Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models

Using a time-varying GJR copula approach, we determine the conditional dependence of the GCC stock indices on oil price between 2007 and 2016. We show how to improve the forecasting accuracy of the co-movement of energy and stock prices in an equally weighted portfolio. Contrary to prior findings, we demonstrate that due to the different co-movements across the GCC stock indices, portfolios of oil assets and several GCC stocks are less likely to be affected by systemic risk. The different co-movements across several stock indices over time provide different entry and exit points for stock investors. This approach is in line with the ‘buy low/sell high’ adage.     

Are Oil Price News Headlines Statistically and Economically Significant for Investors?

While much has been written about the effects of oil price on stock returns, surprisingly nothing is known about the effect of oil price news on stock returns. This article is a response to this research gap. For a large number of stocks on the New York Stock Exchange, the authors find that while oil price news does predict market returns it only predicts returns of some sectors and not all. They find that sorting stocks based on oil price news generates a significant return differential in the cross-section, which holds consistently across a range of models allowing for the well-known risk factors. Their findings suggest that information contained in oil price news affects stock returns.     

Asset pricing and institutional investors with disagreements

We develop a dynamic asset pricing model with two institutional investors who have benchmark incentives and who disagree about the underlying economy. We derive semi-closed form expressions for all equilibrium quantities. We find that the benchmark stock price increases and the non-benchmark stock price decreases with the benchmark incentives. Furthermore, each stock price decreases with its own disagreement and increases with the other stock disagreement. We also show that there is a positive relationship between the co-movement of the stocks and the benchmark incentives, but that this co-movement is negative with the disagreements, owing to the endogenous risk-sharing mechanisms. Moreover, we find that, when one stock disagreement increases, the optimistic institutional investor always takes positions on this stock by shorting the other stock and the bond in order to hedge against the risk of market changes, in line with the pessimistic investor's beliefs.     

Revisiting global economic activity and crude oil prices: A wavelet analysis

Based on the wavelet analysis approach, this paper firstly examines the dynamic relationship between global economic activity (proxied by the Kilian economic index) and crude oil prices in both time- and frequency-domains. Our empirical results demonstrate significant correlation between crude oil prices and global economic activity at high frequencies (in the short run) during the entire sample period; however, the co-movement between the two at low frequencies (in the long run) is weaker and exists only during certain proportions of the sample period. We also document evidence that global economic activity and oil price are positively correlated, with dynamic lead-lag relationships across time. Our findings are robust to alternative choices of oil price indexes and controlling for other confounding factors such as geopolitical risk, armed conflicts, economic policy uncertainty and equity market uncertainty. The current study provides valuable implications for oil market investors based on the information of global economic situation and its dynamic relationships with oil prices.     

Oil price risk in the Spanish stock market: An industry perspective

This study examines the sensitivity of the Spanish stock market at the industry level to movements in oil prices over the period 1993–2010, paying special attention to the presence of endogenously determined structural changes in the relationship between oil price changes and industry equity returns. The empirical results show that the degree of oil price exposure of Spanish industries is rather limited, although significant differences are found across industries. The oil price sensitivity is very weak in the 1990s, a period of fairly stable and low oil prices. Instead, the link between crude oil and stock prices seems to have increased during the 2000s, becoming primarily positive. This evidence highlights the key role played by aggregate demand-side oil price shocks associated with the global real economic activity in the link between oil price fluctuations and the Spanish stock market.     

Analyzing time–frequency relationship between interest rate,stock price and exchange rate through continuous wavelet

In this study we investigate and identify the patterns of co-movement of interest rate, stock price and exchange rate in India in the period between July 1997 and December 2010 using the cross-wavelet power, the cross-wavelet coherency, and the phase difference methodologies. Our empirical findings suggest that stock prices, exchange rates and interest rates are linked. The cross wavelet results show that stock price movements are lagging both to the exchange rate and interest rate fluctuations. The interest rate lead over the stock price movements is even clearer, especially after 2006, and it suggests that the stock market follows the interest rate signals. Comparing results of WTC and XWT, we find very clear results of phase difference of lead–lag relationship between stock prices, exchange rates and interest rates.     

