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1
Yelamanchili, Rama Krishna. "Short-term Economic Indicators, Stock Market Indexes and Indian Oil and Gas Stocks Returns." Indian Journal of Finance and Banking 4, no. 1 (January 8, 2020): 1–13. http://dx.doi.org/10.46281/ijfb.v4i1.454.
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In this paper we examine the causal relationship between short term economic indicators, stock market indexes and oil and gas stocks returns. We postulate that economic indicators positively and significantly cause and predict stock market indexes and oil and gas stock returns in short run. In addition, we posit that stock market indexes cause and predict oil and gas stock returns in short run. To test our hypotheses we chose four short-term economic indicators, two stock market indexes, and 10 oil and gas companies. Our results indicate that there is no causal relationship between both short-term economic indicators and stock market indexes, and between short-term economic indicators and oil and gas stock returns. However, we receive support to one of our hypotheses that stock market indexes cause oil and gas stock returns. This causation is contemporaneous only and we observe that stock market indexes lack short-term predictive power of oil and gas stock returns. We conclude that investors need to be vigilant in considering coincident indicators as explanatory variables to predict stock returns. We suggest that stock market indexes are helpful to predict contemporaneous returns but not future returns of oil and gas stocks.
JEL Classification: B1, C32, D4, G2.
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Sedighi, Mohammadi, Fard, and Sedighi. "The Nexus between Stock Returns of Oil Companies and Oil Price Fluctuations after Heavy Oil Upgrading: Toward Theoretical Progress." Economies 7, no. 3 (July 10, 2019): 71. http://dx.doi.org/10.3390/economies7030071.
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This study attempts to discover the nexus between crude oil price fluctuation after heavy oil upgrading and stock returns of petroleum companies in the U.S. Stock Exchange for the years 2008 to 2018. One of the methods of upgrading heavy crude oil is to extract asphaltene from crude oil. Considering the Asphaltene Removal (AR) as a factor in the nexus between oil price and the stock market is an innovation in the literature of energy finance. Asphaltenes cause many problems in the petroleum industry, which increases the cost of oil production and reduces the financial efficiency of oil companies. The AR is certainly one of the significant matters of the oil industry and can affect the price of oil. Therefore, changes in the price of oil can influence the price of oil company stocks. Hence, changes in stock prices will certainly affect the stock returns of oil companies. In an effort to solve this puzzle, the four financial models were employed to explore the nexus between oil price fluctuations and stock returns. The analysis of the results demonstrated that the oil price fluctuations caused by the removal of asphaltenes influence the stock returns of petroleum companies. Eventually, the theoretical hypothesis was confirmed by considering the USA as a case study. The outcomes of this investigation are a theoretical progression in areas related to the petroleum industry and the stock market that could lead to the adoption of new investment policies in the petroleum industry including investing in new procedures to manage and decrease the costs and time of the AR process, which would result in the advancement of petroleum companies. In fact, we have introduced a modern investment strategy in the oil industry aimed at reducing oil production costs, improving financial statements and increasing the stock returns of petroleum companies. Eventually, we will present new investment policies in the oil industry that can lead to economic growth and development of financial markets especially stock market, derivatives market, futures exchange, commodities exchange, as well as bond market.
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Khurshid, Muzammil, and Berna Kirkulak-Uludag. "Shock and volatility spillovers between oil and emerging seven stock markets." International Journal of Energy Sector Management 15, no. 5 (April 5, 2021): 933–48. http://dx.doi.org/10.1108/ijesm-02-2020-0014.
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Purpose This study aims to examine the volatility spillover effects between oil and stock returns in the emerging seven economies. Design/methodology/approach In this study, the Granger causality test and vector autoregression-generalized autoregressive conditional heteroskedasticity approach to analyze the volatility spillover from 1995 to 2019 were used. The findings provide evidence of significant volatility spillover between oil and Brazil, China, India, Indonesia, Mexico, Russia and Turkey (E7) stock markets. Findings All emerging seven stock markets exhibit positive and low constant conditional correlations with oil assets. The magnitude of the correlation changes in respond to the country’s net position in the crude oil market. While a relatively high level of correlation exists between oil and the stock markets of net oil-exporting countries, a relatively low level of correlation exists between oil and the stock markets of net oil-importing countries. Originality/value The findings suggest that oil asset improves the risk-adjusted performance of a well-diversified portfolio of stocks. However, investors should invest a larger portion of their portfolios in E7 stock markets than in oil.
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Atiq, Zeeshan, and Muhammad Farhan. "IMPACT OF OIL PRICES ON STOCK RETURNS: EVIDENCE FROM PAKISTAN’S STOCK MARKET." Journal of Social Sciences and Humanities 57, no. 2 (December 31, 2018): 47–63. http://dx.doi.org/10.46568/jssh.v57i2.31.
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Very few studies have investigated the movement in stock returns that result due to changes in oil prices. In recent years due to cooling down of China, unveiled oil reserves of Iran, decreasing demand worldwide and discovery of shale gases the world has experienced a large fall in the oil prices. These changes are also affecting performance of manufacturing and other associated companies in countries all over the world. Pakistan has also been affected by these changes in many ways. Especially, the returns on stock markets have been affected a lot by the variations in the oil prices. This paper using monthly data set from years 2014 to 2016 of the non-financial firms operated in Pakistan Stock Exchange (PSX), investigates the effect of variation in oil prices on returns on stock. Results from the panel data analysis indicate a negative relationship between the variables. Since, Pakistan is an oil importing, movement in the prices contribute towards affecting the production cost in a positive manner which in turn affects the execution of the enterprises as well as returns of the stocks negatively.
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Tusiime, Ivan Mugarura, and Man Wang. "Are Islamic stocks subject to oil price risk exposure?" Journal of Risk Finance 21, no. 2 (April 18, 2020): 181–200. http://dx.doi.org/10.1108/jrf-05-2019-0076.
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Purpose The purpose of this paper is to examine whether oil price risk is a significant determinant of stock returns. Design/methodology/approach Using monthly data on a sample of Islamic stocks listed on the New York Stock Exchanges and National Association of Securities Dealers Automated Quotations System (NASDAQ) over the period from January 1990 to December 2017, the study examines whether oil price risk is a significant determinant of stock returns using Fama–French–Carhart’s four-factor asset pricing model amplified with Brent oil price factor. Findings The results from the cross-sectional regression analysis indicate that the extent of the exposure is significantly positive using a full sample period. Moreover, results from size and momentum factors are highly significant whereas book-to-market has no significant impact on Islamic stock returns. Research limitations/implications The results support the concept for diversification in equity investment and are thus important for investors, analysts and policymakers. Originality/value This study is the first of its kind to establish whether oil price risk is a factor that can determine returns of Islamic listed stocks using the most developed stock market in the world (New York Stock Exchanges and NASDAQ).
