The effect of oil prices on stock prices: fresh evidence from asymmetric causality tests

This article investigates the causal impact of oil prices on stock prices in each G7 market as well as in the world market. An asymmetric causality test developed by Hatemi-J is used for this purpose. Since the underlying data appears to be non-normal with time-varying volatility, we use bootstrap simulations with leverage adjustments in order to produce more reliable critical values than the asymptotic ones. Based on symmetric causality tests, we find no causal effect of oil prices on the stock prices of the world market or any of the G7 countries. However, when we apply an asymmetric causality test, we find that increasing oil prices cause stock prices to rise in the world, the U.S. and Japan while decreasing oil prices cause stock prices to fall in Germany. This may imply that the world, the U.S. and Japanese stock markets consider increases in oil prices as an indicator of good news as this may mean that there is an increase in oil demand due to an expected growth in the economy while the German stock market treats decreasing oil prices as a signal of an expected contraction in the economy.     

Firm return volatility and economic gains: The role of oil prices

In this paper we investigate whether the oil price contributes to stock return volatility for 560 firms listed on the NYSE. Using daily data, we find that the oil price is a significant determinant and predictor of firm return variance. We devise trading strategies based on forecasts of firm return variance using the oil prices and historical averages. We find that investors can make substantial gains in returns by using the oil price in forecasting firm return variances.     

Conditional correlations in the returns on oil companies stock prices and their determinants

The identification of the forces that drive stock returns and the dynamics of their associated volatilities is a major concern in empirical economics and finance. This analysis is extremely important for determining optimal hedging strategies. This paper investigates the stock prices’ returns and their financial risk factors for several integrated oil companies, namely Bp (BP), Chevron-Texaco (CVX), Eni (ENI), Exxon-Mobil (XOM), Royal Dutch (RD) and Total-Fina Elf (TFE). We measure the actual co-risk in stock returns and their determinants “within” and “between” the different oil companies, using multivariate cointegration techniques in modelling the conditional mean, as well as multivariate GARCH models for the conditional variances. The distinguishing features of this paper are: (i) focus on the determinants of the market value of each company using the cointegrated VAR/VECM methodology; (ii) specification of the conditional variances of VECM residuals with the Constant Conditional Correlation (CCC) multivariate GARCH model of Bollerslev [(1990) Review of Economics and Statistics 72:498–505] and the Dynamic Conditional Correlation (DCC) multivariate GARCH model of Engle [(2002) Journal of Business and Economic Statistics 20:339–350]; (iii) discussion of the performance of optimal hedge ratios calculated with the DCC estimates. The “within” and “between” DCC indicate time-varying interdependence between stock return volatilities and their determinants. Moreover, DCC models are shown to produce more accurate hedging strategies.     

Oil price and automobile stock return co-movement: A wavelet coherence analysis

This paper explores possible co-movement between oil price and automobile stock return in a joint time-frequency domain. Daily price series from August 01, 1996 to June 20, 2017 is used in this analysis. The results indicate that the co-movement between oil price and automobile stock return is strong during November, 2000–December, 2002 and March, 2006–December, 2009. The co-movement is found to be more pronounced in the long-term and stock return is sensitive to the higher oil price emanating from the demand shock. This contravenes the conventional wisdom that crude oil is always counter-cyclical to the automobile stocks. For investor, this weakens the probable gain from including oil asset in a portfolio of automobile stocks as crude oil does not offer cushion against bearish automobile stock markets during the crisis period.     

A change in the time-varying correlation between oil prices and the stock market

We investigate the time-varying correlation between oil prices and stock prices. Estimation results from a multivariate DCC-GARCH model reveal that the correlation has changed since the financial crisis. Historically, the correlation has been close to zero or slightly negative. However, the correlation changed to positive during the Great Recession and continued to be positive through the first half of 2017. We investigate the role quantitative easing played in this change in correlation using a threshold model.     

Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience

This paper examines whether American banks' exposure to the oil industry could lead to instability in both oil and financial markets. To address this issue, we investigate volatility spillovers between oil prices and the stock prices of the four major American banks involved in the oil industry by employing the vector autoregressive fractionally integrated moving average framework. We use high-frequency data from January 3, 2006, to June 30, 2016. Our results support the existence of such volatility spillovers, as evidenced by the significant volatility responses of oil price (banks' stock price) to a shock in banks' stock price (oil price). These responses, more pronounced following the banks' exposure to the shale industry, mainly reflect the financial fragility of shale companies and their high indebtedness levels. Thus, this paper emphasises how the shale oil industry could trigger turmoil in both oil and financial markets.     

Natural gas prices and stock prices: Evidence from EU-15 countries

This study investigates the long-run relationship between natural gas prices and stock prices by using the Johansen and Juselius cointegration test and error–correction based Granger causality models for the EU-15 countries. We employ quarterly data covering the period from 1990:1 to 2008:1. Empirical findings suggest that there is a unique long-term equilibrium relationship between natural gas prices, industrial production and stock prices in Austria, Denmark, Finland, Germany and Luxembourg. However, no relationship is found between these variables in the other ten EU-15 countries. Although we detect a significant long-run relationship between stock prices and natural gas prices, Granger causality test results imply an indirect Granger causal relationship between these two variables. In addition, we investigate the Granger causal relationship between stock returns, industrial production growth and natural gas price increase for Austria, Denmark, Finland, Germany and Luxembourg. As a result, increase in natural gas prices seem to impact industrial production growth at the first place. In turn, industrial production growth appears to affect stock returns.     

The cross-section and time-series effects of individual stock sentiment on stock prices

In this article, we construct an individual stock sentiment index by using the principal component analysis method. We empirically study the cross-section and time-series effects of investor sentiment on the stock prices based on the panel data model with dummy variable. The results indicate that individual stock sentiment has greater impact on small-firm stock prices than big-firm stock prices, which presents obvious cross-section effect. Moreover, individual stock sentiment leads to much sharper ?uctuations of stock prices in the stock market downturn than in the stock market expansion, which shows obvious time-series effect. Specifically, the individual stock sentiment has the greatest impact on small-firm stock prices under the stock market downturn, exerting significant dual asymmetric effect. Our results are helpful to understanding the micro-mechanism of sentiment effect.     

Impact of state-dependent oil price on US stock returns using local projections

In this paper, we investigate the impact of oil prices on both aggregate and industry US real stock returns over the period 1973–2017. The empirical analysis contributes to the related literature introducing a state-dependent oil price (high and low) and the local projections approach. Our main finding is that, depending on the nature of the shock and industry, the negative effects of oil price shocks become exacerbated -and the positive effects get moderated- if oil prices are already high.     

Return and volatility transmission between world oil prices and stock markets of the GCC countries

This paper investigates the return links and volatility transmission between oil and stock markets in the Gulf Cooperation Council (GCC) countries over the period 2005-2010. We employ a recent generalized VAR-GARCH approach which allows for transmissions in return and volatility. In addition, we analyze the optimal weights and hedge ratios for oil-stock portfolio holdings. On the whole, our results point to the existence of substantial return and volatility spillovers between world oil prices and GCC stock markets, and appear to be crucial for international portfolio management in the presence of oil price risk.     

Intraday stock prices, volume, and duration: a nonparametric conditional density analysis

We investigate the distribution of high-frequency price changes, conditional on trading volume and duration between trades, on four stocks traded on the New York Stock Exchange. The conditional probabilities are estimated nonparametrically using local polynomial regression methods. We find substantial skewness in the distribution of price changes, with the direction of skewness dependent on the sign of trade. We also find that the probability of larger price changes increases with volume, but only for trades that occur with longer durations. The distribution of price changes vary with duration primarily when volume is high.     

The effect of Airbnb announcements on hotel stock prices

The sharing economy model that was developed in the last decade has a major effect on a different aspect of life. The purpose of this research is to test the effect of a sharing economy product on its competitors. Specifically, this study used the event study approach to examine how Airbnb announcements affected hotel stock prices. To accomplish this goal, we used 180 Airbnb announcements to investigate the general effect of Airbnb, and the effects according to the type of announcement and the type of audience. The findings indicate that general Airbnb announcements have a negative effect on the hotel stock prices. In addition, investors respond negatively to positive announcements but not to neutral ones. Finally, announcements targeting young people have no effect on the stock prices of hotel companies, while the effect of announcements targeting families lasts the longest. We also explored investment strategies for general investors and those with inside information. We suggest that general investors short sell the stock on the day of the news announcement. Investors with inside information should short sell the stock a few days before the day of the news announcement. In both cases, investors should close their positions a few days later depending on the type of announcement.     