New Evidence of Psychological Barrier from the Oil Market

The authors examine how stock returns were affected when the oil price reached the psychological barrier of US$100 per barrel for the first time in history. Using an event study approach, 4 key results emerge. First, the authors show that a psychological barrier event in the oil market does affect stock returns. Second, they show that a psychological barrier event in the oil market is a source of return drift—a phenomenon well explained and understood with respect to nonoil news events. Third, the psychological barrier affects small/medium-sized stocks and not large stocks. Last, the authors show that successful trading strategies can be devised based on the information that the oil price psychological barrier significantly impacts the market and that it contributes to return drift.     

Crude oil and BRICS stock markets under extreme shocks: New evidence

In this paper, we propose an extreme Granger causality analysis model to uncover the causal links between crude oil and BRICS stock markets. Instead of analyzing the average causal relationship, as is usually done, we first decompose the data into three cumulative components and investigate the causality between different combinations of extreme positive, extreme negative and normal shocks. These types of combinations can describe all facets of the interactions between crude oil and BRICS stock markets, especially under extreme shocks. In contrast to the results obtained by the traditional Granger causality test, our empirical findings demonstrate that the effect of oil price changes on the stock markets is stronger under extreme circumstances than under normal circumstances. Furthermore, large upward or downward oil price changes have an asymmetric impact on extreme upward or downward stock price changes. Finally, robustness checks verify the rationality and validity of the extreme Granger causality analysis.     

Time-frequency dynamics of return spillover from crude oil to agricultural commodities

ABSTRACT

We explore return spillover from crude oil to ethanol, corn, soybean and wheat on daily data during 17 May 2005–27 June 2018. This study is unique in capturing the time-frequency dynamics of return spillover. We use the frequency-dependent spillover measure that jointly captures information from time and frequency domain. We also identify two endogenous break dates that segregate the study period in three sub-periods. Our results indicate that return spillover from crude oil to ethanol, major feed stocks (i.e. corn and soybean) and food crop (i.e. wheat) is pronounced only in lower frequency band or long-term (more than 1 month). We find that return spillover is stronger only during 2005–2010, i.e. the period of energy and food crisis.     

Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries

While the relationship between oil prices and stock markets is of great interest to economists, previous studies do not differentiate oil-exporting countries from oil-importing countries when they investigate the effects of oil price shocks on stock market returns. In this paper, we address this limitation using a structural VAR analysis. Our main findings can be summarized as follows: First, the magnitude, duration, and even direction of response by stock market in a country to oil price shocks highly depend on whether the country is a net importer or exporter in the world oil market, and whether changes in oil price are driven by supply or aggregate demand. Second, the relative contribution of each type of oil price shocks depends on the level of importance of oil to national economy, as well as the net position in oil market and the driving forces of oil price changes. Third, the effects of aggregate demand uncertainty on stock markets in oil-exporting countries are much stronger and more persistent than in oil-importing countries. Finally, positive aggregate and precautionary demand shocks are shown to result in a higher degree of co-movement among the stock markets in oil-exporting countries, but not among those in oil-importing countries.     

Impact of oil prices on firm stock return: industry-wise analysis

The study investigates the impact of oil prices on firm-level stock returns in case of Pakistan over the period 1998–2014, as this relationship is neglected by the previous literature. By using the panel data estimation, the results of full sample indicate significant positive effect of oil price changes on firm stock returns in the same period, whereas the lagged oil price changes have significant negative effect on firms’ stock return. Moreover, the industry-level analysis also confirms the similar findings; results indicate significant positive impact of oil price on firms’ stock return in full sample, textile, chemical and miscellaneous industry, while the lagged oil price changes negatively affect the stock returns of full sample and all the industries except tobacco, jute and vanaspati industries. The study confirms that rise in oil price transfers a positive signal in the stock market that boosts the firm-level stock returns in Pakistan. In contrast to the negative shocks, the stock returns are significantly affected by the positive oil price shocks.     