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Hoque, Mohammad Enamul, Soo-Wah Low, and Mohd Azlan Shah Zaidi. "The Effects of Oil and Gas Risk Factors on Malaysian Oil and Gas Stock Returns: Do They Vary?" Energies 13, no. 15 (July 31, 2020): 3901. http://dx.doi.org/10.3390/en13153901.
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This study explores Malaysian oil and gas stocks’ exposure to oil and gas risk factors, paying special attention to subindustry classification, stock size, book-to-market value, and volatility state. The study employs firm-level weekly frequency data of oil and gas firms and several multi-asset pricing models within a GARCH (1,1)-X and Markov-switching framework. The empirical findings reveal that oil price, gas price, and exchange rate exhibit positive effects on the stock returns of all oil and gas sub-industries, but they exhibit negative effects on gas utilities sub-industry stock returns. The empirical findings also reveal that the extent of this effect varies across sub-industry, stock size, book-to-market value, and volatility states. Thus, the findings suggest the existence of asymmetric, heterogeneous, and non-linear exposures.
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Salisu, Afees Adebare, Raymond Swaray, and Tirimisiyu Oloko. "US stocks in the presence of oil price risk: Large cap vs. Small cap." Economics and Business Letters 6, no. 4 (March 18, 2018): 116. http://dx.doi.org/10.17811/ebl.6.4.2017.116-124.
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This study queries the act of making generalization about the dynamics of returns and volatility spillovers between oil price and U.S. stocks by merely considering only large cap stocks. It argues that this kind of generalization may be misleading, as the reactions of large cap, mid cap and small cap stocks to change in oil prices are not expected to be uniform. Our findings show that it is correct to make generalization about oil-U.S. stock relationship with large cap stocks when analysing returns spillovers, but the generalization is incorrect when considering stock caps returns volatility spillovers, particularly under falling and relatively stable oil prices.
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Youssef, Manel, and Khaled Mokni. "Do Crude Oil Prices Drive the Relationship between Stock Markets of Oil-Importing and Oil-Exporting Countries?" Economies 7, no. 3 (July 10, 2019): 70. http://dx.doi.org/10.3390/economies7030070.
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The impact that oil market shocks have on stock markets of oil-related economies has several implications for both domestic and foreign investors. Thus, we investigate the role of the oil market in deriving the dynamic linkage between stock markets of oil-exporting and oil-importing countries. We employed a DCC-FIGARCH model to assess the dynamic relationship between these markets over the period between 2000 and 2018. Our findings report the following regularities: First, the oil-stock markets’ relationship and that between oil-importing and oil-exporting countries’ stock markets themselves is time-varying. Moreover, we note that the response of stock market returns to oil price changes in oil-importing countries changes is more pronounced than for oil-exporting countries during periods of turmoil. Second, the oil-stock dynamic correlations tend to change as a result of the origin of oil prices shocks stemming from the period of global turmoil or changes in the global business cycle. Third, oil prices significantly drive the relationship between oil-importing and oil-exporting countries’ stock markets in both high and low oil-stock correlation regimes.
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Priambodo, Oktanindita, Hariyadi, Suwarto, and I. Putu Santikayasa. "Influence of Land Use and Rainfall on Carbon Stock Dynamics for Oil Palm and Rubber." Agromet 34, no. 2 (December 14, 2020): 121–28. http://dx.doi.org/10.29244/j.agromet.34.2.121-128.
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The expansion of agricultural commodities including oil palm plantations potentially causes an increase of greenhouse gas emissions by amplifying carbon dioxide (CO2) in the atmosphere. In the long term, this amplification will alter climate change. However, oil palm also has the potency to reduce greenhouse gas emissions by absorbing CO2 through photosynthesis. This study aims to determine the carbon stock that can be absorbed by oil palm and rubber plants, and to determine the relationship of rainfall with carbon stock in oil palm plants. The study used satellite image data based on Landsat and combined with rainfall data from near Perbaungan District, North Sumatra. Three Landsat data (acquisition date: (i) 12 February 2000, (ii) 8 March 2009, and (iii) 11 August 2019) were processed to estimate carbon stock. The procedure for estimating carbon stock was as follows: determining the sample and digitizing the sampling points, converting the digital value of the numbers into the spectral spectrum, calculating the albedo values, calculating the long-wave and short-wave radiations, computing biomass, and the absorbed carbon stock. The results showed that the carbon stock in oil palm was greater than that of rubber plants as oil palm has a greater biomass. The greater the plant biomass, the bigger the carbon stock absorbed. Further, the findings revealed that rainfall in dry season has a contribution to carbon stock in oil palm and rubber. The higher the total rainfall during dry season will increase the absorbed carbon stocks.
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Puspitasari, Ardina, Hermanto Siregar, and Trias Andati. "ANALISIS INTEGRASI BURSA SAHAM ASEAN 5." JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN 4, no. 2 (January 31, 2018): 187–206. http://dx.doi.org/10.29244/jekp.4.2.187-206.
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This study aimed to analyze the integration of the stock markets of ASEAN 5 (Indonesia, Malaysia, Singapore, Thailand, and the Philippines) associated with the event of dropped world oil prices in 2014. This study using Vector Error Correction Model (VECM) to analyze market integration 5 stocks with variable stock market. In this study uses a dummy variable of oil price with the value of 0 for the period 2009 to 2013 where world oil prices are still stable and the value of 1 for the period 2014 to 2015 where a decline in world oil prices. Results from this study shows that there is a relationship between the stock market cointegration ASEAN 5 during the study period that’s mean that there is integration among ASEAN 5 stock markets. Indonesia's stock market is influenced by Thailand and Singapore in the long term. Dummy variables significantly influence the JCI during the short term.
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Puspitasari, Ardina, Hermanto Siregar, and Trias Andati. "ANALISIS INTEGRASI BURSA SAHAM ASEAN 5." JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN 4, no. 2 (January 31, 2018): 187–206. http://dx.doi.org/10.29244/jekp.4.2.2015.187-206.
