Oil Stock Research Articles

Analisis Pengaruh Harga Minyak Kelapa Sawit (CPO), Inflasi, Kurs Dan Suku Bunga Terhadap Harga Saham (Studi Empiris Pada Perusahaan Crude Palm Oil Di BEI Periode 2017-2021)

The purpose of this study was to analyze how the effect of crude palm oil prices, inflation rates, exchange rates and interest rates on stock prices in oil palm plantation companies listed on the Indonesia Stock Exchange for the period 2017-2021. The results of this study are expected to contribute in addition to researchers, practitioners and investors in helping them to make decisions, whether to sell, buy or hold their shares. The data used is secondary data in the form of annual reports of each issuer and statistical publications from the Indonesia Stock Exchange, Bank Indonesia and IndexMundi from 2017 to 2021. The sampling technique is purposive sampling with certain criteria. A sample of 10 Palm Oil Plantation (CPO) companies listed on the IDX during the observation period 2017-2021 was obtained. The analysis technique used is panel data regression analysis. The hypothesis was tested using t statistics to test the significance of the regression coefficient partially at a significance level of 95%. From the test results, all independent variables, namely palm oil prices, inflation, exchange rates, and interest rates, have an effect on stock prices in palm oil-producing plantation companies listed on the IDX in 2017-2021. Keywords: Palm Oil Prices (CPO), Inflation, Exchange Rates, Interest Rates and Stock Prices

Oil, gold and international stock markets: Extreme spillovers, connectedness and its determinants

This study examines the lower and upper return spillovers and connectedness between important commodity (crude oil and gold) and main international stock markets using the quantile connectedness approach by Ando et al. (2018). The results show stronger return spillovers during bearish and bullish market conditions. Crude oil and gold are net receivers of return spillovers irrespective of quantiles. Furthermore, an intense spillover is observed during high stress periods including COVID-19 in March 2020, and global economic slowdown and the Brexit referendum of 2016, oil price crash in 2014–2016, Tapering Tantrum in 2013, and the subprime crisis of 2008. Moreover, the spillovers in lower quantiles are stronger than in upper quantiles. The volatility uncertainty index (VIX) has a negative impact on the connectedness index at low and median quantiles. Gold and economic policy uncertainty indexes have a positive impact on lower quantile spillovers. In contrast, oil uncertainty index has a negative impact on quantile spillovers. COVID-19 crisis has a positive impact on lower, medium, and upper spillovers.

The Relationship Between Stock Performance and Money Supply Based on VAR Model in the Context of E-commerce

Abstract With the development of network technology, electronic money as a payment and settlement tool based on the network has been developing at an unprecedented speed. Based on the background of e-commerce, this study uses the data from June 2012 to June 2022 to establish a vector autoregressive model to study the interaction between oil prices, stock performance, and money supply. Such a model can not only further our understanding of the complex relationship between these important variables but also shed light on future oil prices. Granger causality test, impulse response function analysis, and variance decomposition analysis have been applied to variables in the model. The main finding is that oil price responds to changes in stock performance and money supply, stock performance is affected by both oil price and money supply, and changes in money supply can be explained by stock performance fluctuations. Such a relationship can help inform traders in e-commerce and investment banking to generate better predictions of future oil prices.

Quantile dependence and portfolio management between oil, gold, silver, and MENA stock markets

The impacts of the global financial crisis (GFC) and the COVID-19 pandemic crisis can be far-reaching, shedding light on the dynamics of dependence between commodity markets (e.g., gold, silver, and Brent) and stock markets. This paper employs a novel quantile-on-quantile regression and the causality-in-quantiles approaches to elicit significant asymmetric dependence between commodity and the stock markets across MENA countries. Our results show that the marginal impact of stock prices on commodity markets varies; the effects are generally negative across quantiles, with all stock markets exerting a greater impact on commodity prices at lower quantiles. Exogenous shocks (e.g., GFC) appear to have imparted greater negative impact on both the dynamic nature of interdependence and the direction of causality, demonstrating investors’ adaptability to uncertainty. For several MENA countries, the hedging ratio shows strong hedging effectiveness for silver and even greater for Brent. The gold appears to lose its shine over hedging effectiveness.