Dynamic relationships between crude oil prices and socially responsible investing in Brazil: evidence for linear and non-linear causality

Recent years have witnessed an increasing interest in socially responsible investing (SRI), reflecting investors’ growing awareness of social, environmental, ethical and corporate governance issues. At the same time, the effect of oil price shocks on stock price returns has become a prominent issue due to surges in energy prices. Using the Brazilian corporate sustainability index (ISE) as a benchmark for socially responsible investments in the Brazilian stock market, the present study extends the understandings on the impact of oil prices on stock price behaviour, focusing on a new class of assets: those from socially responsible firms. To this end, apart from conventional linear causality approaches, we apply a nonparametric test by Diks and Panchenko (DP) on daily data spanning from January 2008 to December 2015 to test for non-linear causality, before and after controlling for conditional heteroscedasticity. Our findings show that, in spite of their efforts to become more socially responsible, firms that have adhered to the ISE in recent years are influenced by crude oil spot prices, especially the WTI crude. In line with previous studies, we also provide consistent evidence that the Brazilian stock market, as a whole, is associated with the international crude oil market.     

TERRORISM AND THE RETURNS TO OIL

The effect of terrorism on global oil prices has been largely explained through demand-side effects. We estimate an empirical model to re-examine the effect of terrorism on the price of global oil stocks across oil market regimes that reflect different supply constraints. We believe that terrorism will have larger impacts when global capacity is tight (i.e. when global demand is close to global supply). This means that any shock to capacity (say by conflict) should have the largest impact on profits before the first OPEC shock in the early 1970s. Since then, conflict shocks would not allow firms to exploit production in the same way, thus reducing the available profits that could be garnered by such production manipulation. If capacity constraints are binding when a conflict occurs, then we predict that a positive stock price reaction can be expected for oil firms from such a shock. We exploit a new panel dataset to investigate the relationship between oil profitability and conflict, using conflict data from the top 20 oil producing and exporting countries in the world. We show that in the later part of our sample, 1974–2005, as cartel behavior of OPEC member countries has diminished and as conflict has become more regular and thus the information surrounding it noisier, oil stock prices do not increase in response to conflict. However, in earlier capacity constrained eras, we find that oil stocks can in fact increase in response to conflict. In some cases, the impact of conflict may cause the return of oil stocks to increase by as much as 10 percentage points.     

Long-run waves or short-run fluctuations – what establishes the correlation between oil and food prices?

The strong correlation between food prices and energy prices has gained much attention in the public debate. In this article, we focus on the so-called excess co-movement, which is the correlation between crude oil price and the prices of food commodities after controlling for economic activity. We use a frequency domain Granger causality test to analyse short-run and long-run relationships between crude oil prices and prices of food commodities. For important biofuel inputs like maize, soybeans, rapeseed and EU sugar, we find evidence for long-run Granger causality in particular for the period after 2007. This supports the hypothesis that the increasing biofuel production creates the link between the prices of crude oil and food commodities. However, we also find short-run Granger causality for various food commodities. This result is more in line with herd behaviour or speculation in commodity markets.     

T+1 trading mechanism causes negative overnight return

The T+1 trading mechanism is unique in the Chinese stock market, thus providing a natural experimental field to study the trading mechanism and price behaviors. This paper proposes and proves that T+1 trading mechanism causes negative overnight return, the overnight return can serve as a proxy of the T+1 trading mechanism. The paper finds that the overnight return of the Chinese stock market is significantly negative, whereas those under the T+0 trading mechanism, such as China’s stock index futures, Hong Kong stocks, and major international indices, all have around 0 or positive overnight returns. T+1 trading mechanism has greater impacts on stocks with more divergent investor opinions, higher risk, more individual investor percentages, higher arbitrage restrictions, and less liquidity. The T+1 trading mechanism distorts the price generation mechanism of stocks. The paper contributes to the understanding of impact of trading mechanism on stock prices.     