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This study aimed to analyze the integration of the stock markets of ASEAN 5 (Indonesia, Malaysia, Singapore, Thailand, and the Philippines) associated with the event of dropped world oil prices in 2014. This study using Vector Error Correction Model (VECM) to analyze market integration 5 stocks with variable stock market. In this study uses a dummy variable of oil price with the value of 0 for the period 2009 to 2013 where world oil prices are still stable and the value of 1 for the period 2014 to 2015 where a decline in world oil prices. Results from this study shows that there is a relationship between the stock market cointegration ASEAN 5 during the study period that’s mean that there is integration among ASEAN 5 stock markets. Indonesia's stock market is influenced by Thailand and Singapore in the long term. Dummy variables significantly influence the JCI during the short term.
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Farhan, Muhammad, and Syed Shahid Zaheer Zaidi. "Oil Price Shocks and Stock Market Performance: A comparison between Oil Exporting and Oil Importing Nations." South Asian Journal of Management Sciences 15, no. 2 (2021): 118–34. http://dx.doi.org/10.21621/sajms.2021152.01.
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The paper explores the impact of shocks in oil prices on the stock market for the oil importing and exporting nations. As Pakistan is heavily dependent on imports of oil therefore, we focus on Pakistan as an oil importing nation and have taken Iran, as an oil exporting nation because, it is considered to be among top ten nations of the world that exports oil. Various studies in Pakistan have investigates the relationship between shocks in prices of oil and return on the stock but none of the study has examined the association between shocks in oil prices and return on the stock market by comparing Pakistan and Iran as an oil importer and exporter nations of the world. This study has employed Autoregressive Distributed Lag model to find out the relationship between dependent and independent variables. We have taken prices of oil as an independent variable, whereas, stock price has been taken as a dependent variable. On the other hand, rate of exchange and rate of interest are the other independent variables. The results of this study and bound test reveals a long run association between prices of oil and the stock return for both nations. It has been indicated in the results that high oil prices have an adverse impact on market of stock for an oil importing nation (i.e., Pakistan) and have positively impacted on Iran which is an oil exporter nation. The results confirm that oil price shock contributed towards positively affecting the market of stock of an oil exporter nation but negatively affected the stock market if an oil importing nation. The author recommended the investors of both nations to evaluate various alternatives to diversify portfolios of their stock market by utilizing other financial assets.
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Safitri, Yunita Dewi, and Robiyanto Robiyanto. "KORELASI DINAMIS ANTARA PERGERAKAN HARGA MINYAK DUNIA DAN INDEKS HARGA SAHAM SEKTORAL DI BURSA EFEK INDONESIA." Jurnal Ekonomi Bisnis dan Kewirausahaan 9, no. 3 (December 28, 2020): 188. http://dx.doi.org/10.26418/jebik.v9i3.42949.
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Changes in the situation that move very quickly on the commodity market have an impact on financial markets, one of which is the stock market in Indonesia. Therefore this study aims to examine the dynamic correlation between the movement of world oil prices and the Sectoral Stock Price Index listed on the Indonesia Stock Exchange (IDX). The data used is obtained from secondary data in the form of daily closing price data for world oil prices and Sectoral Stock Price Index from January 2017 to June 2020. The analysis technique used is Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH), due to previous studies mostly using a static approach. The results of this study show that the DCC-GARCH value between world oil prices (Brent and WTI) and Sectoral Stock Price Index tends to be very weak. A negative dynamic correlation was also found in the Consumer Goods Sector. This research can be a reference for investors who want to invest stocks in Indonesia by looking at the correlation between world oil prices and the Sectoral Stock Price Index.
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JONES, CHARLES M., and GAUTAM KAUL. "Oil and the Stock Markets." Journal of Finance 51, no. 2 (June 1996): 463–91. http://dx.doi.org/10.1111/j.1540-6261.1996.tb02691.x.
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Van Hecke, T. "Optimal planning of oil stock." Journal of Statistics and Management Systems 14, no. 2 (March 2011): 289–94. http://dx.doi.org/10.1080/09720510.2011.10701557.
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Guesmi, Khaled, Heni Boubaker, and Van Son Lai. "From Oil to Stock Markets." Journal of Economic Integration 31, no. 1 (March 15, 2016): 103–33. http://dx.doi.org/10.11130/jei.2016.31.1.103.
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Chen, Chun-Da, Chiao-Ming Cheng, and Rıza Demirer. "Oil and stock market momentum." Energy Economics 68 (October 2017): 151–59. http://dx.doi.org/10.1016/j.eneco.2017.09.025.
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Hoque, Mohammad Enamul, and Soo-Wah Low. "Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework." Mathematics 8, no. 10 (October 9, 2020): 1732. http://dx.doi.org/10.3390/math8101732.
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This study employs a mean semi-variance asset pricing framework to examine the influence of risk factors on stock returns of oil and gas companies. This study also examines how downside risk is priced in stock performance. The time-series estimations expose that market, size, momentum, oil, gas, and exchange rate have significant impacts on oil and gas stock returns, but effects are heterogeneous depending on an individual stock. The two-stage cross-section estimations provide new insights about investors’ risk-return trade-off when facing downside risks. The results show that downside risk exposures to market, momentum, oil, and exchange rate factors are negatively priced in the Malaysian oil and gas stocks. This implies that investors are penalized for their downside exposure to these risk factors, and such inference is consistent with the risk preference explanation of prospect theory. Liquefied natural gas (LNG) is the only risk factor found to be positively priced in the returns of oil and gas stocks. Additionally, we find a negative relationship between LNG factor and total risk. This suggests that as the risk exposure to LNG increases, the total risk decreases, implying that the LNG risk factor is an idiosyncratic risk and not a systematic risk factor. Such interpretation is consistent with the correlation result, which shows no association between LNG and the market risk factor.
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Ghosh, T. P. "Oil Dependency of GCC Stock Markets: Co-integration of GCC Stock Market Indices and Oil Price." International Journal of Business and Management 12, no. 1 (December 28, 2016): 188. http://dx.doi.org/10.5539/ijbm.v12n1p188.
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Oil dependent economies of GCC countries had passed through various cycles of boom and trough of oil price. In the aftermath of the economic recession of 2008 and oil price, the GCC countries have been pursuing plans for diversifying to non-oil revenues. The oil of 2014-16 raised the issue of stock market cointegration to oil price movement in the background of non-oil diversification.This research study analyzes long term cointegration of oil price and GCC stock indices, and also cointegration among the GCC stock indices per se in an attempt to investigate if there is any early sign of disintegration of GCC stock markets from oil price cyclicality. The study period is linked to cyclicality of oil price: the first period comprising of Jan 2006- Dec. 2011 that covers oil price cycle during economic recession of 2008, and the second period comprising of Jan 2012 –September 2016 which covers the post-economic recession oil price cycle. The null hypotheses is that oil price and stock market indices are co-integrated.Based on Johansen Cointegration test on Box Cox transformed data of oil price and seven stock market indices of GCC countries, it is found that oil price and GCC stock markets are co-integrated. Analysis using Augmented Dickey- Fuller test and Phillips –Perron test shows that data series are all I (1). This study establishes that efforts to reduce oil dependency in GCC countries is yet to result in decoupling of financial markets from oil price cyclicality. This study also establishes that GCC stock markets per se are co-integrated but factors of cointegration beyond oil price are not explored.