Oil Demand and Stocks

Current data of world oil demand. This includes international bunkers and refinery fuel. Updated on a monthly basis.Current data of oil demand from counties such as Canada, the United States of America, Japan, OECD Europe, Belgium, France, Germany, Italy, Netherlands, Spain, Sweden, the United Kingdom, Australia, Mexico, Republic of Korea, and Turkey. Updated on a monthly basis.Current data for crude oil and refined product stocks in Canada, Chile, Mexico, the United States (Western Hemisphere), France, Germany, Italy, Netherlands, Spain, the United Kingdom and Other Europe (Europe), Japan, Republic of Korea, Other Pacific (Asia‐Pacific), and Total OECD (Table 12.1)Current data for refined product stocks in the OECD Western Hemisphere, OECD Europe, OECD Asia‐Pacific and Total OECD. Products include gasoline, diesel and gasoil, and heavy fuel oil. Updated on a monthly basis (Table 12.2).

Asymmetric dynamic spillover and time-frequency connectedness in the oil-stock nexus under COVID-19 shock: Evidence from African oil importers and exporters

Amid the profound disruptions triggered by COVID-19 in financial markets, this paper investigates changes in the interconnectedness behavior in terms of mean and volatility contagion between crude oil and stock markets in African oil importers and exporters. To this aim, we employ asymmetric BEKK-Copula-GARCH and Wavelet Coherence methods, and the analyses are evaluated before and during COVID-19. The findings indicate that the interdependence between crude oil and African stock returns is relatively weak before COVID-19, but the strength is amplified during the pandemic. Significant volatility spillover from crude oil to stock markets is exhibited in South Africa, Tunisia, and Tanzania during COVID-19. However, the results are insignificant in all the selected African countries before the pandemic. Furthermore, evidence of asymmetric volatility transmission is uncovered in South Africa and Tunisia during COVID-19. The findings also reveal that the connectedness between crude oil and African stocks is time and frequency dependent, with the strong linkage observed in the mid-term and long-term at specific time points. Overall, this study holds vital contributions as it unveils new insights into how COVID-19 reshaped the traditional behavior regarding the oil-stock nexus in Africa, thus informing policy responses and investment strategies at times of extreme events.

The Interpretability of LSTM Models for Predicting Oil Company Stocks: Impact of Correlated Features

Oil companies are among the largest companies in the world whose economic indicators in the global stock market have a great impact on the world economy (Stevens, 2018) and market due to their relation to gold (Aijaz et al., 2016), crude oil (Henriques & Sadorsky, 2008), and the dollar (Huang et al., 1996). This study investigates the impact of correlated features on the interpretability of long short-term memory (LSTM) (Peters, 2001) models for predicting oil company stocks. To achieve this, we designed a standard long short-term memory (LSTM) network and trained it using various correlated data sets. Our approach is aimed at improving the accuracy of stock price prediction by considering the multiple factors affecting the market, such as crude oil prices, gold prices, and the US dollar. The results demonstrate that adding a feature correlated with oil stocks does not improve the interpretability of LSTM models. These findings suggest that while LSTM models may be effective in predicting stock prices, their interpretability may be limited. Caution should be exercised when relying solely on LSTM models for stock price prediction as their lack of interpretability may make it difficult to fully understand the underlying factors driving stock price movements. We have employed complexity analysis to support our argument, considering that financial markets encompass a form of physical complex system (Peters, 2001). One of the fundamental challenges faced in utilizing LSTM models for financial markets lies in interpreting the unexpected feedback dynamics within them.

The Asymmetric Interaction Between Oil Price Change and Stock Returns of the Renewable Energy Companies in India: A Panel NARDL Approach

The Asymmetric Interaction Between Oil Price Change and Stock Returns of the Renewable Energy Companies in India: A Panel NARDL Approach

Global oil price and stock markets in oil exporting and European countries: Evidence during the Covid-19 and the Russia-Ukraine war

