysis technique by carrying out F test and t test. Based on the F test it is found that simultaneously the rupiah exchange rates and crude oil prices have influence to the stock return. Based on the t test it is found that partially the rupiah exchange rates have no influence to PT. Indomobil Sukses Internasional Tbk stock return but have influence to PT. Astra Internasional Tbk stock return and crude oils prices have influence to stock return. t test indicates the dominant influence to the stock return PT. Indomobil Sukses International Tbk is crude oils variable and stock return PT. Astra International Tbk is exchange rates variable

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