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BenMabrouk, Houda. "Cross-herding behavior between the stock market and the crude oil market during financial distress." Managerial Finance 44, no. 4 (April 9, 2018): 439–58. http://dx.doi.org/10.1108/mf-09-2017-0363.
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Purpose The purpose of this paper is to investigate herding behavior around the crude oil market and the stock market and the possible cross-herding behavior between the two markets. The analysis examines also the herding behavior during financial turmoil and includes the investor sentiment and market volatility. Design/methodology/approach The authors use a modified version of the cross-sectional standard deviation and the cross-sectional absolute deviation to include investor sentiment, financial crisis and market volatility. Findings The authors find that the volatility of the stock market reduces the herding behavior around the oil market and boosts that around the stock market. However, the investors’ sentiment reduces the herding around the stock market and boosts that around the crude oil market. Consequently, the authors can conclude that the herding behavior around the two markets moves inversely and the herding in each market is enhanced by the lack of information in the other market. Research limitations/implications This paper is limited to the herding of stocks around the crude oil market and ignores the possible herding of commodities around the oil market. Originality/value The originality of the paper rests on the study of the possible cross-herding behavior between the oil market and the stock market especially during financial turmoil.
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Asif, Muhammad, Sharif Ullah Jan, and Shahid Iqbal. "OIL PRICES MOVEMENTS AND INDUSTRY STOCK RETURNS: EVIDENCE FROM PAKISTAN STOCK EXCHANGE (PSX)." March 2021 37, no. 01 (March 30, 2021): 84–96. http://dx.doi.org/10.51380/gujr-37-01-08.
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The recent financial and economic recessions have chiefly increased the importance of risk management and forecasting for business firms. Capital markets being the main pillar of economy are affected the most in such circumstances. The current study has attempted to investigate the impact of oil prices on the returns and volatility of Pakistani listed firms using the GARCH (1,1) model. Furthermore, this relationship has been investigated by categorizing the existing sectors of the Pakistan Stock Exchange (PSX) into oil producers, oil users, and oil substitutes for the period from January 2015 to December 2019. The findings of the study highlighted some strong evidence regarding the oil price movement and the firms’ returns across these sectors. Interestingly, firms’ returns behave differently about the magnitude of significance and direction of symbols based on their nature of the industry. Therefore, it is suggested for future studies to consider the nature of the sector of oil while exploring the relationship between oil prices and stock returns.
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Chandra, Kristian. "THE EFFECT OF INFLATION LEVELS AND OIL PRICES ON STOCK RETURN FOOD AND BEVERAGE." Business and Entrepreneurial Review 17, no. 2 (August 12, 2019): 135. http://dx.doi.org/10.25105/ber.v17i1.5192.
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<p>This study aims to synthesize to see the consequences of inflation and oil prices on stock returns. The shares observed in this study are stocks that are included in the food and beverage section listed on the Indonesia Stock Exchange (IDX) during the year 2010-2015. To determine the sample sorted in this study is to use Purposive Sampling techniques to obtain samples that match the parameters that have been used as a benchmark. The number of food and beverage industry samples that meet the criteria are 13 listed on the Indonesia Stock Exchange in 2010-2015. Regression analysis using the EViews program was chosen as the method used in analyzing the data. The results confirm that inflation has a negative and significant effect on stock returns and oil prices have a positive and significant effect on the return of food and beverage stocks listed on the IDX in 2010-2015.</p>
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Oskooe, Seyyed Ali Paytakhti. "Oil price shocks and stock market in oil-exporting countries: evidence from Iran stock market." OPEC Energy Review 36, no. 4 (December 2012): 396–412. http://dx.doi.org/10.1111/j.1753-0237.2012.00217.x.
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Wu, Maoguo, and Daimin Lu. "Volatility Spillover Effect of International Crude Oil Futures and China-Russia Stock Market: A Multivariate BEKK-GARCH Model Based on Wavelet Multiresolution Analysis." Asian Journal of Finance & Accounting 11, no. 1 (May 19, 2019): 183. http://dx.doi.org/10.5296/ajfa.v11i1.14348.
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The increasingly prominent strategic position of crude oil determines its high impact on macro-economy. The value of crude oil is reflected in the price of crude oil futures. Stock market is the barometer of macro economy. To what extent does international crude oil futures price affect stock market? China and Russia are the biggest importer and exporter of crude oil, respectively. Crude oil is of strategic value to both countries. This study empirically investigates the volatility spillover effect of international crude oil futures and China-Russia stock market from April 24th, 2015 to April 20th, 2018, based on the data of international crude oil futures prices, China-Russia stock market composite index, and industry stock index. The empirical results show that there is a short-term relationship between China-Russia stock market composite index and international crude oil futures price. The international crude oil futures price has a greater explanatory power to Russian RTS index, but a smaller explanatory power to Shanghai composite index. All industry stock indices are cointegrated with international crude oil futures prices. Except for China industry and Russia energy, the adjustment coefficient of international crude oil futures price on stock index volatility of other industries is insignificant. This study mainly studies the relationship between international crude oil futures price and the comprehensive stock index and industry stock index of China and Russia, and compares the impact of international crude oil futures price on the stock market of the largest importer and the largest exporter of crude oil to explore the linkage between crude oil futures price and stock market, and puts forward policy implications based on the empirical results.
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Alqahtani, Abdullah, Amine Lahiani, and Ali Salem. "Crude oil and GCC stock markets." International Journal of Energy Sector Management 14, no. 4 (January 13, 2020): 745–56. http://dx.doi.org/10.1108/ijesm-06-2019-0013.
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Purpose This paper aims to investigate the transmission of international oil prices to the stock market indices of the Gulf Cooperation Council (GCC) countries over the weekly period from April 07, 2004, to August 15, 2018. Design/methodology/approach The authors use the augmented Dickey–Fuller (ADF) unit root test to check the order of integration of data series. Afterward, the authors use the ordinary least square method to determine the spillover of international oil prices to the stock markets of GCC countries while accounting for the time-varying volatility of oil and stock market returns through the generalized autoregressive conditional heteroskedasticity. Then, the Johansen (1991) cointegration test is used to determine the long-run equilibrium relationship. Finally, the Granger (1969) causality test is used to determine the short-run causal effects between oil and the stock markets returns of GCC countries. Findings The findings indicate that the stock markets of GCC countries are efficient and respond significantly to international oil prices and evidence of high volatility associated with oil returns. Originality/value Investors and portfolio managers should consider the association between international oil prices and GCC stock returns when allocating their funds for diversification strategy. Moreover, policymakers should better understand the behavior of local stock markets.