The relationship between oil price movements and stock markets during the COVID-19 pandemic and the geopolitical crisis like the ongoing Russian-Ukraine war is yet unexplored extensively. This study therefore examines the return-correlation effects of oil prices on stock markets and their spillover effects in oil-exporting and European countries using daily closing data. After estimating the GARCH process, we employ the static and dynamic Markov Switching model that allow the relationship between oil price and stock market to switch between two regimes coined the COVID-19 and the Russia-Ukraine war periods. The static model shows stock price returns to respond positively and significantly to oil price returns in Italy, Germany and the US during the Covid-19 period while the response is significantly positive only for US in the Russia-Ukraine war period. As regards the volatility spillover, significant spillover is found from stock to oil market for Nigeria, vice versa for Saudi Arabia and bi-directional volatility spillover found for the US, Italy and Germany during the COVID-19 period. The policy implication is that Nigeria and Saudi Arabia should prioritize financial policy and energy policy respectively while US, Italy and Germany should adopt policy coordination to stabilize oil-stock market volatility during low oil price period like the COVID-19 period.

Oil Demand and Stocks

Current data of world oil demand. This includes international bunkers and refinery fuel. Updated on a monthly basis.Current data of oil demand from counties such as Canada, the United States of America, Japan, OECD Europe, Belgium, France, Germany, Italy, Netherlands, Spain, Sweden, the United Kingdom, Australia, Mexico, Republic of Korea, and Turkey. Updated on a monthly basis.Current data for crude oil and refined product stocks in Canada, Chile, Mexico, the United States (Western Hemisphere), France, Germany, Italy, Netherlands, Spain, the United Kingdom and Other Europe (Europe), Japan, Republic of Korea, Other Pacific (Asia‐Pacific), and Total OECD (Table 12.1)Current data for refined product stocks in the OECD Western Hemisphere, OECD Europe, OECD Asia‐Pacific and Total OECD. Products include gasoline, diesel and gasoil, and heavy fuel oil. Updated on a monthly basis (Table 12.2).

Volatility Spillovers in Emerging Markets: Oil Shocks, Energy, Stocks, and Gold

This paper extends the literature on the relationship between oil price shocks and financial markets by examining the effect of supply and demand oil shocks on emerging energy markets, stocks of emerging markets, and gold and exploring the impact of unpredictable oil events on the degree of connectedness among these markets. We show that the effect of supply oil price disturbances drives volatility spillovers in emerging markets with prominent medium- and long-term effects, unlike demand oil price unanticipated changes, particularly during turbulent periods such as the 2008 subprime crisis, the COVID-19 pandemic, and the 2015 oil price crash. These volatility spillover effects are influenced by a marked relationship between supply oil disturbances and emerging energy markets. We also expose that the COVID-19 pandemic volatility spillover consequences in emerging markets are unprecedented compared to the 2008 financial crisis. This can be attributed to the different nature of the related oil price disturbances and financial crises. Overall, the findings highlight the role of crude oil supply shocks as drivers not only of volatility dynamics in energy and equity emerging markets but also of financial connectedness patterns in these economies.

Frequency spillovers between oil shocks and stock markets of top oil-producing and -consuming economies

Motivated by large oil price swings, high economic and geopolitical uncertainties, and the financialization of oil, this paper examines the frequency spillovers and co-movements between oil shocks (risk and demand) and the stock markets of top oil-producer and consumer countries, namely, Canada, China, Russia, Saudi Arabia, and the US. The analysis uses the time-domain spillover index of [1], the frequency-domain spillover of [2]; and the wavelet coherence approach. The findings reveal that spillovers run from the U.S., Canada, and, to a lesser extent, Russia to oil shocks. On the other hand, oil shocks, Saudi Arabia, and China constitute net receivers of shocks. The intensity of spillovers is heavier in the short-term frequency than in the intermediate- and long-term. Furthermore, the direction of spillovers is more defined in the long-term. The U.S. stock market exerts a strong impact on oil risk in general, but the impact is stronger in the short-term. Conversely, an oil demand shock is susceptible to innovations from Canada and Russia that are stronger in the long-term. This means that oil risk shock stemming from innovations in financial markets is short-lived and dissipates quickly due to quick reactions from market participants. On the contrary, long-term links characterize the relationship between oil demand shock and financial markets, mirroring the macroeconomic nature of the linkages. Finally, while the 2008 crisis, EDC, oil price crash, and the COVID-19 pandemic coincided with strong spillovers in the short-term, the COVID-19 era was marked by higher spillovers in the long term. The findings provide important information for investors and policymakers in terms of diversification, risk management, and efforts to mitigate contagion.