Currency exposures of the oil and natural gas stock prices in the Hushen-300 stock market： A nonlinear model approach

The paper embarks to investigate the relationship between currency risk and stock prices of the oil and natural gas exploitation industry in the value-weighted Hushen-300 stock market, by applying the standard Capital Asset Pricing Model （CAPM） and nonlinear exchange rate exposure model to the Renminbi against US dollar. The results show that the currency exposure does vary in the oil-gas stock prices throughout the bull and bear market. The study suggests that the models of the equilibrium exchange rate exposure must be extended to considering the nonlinear exchange rate exposure, the regime periods of bull and bear market, and the industry types that is sensitive to the currency exposures. The nonlinear dynamic relationship between the exchange rate changes and the Chinese energy stock prices throughout the bull and bear market add to the recent empirical evidences that foreign exchange markets and stock markets are closely correlated.     

The behaviour of Hong Kong stock prices

The primary function of a stock market is to allocate resources to the most profitable investment opportunities. If stock prices provide accurate signals for resource allocation, firms are able to make correct production–investment decisions, and investors are able to choose the most suitable stocks for investment. These choices are only possible if the market is efficient, that is, if stock prices ‘fully reflect’ all available information.

Hong Kong is now an international financial centre. Although Hong Kong's stock market is ranked as one of the five largest in the world in terms of turnover, little research has been devoted to the behaviour of its stock prices. This is a study of the efficiency of Hong Kong's stock market. It is based upon two widely accepted statistical tests, namely, serial correlation analysis and runs tests. Data used cover the daily prices of 28 major Hong Kong stocks over a period of four years from 1977 to 1980. The evidence is mixed; it does not provide clear support for the efficient market hypothesis.     

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.     

Inflation volatility and stock prices: Evidence from ARCH effects

This paper examines the impact of inflation uncertainty on stock prices in developed as well as in emerging capital markets over the period 1980:1–93:12 via an Autoregressive Conditional Heteroskedasticity (ARCH) model for inflation. The results seem to support the presence of a negative association between inflation uncertainty and stock prices.The authors would like to thank, without implicating, Gikas Hardouvelis, Costas Karfakis, and especially the discussant of the conference session held in Williasmsburg, Robert C. Winder, for helpful comments and suggestions.     

Oil prices and stock returns: nonlinear links across sectors

We present evidence of an asymmetric relationship between oil prices and stock returns. The two regime multivariate Markov switching vector autoregressive (MSVAR) model allow us to capture the state shifts in the relationship between regional stock markets and sectors. Results suggest that oil price risk is significantly priced in the sample used. The impact is asymmetric with respect to market phases, and regimes have been associated with world economic, social and political events. Our study also suggests asymmetric responses of sector stock returns to oil price changes and different transmission impacts depending on the sector analyzed. There is a high causality from oil to sectors like Industrials and Oil & Gas. Companies inside the Utilities sector were more able to hedge against oil price increases between 2007 and 2012. Historical crisis events between 1992–1998 and 2003–2007 do not seem to have affected the relationship between oil and sector stock returns, given the higher probability of remaining smoother. For all sectors there seems to be a turn back to stability from 2012 onwards. Finally, investors gain more through portfolio diversification benefits built across, rather than within sectors.     

The impact of oil prices on trade

This paper introduces an oil price–distance interaction variable in a gravity equation to explain how global trade behaves as a result of oil price changes. The findings are that as oil prices increase, international trade becomes more localized in that countries begin trading relatively more with their neighbors. In contrast, when they decrease, trade becomes more dispersed in that the distance between countries becomes less relevant. These results are highly significant across specifications, and the magnitude is not to be ignored. According to the full specification an oil price halving will make trade more dispersed by relatively increasing trade by 40% for a distance of 10,000 miles and by 25% for a distance of 1,000 miles.