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Teulon, Frederic, and Khaled Guesmi. "Dynamic Spillover Between The Oil And Stock Markets Of Emerging Oil-Exporting Countries." Journal of Applied Business Research (JABR) 30, no. 1 (December 30, 2013): 51. http://dx.doi.org/10.19030/jabr.v30i1.8280.
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<p>The paper investigates the time-varying correlations between stock market returns and oil prices in oil-exporting countries. A multivariate GARCH-DCC process is employed to evaluate this relationship based on data from Venezuela, the United Arab Emirates, Saudi Arabia and Kuwait. The results show that there are time-varying correlations between the oil and stock markets in emerging, oil-producing countries, indicating that they are affected by conditions in world markets. In addition, the relationship between oil prices and stock returns is found to be influenced by the origin of shocks to oil prices, with stock market responses being stronger to demand-side shocks caused by political turmoil or fluctuations in the global business cycle than to supply-side shocks caused by cuts in oil production. The results also provide evidence of volatility spillovers between the oil and stock markets.</p>
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Wan, Jok-Tong, Evan Lau, and Rayenda Khresna Brahmana. "CONTAGIOUS EFFECTS OF OIL PRICES ON ASIAN STOCK MARKETS’ BEHAVIOUR." Journal of Indonesian Economy and Business 31, no. 1 (October 15, 2016): 141. http://dx.doi.org/10.22146/jieb.15275.
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The main objective of this study is to examine the stock markets’ shock due to the effect of the price of oil in the East Asia Region. Particularly, this study examines if there is stock market interdependence during global oil price shocks (sudden changes) for a sample of five total oil importers (the Philippines, Hong Kong SAR, Taiwan, South Korea, and Japan), four net oil importers (Indonesia, Singapore, Thailand, and China), and one net oil exporter (Malaysia) between 1999 and 2014. From the result, an oil price change is collectively found to have a small but significant positive impact on the stock markets, in particular where a sudden decrease in oil prices tends to cause a stock market downturn and volatility. The world economy’s spending, financial investments in oil futures and foreign investment by oil rich nations are some underlying motives for inducing this oil-stock positive relation. The same direction of time-varying conditional correlations is found across East Asian stock markets during negative oil price shocks. The integration among East Asian stock markets is inducing the oil shock contagion to be transmitted from direct oil-affected countries (South Korea, Hong Kong, and Singapore) to non-direct oil affected countries’ (Japan and Taiwan) stock markets. In spite of a long practiced ASEAN+3 macroeconomics surveillance process and Early Warning System (EWS) which can be customized for stock markets to prevent or detect the oil risk, hedging against initial oil-affected stock markets and a stronger influence by the East Asian countries in the global world of oil and capital investment are strongly suggested.Keywords: oil price; capital market integration; stock market behaviour
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Güntner, Jochen H. F. "HOW DO INTERNATIONAL STOCK MARKETS RESPOND TO OIL DEMAND AND SUPPLY SHOCKS?" Macroeconomic Dynamics 18, no. 8 (June 7, 2013): 1657–82. http://dx.doi.org/10.1017/s1365100513000084.
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Building on Kilian and Park's (2009) structural VAR analysis of the effects of oil demand and supply shocks on the U.S. stock market, this paper focuses on the differences and commonalities of stock price responses in oil exporting and importing economies in 1974–2011. Structural oil price shocks add to our understanding of the 2008 stock market crash. I find that unexpected reductions in world oil supply do not affect stock returns in any of six OECD countries. Although an increase in global aggregate demand consistently raises oil prices and cumulative real stock returns, the effect is more persistent for oil exporters. Other, e.g., precautionary oil demand shocks have a detrimental impact on stock markets in oil-importing countries, a statistically insignificant effect for Canada, and a significantly positive effect for Norway. Oil price shocks account for a larger share of the variation in aggregate international stock returns than in national stock returns.
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Viroja, Dharmendra H., and Ruhi D. Viroja. "Study of Dynamic Linkage between Stock-Market and Crude Oil." International Journal of Trend in Scientific Research and Development Volume-1, Issue-1 (December 31, 2016): 51–55. http://dx.doi.org/10.31142/ijtsrd102.
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Yusmia, Liza, and Abitur Asianto. "DETERMINANT ANALYSIS OF FINANCIAL SECTOR STOCK IN INDONESIA STOCKS EXCHANGE." Dinasti International Journal of Economics, Finance & Accounting 1, no. 5 (December 1, 2020): 850–64. http://dx.doi.org/10.38035/dijefa.v1i5.621.
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These research had purposed to examine related to macroeconomic variables on financial sector stock index in Indonesia Stock Exchange. This research used Vector Error Correction Model (VECM) method with monthly data from financial sector stock index as the dependent variable and the GDP quarterly data, as well as monthly data on inflation, BI interest rates, exchange rates, the Fed interest rate, gold prices, oil prices,and also the S&P 500 index as independent variable with data range from January 2014 to August 2019. These results that obtained from this research were the shocks in BI interest rate variable and the exchange rate which have positive responses in the long term, while the GDP, inflation, and Fed interest rates , gold prices, oil prices, and the S&P 500 index responded negatively in the long term by the financial sector stock index. Beside that, the BI interest rate variable has the greatest contribution in changed of financials stock index.
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Samsuar, Alfan, and Pardomuan Sihombing. "DETERMINANT ANALYSIS IN PROPERTY STOCKS INDEX AT INDONESIA STOCK EXCHANGE." Dinasti International Journal of Management Science 2, no. 2 (November 17, 2020): 255–67. http://dx.doi.org/10.31933/dijms.v2i2.453.