A study of oil and gas producers subsector portfolio using the trade-off ranking method

In the topic of stock selection, numerous multi-criteria decision-making (MCDM) techniques have been applied to handle selection difficulties. This paper proposes a compromise approach for the subsector stocks of oil and gas companies, motivated by the pandemic crisis and the political issue in Malaysia. The paper presents a novel analysis of the existing trade-off ranking (TOR) method for ranking the stocks of oil and gas producers in conflicting multi-criteria problems. As a result, the TOR technique ranks the subsector stocks effectively for two criteria weights. Comparison with TOPSIS shows that both methods exhibit similar performance.

Is the Influence of Oil Prices Changes on Oil and Gas Stock Prices in Nigeria Symmetric or Asymmetric?

Is the Influence of Oil Prices Changes on Oil and Gas Stock Prices in Nigeria Symmetric or Asymmetric?

Asymmetric volatility spillovers between Bitcoin, oil, and global stock in economic uncertainty

Asymmetric volatility spillovers between Bitcoin, oil, and global stock in economic uncertainty

Asymmetric volatility spillovers between Bitcoin, oil, and global stocks in economic uncertainty

Asymmetric volatility spillovers between Bitcoin, oil, and global stocks in economic uncertainty

Oil Demand and Stocks

Current data of world oil demand. This includes international bunkers and refinery fuel. Updated on a monthly basis.Current data of oil demand from counties such as Canada, the United States of America, Japan, OECD Europe, Belgium, France, Germany, Italy, Netherlands, Spain, Sweden, the United Kingdom, Australia, Mexico, Republic of Korea, and Turkey. Updated on a monthly basis.Current data for crude oil and refined product stocks in Canada, Chile, Mexico, the United States (Western Hemisphere), France, Germany, Italy, Netherlands, Spain, the United Kingdom and Other Europe (Europe), Japan, Republic of Korea, Other Pacific (Asia‐Pacific), and Total OECD (Table 12.1)Current data for refined product stocks in the OECD Western Hemisphere, OECD Europe, OECD Asia‐Pacific and Total OECD. Products include gasoline, diesel and gasoil, and heavy fuel oil. Updated on a monthly basis (Table 12.2).

Dynamic Relationship Among Crude Oil Price, Stock Price, and Exchange Rates In Indonesia

This study aimed to examine the causal relationship among oil prices, JCI stock prices, and exchange rates in Indonesia. Observational data were from the period 2015M01-2020M06. The research analysis model used was Toda-Yamamoto (1995) causality test. The results showed a two-way causal relationship between exchange rates and oil and a one-way relationship between exchange rates and stocks. There was a one-way effect of stocks on oil. Stock shocks occurred due to the influence of the stocks themselves—only 10 percent of the exchange rates and 0.62 percent of the oil price. Meanwhile, oil prices experienced shocks from stocks of 35.95 percent and exchange rates of 20.87 percent. Changes were found in the exchange rates because stocks were 57.21 percent and oil prices were 11.27 percent. It is recommended to control the exchange rates so that the economy becomes stable, explore oil in the country or use renewable energy technology to break away from dependence on fossil oil, and maintain the value of stocks to be strong and stable.

Gold Price, Oil Price, and Stock Market Return Spillovers: Empirical Evidence from Vietnam

This paper analyzes the spillovers of oil prices, gold prices and stock market returns in Vietnam. By adopting the time-varying parameter vector autoregression model (TVP-VAR), the results show a moderate interdependence among the variables from 2010-2022. Additionally, the relationship between oil prices, gold prices, and stock market returns changes over time and is influenced by economic and political events. Overall, stock market returns are net shock transmitters with the highest volatility among all the variables, while the oil and gold markets are net recipients. Finally, our results remain robust to Vietnam's alternative stock market index.

Corrigendum to ‘Frequency interdependence and portfolio management between gold, oil and sustainability stock markets’ [International Economics 176, December 2023, 100461]

Corrigendum to ‘Frequency interdependence and portfolio management between gold, oil and sustainability stock markets’ [International Economics 176, December 2023, 100461]