Oil Price Shocks and Volatility in Australian Stock Returns

This paper examines the effect of oil shocks on return and volatility in the sectors of Australian stock market and finds significant effects for most sectors. For the overall market index, an increase in oil price return significantly reduces return, and an increase in oil price return volatility significantly reduces volatility. An advantage of looking at sector returns rather than a general index of stock returns is that sectors may well differ markedly in how they respond to oil price shocks. The energy and material sectors (as expected) and the financial sector (surprisingly) are out of step (in different ways) with results for the other sectors and for the overall index. A rise in oil price increases returns in the energy and material sectors and an increase in oil price return volatility increases stock return volatility in the financial sector. Explanation for the negative (positive) association between oil return (oil return volatility) and returns (volatility of returns) in the financial sector must be based on the association via lending to and/or holdings of corporate bonds issued by firms with significant exposure to oil price fluctuations and their speculative positions in oil‐related instruments.     

Interpreting the movement of oil prices: Driven by fundamentals or bubbles?

Based on the historical data of crude oil, diesel and gasoline markets during November 2001–December 2015, this paper employs the state-space model and log-periodic power law (LPPL) model to explore the dynamic bubbles of oil prices and predict their crash time. The results indicate that, first, oil price bubbles only exist during November 2001–July 2008, and crude oil and diesel prices are significantly driven by bubbles, whereas gasoline prices are mainly driven by fundamentals. Second, the state-space model captures the time-varying bubbles of crude oil and diesel prices. Finally, the LPPL model well predicts the crash time of bubbles.     

EFFECT OF OIL PRICES ON STOCK MARKETS: EVIDENCE FROM NEW GENERATION OF STAR MODEL

This paper aims to introduce an evidence of new generations of smooth transition regression model (STAR). It proposes two different forms of STAR model. First: a time varying STAR model (TVSTAR), which identify the estimated coefficients at each point of time. Second: a full specification STAR model (FSSTAR) which provides a consistent estimate even in the existence of some measurement errors, omitted variables and even if the true functional form is unknown. This study will consider the two proposed models and the traditional STAR model to examine the nonlinear relation between oil price and stock market index for two countries (Egypt and Turkey). Our results confirm the existing of a non‐linear relation between oil prices and stock return for both countries. The suggested models gives more accurate information about the time varying effect of oil price changes on stock markets and robust forecasts.     

A bubble identification mechanism: Evidence from the Chinese stock market

This paper provides a bubble date-stamping mechanism using the agent-based computational finance method. The key steps of the bubble date-stamping mechanism are the construction of the simulated financial market, the computation of the characteristic indexes, and the thresholds of the Price Band in the simulated financial market. The present study adopts the mechanism to identify the bubbles of sample stocks in the Chinese stock market from April 2003 to December 2019. The findings show that the bubbles are primarily distributed in 2006–2008, 2009–2012 and 2014–2018, respectively. Furthermore, we analyse the bubble strength and the price fluctuation during the above three periods. In addition to the bubble date-stamping mechanism, the paper also studies the factors that drive the bubbles in the Chinese stock market from both macro and micro perspectives.     

Relationships among U.S. oil prices and oil industry equity indices

The cointegration analysis suggests that the pure oil industry equity system and the mixed oil price/equity index system offers more opportunities for long-run portfolio diversification and less market integration than the pure oil price systems. On a daily basis, in the oil price systems all oil prices with the exception of the 3-month futures can explain the future movements of each other. In the mixed system, none of the daily oil industry stock indices can explain the daily future movements of the New York Mercantile Exchange (NYMEX) futures prices, whereas these prices can explain the movements of independent companies engaged in exploration, refining, and marketing. The spillover analysis of oil volatility transmission suggests that the oil futures market has a matching or echoing volatility effect on the stocks of some oil sectors and a volatility-dampening effect on the stocks of others. The policy implication is that, during times of high oil volatility, traders should choose the S&P oil sector stocks that match their tolerance for volatility and use the right financial derivative to hedge against or profit from this volatility. The day effect for volatility transmission suggests that Friday has a calming effect on the volatility of oil stocks in general. The effect for Monday is not significant.