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This research aims to determine those influence of inflation, interest rates, exchange rates, world oil prices and world gold prices against the property sector stock index which registered In Indonesia Stock Exchange. These population of research were all activities from monthly movement of property sector stock index, inflation, exchange rates, BI interest rates, world oil prices and world gold prices. The sample chosen method by purposive sampling where the researcher gathered its data based on proficiency strategies or personal considerations, selecting data based on these following criteria: 1) Availability of macro economic data that affects shares from property sector during January 2016 to December 2019; and 2) Availability of property stock index data from January 2016 till December 2019. The model used in this research was the Vector Error Correction Model (VECM). With The results showed that: 1) ISP responsiveness to inflation movements where stumbled or shocks that occur on inflation had positive influence towards ISP movements; 2) Responsiveness of ISP to instability or shocks that occur in exchange rates will negatively affect ISP movements; 3) Those responsiveness of ISP to the BI rate movement was responded positively; 4) Based on these results from research conducted, the ISP responded negatively on stumbled or shocks towards oil price movements; and 5) ISP responsiveness to movements or shocks to gold price had been responded positively by the ISP.
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Çevik, Emrah, Erdal Atukeren, and Turhan Korkmaz. "Oil Prices and Global Stock Markets: A Time-Varying Causality-In-Mean and Causality-in-Variance Analysis." Energies 11, no. 10 (October 21, 2018): 2848. http://dx.doi.org/10.3390/en11102848.
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This study examines the Granger-causal relationships between oil price movements and global stock returns by using time-varying Granger-causality tests in mean and in variance. We use the daily returns from Morgan Stanley Capital International (MSCI) G7 and the MSCI Emerging Stock Market Indexes to distinguish between the effects of daily oil price movements on G7 countries’ and emerging market countries’ stock markets. We further divide the emerging markets into two groups as oil-exporting and oil-importing countries. For the oil market, we use both the West Texas Intermediate (WTI) and Brent oil daily price movements. While the Granger-causality-in-mean tests indicate a causal link from WTI oil prices and G7 countries’ stock returns to MSCI emerging countries’ stock returns, the Granger-causality-in-variance tests suggest no causal link from global oil market prices to stock market returns. Nonetheless, a causal link from the G7 countries’ stock returns to the MSCI emerging countries’ stock returns is detected. In addition, G7 countries’ stock market volatility is found to Granger-cause Brent oil price volatility. The time-varying Granger-causality-in-mean and Granger-causality-in-variance tests present new and further insights. A causal relationship between oil price changes and G7 countries’ stock returns is found for some periods during and after the global financial crisis. Time-varying Granger-causality-in-variance test results indicate evidence of causal linkages among oil prices and global stock market returns that are specific only to certain time periods. We also find that there might be a difference between the movements in Brent and WTI oil prices with respect to their Granger-causal effects on oil-importing emerging markets’ stock returns—especially after the global financial crisis. Our results provide further evidence that the effects of oil price movements on stock returns might be different depending on the volatility in the stock markets.
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Ghorbel, Achraf, Mouna Abbes Boujelbene, and Younes Boujelbene. "Behavioral explanation of contagion between oil and stock markets." International Journal of Energy Sector Management 8, no. 1 (April 1, 2014): 121–44. http://dx.doi.org/10.1108/ijesm-09-2012-0007.
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Purpose – This paper aims to investigate empirical evidence of behavioral contagion between oil market, US market and stock markets of oil-importing and oil-exporting countries, during the oil shock and US financial crisis period of 2008-2009, after controlling for fundamentals-driven co-movements. Design/methodology/approach – To examine the volatility spillover among oil market and stock markets, the conditional variance of the trivariate BEKK-GARCH model includes three variables: oil returns, US index returns, and the respective individual market returns of 22 oil-importing and exporting countries. The authors estimate the time-varying correlation coefficients between the prediction error of oil market and each stock index. Also, the authors estimate the time-varying correlation coefficients between the prediction error of US market and each stock index. Findings – The estimation of the trivariate BEKK-GARCH model for VIX, oil market and 23 stock markets of oil-importing and oil-exporting countries suggests the volatility spillover of American investor sentiment to stock market and oil market returns. To capture the pure contagion effects between oil market and stock markets, the authors estimate the forecasting errors of time-varying parameter using the Kalman independently of macroeconomic fundamentals factors. The authors analyze the dynamic correlation between forecasting errors of oil price returns and stock indices returns. The authors show a sharp increase in time-varying correlation coefficients during the oil crisis and US financial crisis period of 2008-2009, which provides strong evidence of herding contagion between oil market and stock markets during the turmoil period. Originality/value – This paper makes an original contribution in identifying the behavioral contagion between oil market, US market and stock markets of oil-importing and exporting countries especially during the oil shock and US financial crisis period of 2008-2009. Specifically, the authors consider investor sentiment and herding bias to explain the volatility transmission between oil and stock market returns.
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Suroso, Arif Imam, Hansen Tandra, Yusman Syaukat, and Mukhamad Najib. "The issue in Indonesian palm oil stock decision making: Sustainable and risk criteria." Decision Science Letters 10, no. 3 (2021): 241–46. http://dx.doi.org/10.5267/j.dsl.2021.4.001.
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The palm oil industry has a strategic role in economic development in Indonesia, especially in alleviating poverty and creating other businesses that can support the industry. Operational activities in the palm oil industry are closely related to environmental issues (deforestation, land-use change, and air pollution) and social conflict. The certification program is an effort for the palm oil industry to implement sustainable development. The certified palm oil industry will increase industrial profitability in the long run to increase investor interest in the future. The decision to choose palm oil industry stocks that carry out sustainable practices and generate maximum returns is an exciting issue, but how investors can choose the right stocks and the minimum risk level. This study aims to apply the decision-making model to choose the optimal stock in the palm oil industry, which involves sustainable certification and risk criteria. The method used in this study was the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) based on the Indonesia Stock Exchange (IDX) data. Determinants of stock selection decisions from previous research are considered criteria for decision making. Through the PROMETHEE method, a list of the rankings of the oil palm industry shares can be generated. The sustainable certification and risk criteria can be used as a reference for relevant stakeholders such as investors. Further studies need to be developed by adding non-financial criteria in the firm and developing the criteria to differentiate each other.
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Bachmeier, Lance J., and Soheil R. Nadimi. "Oil shocks and stock return volatility." Quarterly Review of Economics and Finance 68 (May 2018): 1–9. http://dx.doi.org/10.1016/j.qref.2018.01.001.
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Chen, An-Sing, and Che-Ming Yang. "Oil price thresholds and stock returns." Investment Analysts Journal 48, no. 2 (April 3, 2019): 125–45. http://dx.doi.org/10.1080/10293523.2019.1638078.
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Ready, Robert C. "Oil Prices and the Stock Market*." Review of Finance 22, no. 1 (February 16, 2017): 155–76. http://dx.doi.org/10.1093/rof/rfw071.
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Cheema, Muhammad A., and Frank Scrimgeour. "Oil prices and stock market anomalies." Energy Economics 83 (September 2019): 578–87. http://dx.doi.org/10.1016/j.eneco.2019.08.003.
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Mezghani, Taicir, and Mouna Boujelbène. "The contagion effect between the oil market, and the Islamic and conventional stock markets of the GCC country." International Journal of Islamic and Middle Eastern Finance and Management 11, no. 2 (June 18, 2018): 157–81. http://dx.doi.org/10.1108/imefm-08-2017-0227.
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PurposeThis study aims to investigate the transmission of shock between the oil market and the Islamic and conventional stock markets of the Gulf Cooperation Council (GCC) countries during the oil shocks of 2008 and 2014.Design/methodology/approachThis study uses two models. First, the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic model has been used to capture the fundamental contagion effects between the oil market and the Islamic and conventional stock markets during the tranquil and turmoil-crisis periods of 2008-2014. Second, the filter of Kalman has been used to capture the effects of pure contagion between the oil market and the GCC Islamic and conventional stock markets. The authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices.FindingsThe main findings of this investigation are: first, the estimation of the dynamic conditional correlation– generalized autoregressive conditionally heteroskedastic model for oil market and the Islamic and conventional stock markets proves that the Islamic and conventional stock markets and oil market displayed a significant increase in the dynamic correlation during the turmoil period, from mid-2008 and mid-2014. This proves the existence of contagion between the markets studied. Second, the authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices. They show a strong increase in the correlation coefficients between the oil market and the conventional GCC stock markets, and between the conventional and Islamic GCC stock markets during the oil crisis of 2014. However, there is no change in regime in the figure of the correlation coefficient between the oil market and the GCC Islamic stock markets during the 2008 financial crisis. This pure contagion is mainly attributed to the herding bias in 2014 oil crisis.Originality/valueThis study contributes to identifying the contribution of herding bias on the volatility transmission between the oil markets, and the GCC Islamic and conventional stock market, especially during two controversial shocks: the 2008 oil-price increase and the 2014 oil drop.
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Hamma, Wajdi, Bassem Salhi, Ahmed Ghorbel, and Anis Jarboui. "Conditional dependence structure between oil prices and international stock markets." International Journal of Energy Sector Management 14, no. 2 (July 31, 2019): 439–67. http://dx.doi.org/10.1108/ijesm-04-2019-0010.
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Purpose The purpose of this paper is to analyze the optimal hedging strategy of the oil-stock dependence structure. Design/methodology/approach The methodology consists to model the data over the daily period spanning from January 02, 2002 to May 19, 2016 by a various copula functions to better modeling the dependence between crude oil market and stock markets, and to use dependence coefficients and conditional variance to calculate optimal portfolio weights and optimal hedge ratios, and to suggest the best hedging strategy for oil-stock portfolio. Findings The findings show that the Gumbel copula is the best model for modeling the conditional dependence structure of the oil and stock markets in most cases. They also indicate that the best hedging strategy for oil price by stock market varies considerably over time, but this variation depends on both the index introduced and the model used. However, the conditional copula method with skewed student more effective than the other models to minimize the risk of oil-stock portfolio. Originality/value This research implication can be valuable for portfolio managers and individual investors who seek to make earnings by diversifying their portfolios. The findings of this study provide evidence of the importance of stock assets for making an optimal portfolio consisting of oil in the case of investments in oil and stock markets. This paper attempts to fill the voids in the literature on volatility among oil prices and stock markets in two important areas. First, it uses copulas to investigate the conditional dependence structure of the oil crude and stock markets in the oil exporting and importing countries. Second, it uses the dependence coefficients and conditional variance to calculate dynamic hedge ratios and risk-minimizing optimal portfolio weights for oil–stock.
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Osei, Prince Mensah, and Anokye M. Adam. "Quantifying the Information Flow between Ghana Stock Market Index and Its Constituents Using Transfer Entropy." Mathematical Problems in Engineering 2020 (August 28, 2020): 1–10. http://dx.doi.org/10.1155/2020/6183421.
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We quantify the strength and the directionality of information transfer between the Ghana stock market index and its component stocks as well as observe the same among the individual stocks on the market using transfer entropy. The information flow between the market index and its components and among individual stocks is measured by the effective transfer entropy of the daily logarithm returns generated from the daily market index and stock prices of 32 stocks ranging from 2nd January 2009 to 16th February 2018. We find a bidirectional and unidirectional flow of information between the GSE index and its component stocks, and the stocks dominate the information exchange. Among the individual stocks, SCB is the most active stock in the information exchange as it is the stock that receives the highest amount of information, but the most informative source is EGL (an insurance company) that has the highest net information outflow while the most information sink is PBC that has the highest net information inflow. We further categorize the stocks into 9 stock market sectors and find the insurance sector to be the largest source of information which confirms our earlier findings. Surprisingly, the oil and gas sector is the information sink. Our results confirm the fact that other sectors including oil and gas mitigate their risk exposures through insurance companies and are always expectant of information originating from the insurance sector in relation to regulatory compliance issues. It is our firm conviction that this study would allow stakeholders of the market to make informed buy, sell, or hold decisions.
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Darmawan, Indra, Hermanto Siregar, Dedi Budiman Hakim, and Adler Haymans Manurung. "The Effect of Crude Oil Price Shocks on Indonesia Stock Market Performance." Jurnal Organisasi dan Manajemen 16, no. 1 (June 28, 2020): 11–23. http://dx.doi.org/10.33830/jom.v16i1.785.2020.
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The main purpose of this study is to observe the effects of the crude oil price shocks on Indonesia stock market performance to complete the literature on Indonesia stock market behavior. We examined the effects of the crude oil price shocks on Indonesia stock market performance through the cointegration relationship mechanism between IHSG and the crude oil price and between IHSG and the global stock market indices. The Brent crude oil price data taken from FRED economic data, the Federal Reserve Bank of St.Lois, and the stock market indices data taken from yahoo.finance.com. By using a vector error correction model (VECM) approach, we found that IHSG has significant long-run relationships with the crude oil price and the global stock market indices. This finding indicates that the effects of the crude oil price shocks on IHSG transmitted directly through the cointegration mechanism between IHSG and the crude oil price, and indirectly through the cointegration mechanism between IHSG and the global stock market indices.
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MALIK, MUHAMMAD IRFAN, and ABDUL RASHID. "RETURN AND VOLATILITY SPILLOVER BETWEEN SECTORAL STOCK AND OIL PRICE: EVIDENCE FROM PAKISTAN STOCK EXCHANGE." Annals of Financial Economics 12, no. 02 (June 2017): 1750007. http://dx.doi.org/10.1142/s2010495217500075.
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This paper aims to investigate the return and volatility spillover between world oil prices and the sectoral stock of Pakistan. We estimate a bivariate VAR(1)-AGARCH (1,1) model using weekly data sampled from January 1, 2001 to December 31, 2015. The model results are used to estimate the optimal portfolio weights and hedge ratios. The empirical findings suggest no short-run price transmission between world oil prices and stock sectors of Pakistan Stock Exchange. Only the past unexpected shocks in world oil prices has significant effect on the volatility of sectoral stock returns of Pakistan Stock Exchange, and no volatility spillover exist between world oil price and stock sectors. The optimal portfolio weights and hedge ratios for oil/stock holdings are sensitive to sectors considered. These findings are of great interest for policy makers, hedge fund managers, [Formula: see text] investors and market participants.
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Hanif, Muhammad. "RELATIONSHIP BETWEEN OIL AND STOCK MARKETS: EVIDENCE FROM PAKISTAN STOCK EXCHANGE." International Journal of Energy Economics and Policy 10, no. 5 (August 10, 2020): 150–57. http://dx.doi.org/10.32479/ijeep.9653.
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Hammoudeh, Shawkat, and Huimin Li. "Oil sensitivity and systematic risk in oil-sensitive stock indices." Journal of Economics and Business 57, no. 1 (January 2005): 1–21. http://dx.doi.org/10.1016/j.jeconbus.2004.08.002.
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Belhassine, Olfa, and Amira Ben Bouzid. "Oil price risk in the Eurozone: a sectoral analysis." Problems and Perspectives in Management 15, no. 3 (October 12, 2017): 108–18. http://dx.doi.org/10.21511/ppm.15(3).2017.09.
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This study investigates how oil price movements impact the main Eurozone industry supersectors returns. We use a multifactor market model in which we incorporate oil price changes as an additional risk factor. In order to account for possible breaks in the relationship, we use the Bai and Perron (1998, 2003) breakpoints identification methodology. We find evidence of the presence of structural instabilities on the relationship between sector stock returns and oil price changes. Different breakpoints are identified, particularly the 2003 Iraq invasion year, the 2008 subprime crisis and the 2012 Euro debt crisis. Moreover, our results prove that stock return sensitivities to oil prices are time varying and sector dependent. Besides, the subprime financial crisis appears to induce a significantly positive effect on the oil-stock market nexus. However, the Euro debt crisis has a mostly negative effect. The other identified breakpoints do not seem to have any significant effect on the oil stock market nexus.
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Lu, Xunfa, Kai Liu, Kin Keung Lai, and Hairong Cui. "The Relationship between Crude Oil Futures Market and Chinese/US Stock Index Futures Market Based on Breakpoint Test." Entropy 23, no. 9 (September 6, 2021): 1172. http://dx.doi.org/10.3390/e23091172.
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Combined with the B-P (breakpoint) test and VAR–DCC–GARCH model, the relationship between WTI crude oil futures and S&P 500 index futures or CSI 300 index futures was investigated and compared. The results show that breakpoints exist in the relationship in the mean between WTI crude oil futures market and Chinese stock index futures market or US stock index futures market. The relationship in mean between WTI crude oil futures prices and S&P 500 stock index futures, or CSI 300 stock index futures is weakening. Meanwhile, there is a decreasing dynamic conditional correlation between the WTI crude oil futures market and Chinese stock index futures market or US stock index futures market after the breakpoint in the price series. The Chinese stock index futures are less affected by short-term fluctuations in crude oil futures returns than US stock index futures.
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Djamaluddin, Said, Riki Ardoni, and Aty Herawati. "STOCK PRICE INDEX (CSPI)IN INDONESIA STOCK EXCHANGE (IDX) PERIOD 2014-2018." Dinasti International Journal of Economics, Finance & Accounting 1, no. 1 (March 26, 2020): 40–53. http://dx.doi.org/10.38035/dijefa.v1i1.205.
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This study aims to determine the effect of the BI rate, the dollar exchange rate, the yuan exchange rate, the Dow Jones index, the Shanghai index and world oil prices on the composite stock price index (CSPI). The data used is the period from January 2014 to December 2018 with the multiple regression analysis method. The results showed that the BI rate, Dollar Exchange, Yuan Exchange, Dow Jones, SSE Composite Index and WTI were able to explain the 91.8% effect on CSPI and the remaining 8.2% explained by other variables not examined. T test results show that partially BI interest rates, the yuan and Shanghai exchange rates do not have a significant effect on CSPI. While the dollar exchange rate, Dow Jones Index and world crude oil prices have a significant influence on the composite stock price index (CSPI) with coefficients respectively - 0.41705, +0.21245 and -7.86373. The independent variable that has the most dominant influence on CSPI is Crude Oil (WTI).
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Bastianin, Andrea, and Matteo Manera. "HOW DOES STOCK MARKET VOLATILITY REACT TO OIL PRICE SHOCKS?" Macroeconomic Dynamics 22, no. 3 (January 16, 2017): 666–82. http://dx.doi.org/10.1017/s1365100516000353.
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We study the impact of oil price shocks on the U.S. stock market volatility. We jointly analyze three different structural oil market shocks (i.e., aggregate demand, oil supply, and oil-specific demand shocks) and stock market volatility using a structural vector autoregressive model. Identification is achieved by assuming that the price of crude oil reacts to stock market volatility only with delay. This implies that innovations to the price of crude oil are not strictly exogenous, but predetermined with respect to the stock market. We show that volatility responds significantly to oil price shocks caused by unexpected changes in aggregate and oil-specific demand, whereas the impact of supply-side shocks is negligible.
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Muhtaseb, Buthaina M. A., and Ghazi Al-Assaf. "Oil Price Fluctuations and Their Impact on Stock Market Returns in Jordan: Evidence from an Asymmetric Cointegration Analysis." International Journal of Financial Research 8, no. 1 (December 8, 2016): 172. http://dx.doi.org/10.5430/ijfr.v8n1p172.
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This paper examines whether Amman stock market returns responds asymmetrically to oil price fluctuations for the quarterly period 2000-2015 by applying asymmetric cointegration. Using both TAR and MTAR specification of Enders and Siklos’s (2001) models, and based on the asymmetric ECM, the results provide evidence that stock returns react to oil price variations in an asymmetric manner. In particular, rising oil prices has a larger impact on stock returns; this implies that increases in oil prices have a significant effect on the behavior of stock market in Jordan. The significant relationship between oil prices and stock returns strengthen their predictability power, so that appropriate strategies may be built on the basis of expected increases or decreases in oil prices.