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.     

An empirical research of crude oil price changes and stock market in China: evidence from the structural breaks and quantile regression

This article investigates the relationship between real crude oil price changes and the Chinese real stock market at the industry level. Our study uses monthly data over the period 1994:03 to 2013:12. Based on input–output (IO) tables, this article will explore more details for the driving factors of sensitivity to oil price changes. We divide these driving factors into cost- and demand-side dependence. Empirical results reveal that sensitivity varies across different industries and periods based on structural breaks and asymmetric effects of oil price changes. Furthermore, some industries seemingly not directly affected by oil are sensitive to the real oil price changes. Finally, using a penalized quantile regression for panel data, we find that these two factors significantly affect lower, but not upper, quantile of sensitivity.     

Oil prices and UK industry-level stock returns

In this article, we study whether the behaviour of oil prices can be used as a reliable predictor for the disaggregated industry-level stock market indices. We find strong evidence for the relevance of changes in oil price as a predictor for the returns of UK industry portfolios, while this relevance is heterogeneous across industries. In an out-of-sample framework, we find that both the contemporaneous and lagged oil price changes do predict UK industry stock market returns. The predictive power is more transient for the latter case, and mostly appearing after allowing for time variation in the relative performance. In addition, we find some evidence of asymmetry in the oil–stock price relationships.     

Exchange Rates and Stock Prices in the MENA Countries: What Role for Oil?

This paper considers the linkage between stock prices and exchange rates in four MENA (Middle East and North Africa) emerging markets. In contrast to the existing evidence that uses a global market index to uncover such a relationship it is found that for the sample countries oil prices emerge as the dominant factor in the above relationship. The paper considers the presence of regime shifts and evidence is found of cointegration only for the period following the 1999 oil price shock. Readjustment towards equilibrium in each stock market occurs via oil price changes. Finally, a number of robustness checks are performed and persistence profiles produced.     

Market efficiency in the Spanish derivatives markets: An empirical analysis

This paper analyzes Granger caUSAlity between daily prices of the Spanish stock index (Ibex 35) and its futures contract using Johansen cointegration methodology. The study differentiates between short-run and long-run caUSAlity. The empirical results prove that, in the short run, the futures price causes the spot price. However, the opposite is not true. On the other hand, long-run caUSAlity is embodied in the response of futures prices after deviations from the long-run equilibrium. These results say that during the period of study, the Spanish futures market behaved as an efficient market.     

A股市场上的“中石油魔咒”现象及其解释

文章针对A股市场上流传甚广的"中石油魔咒"现象,首次从基本面角度进行了解释,认为造成这一现象的根本原因是国际原油价格对我国股票市场存在显著的负向溢出效应,即当国际原油价格上涨时,对中石油个股产生利好,但对整体宏观经济却构成利空,因而中石油股票价格上涨,整个股票市场却会下跌。进一步研究还发现,这种负向溢出效应具有非线性特征,表现为国际原油价格上涨对股票市场的打压力度要大于其下跌对股票市场的提升力度。这提醒A股投资者相对于国际原油价格下跌,要更加关注国际原油价格上涨带来的投资风险。     

The comovement between exchange rates and stock prices in the Asian emerging markets

This study investigates the comovement between exchange rates and stock prices in the Asian emerging markets. The sample covers major institutional changes, such as market liberalization and financial crises, so as to examine how the short-term and long-term relations change after such events. The autoregressive distributed lag (ARDL) model proposed by Pesaran et al. (2001) is adopted, which allows us to deal with structural breaks easily, and to handle data that have integrals of different orders. Interest rates and foreign reserves are also included in the analysis to reduce potential omitted variable bias. My empirical results suggest that the comovement between exchange rates and stock prices becomes stronger during crisis periods, consistent with contagion or spillover between asset prices, when compared with tranquil periods. Furthermore, most of the spillovers during crisis periods can be attributed to the channel running from stock price shocks to the exchange rate, suggesting that governments should stimulate economic growth and stock markets to attract capital inflow, thereby preventing a currency crisis. However, the industry causality analysis shows the comovement is not stronger for export-oriented industries for all periods, such as industrials and technology industries, thus implying that comovement between exchange rates and stock prices in the Asian emerging markets is generally driven by capital account balance rather than that of trade.     

Revisiting the shock and volatility transmissions among GCC stock and oil markets: A further investigation

The paper explores the empirical evidence of the volatility interactions among the Gulf Cooperation Council (GCC) stock markets and world oil price over the weekly period spanning from June 24, 2005 to March 25, 2011. The study is conducted based on the BEKK-GARCH process developed by Kroner and Ng (1998) and outlining the asymmetry in the conditional variances of the stock and oil markets. The findings show evidence of shock and volatility linkages among GCC stock and oil markets, and reveal that the spillover effects are more apparent for volatility patterns. They also indicate that the stock and oil markets exhibit asymmetry in the conditional variances. From the perspective of portfolio strategies, the results display certain sensitivity to the GCC stock prices, allowing thus better understanding of the relationship between each stock market and oil price. Our findings are crucial for practitioners, policy makers and investors who seek to make earnings by diversifying their portfolios.     

Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach

Crude oil price behaviour has fluctuated wildly since 1973 which has a major impact on key macroeconomic variables. Although the relationship between stock market returns and oil price changes has been scrutinized excessively in the literature, the possibility of predicting future stock market returns using oil prices has attracted less attention. This paper investigates the ability of oil prices to predict S&P 500 price index returns with the use of other macroeconomic and financial variables. Including all the potential variables in a forecasting model may result in an over-fitted model. So instead, dynamic model averaging (DMA) and dynamic model selection (DMS) are applied to utilize their ability of allowing the best forecasting model to change over time while parameters are also allowed to change. The empirical evidence shows that applying the DMA/DMS approach leads to significant improvements in forecasting performance in comparison to other forecasting methodologies and the performance of these models are better when oil prices are included within predictors.     

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.     

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.     

Exploring the influence of industries and randomness in stock prices

This study explores the behavior of time series of historical prices and makes two additional contributions to the literature. In summarized form, we present an overview of each of the financial theories that discuss the movements of stock prices and their connection with industry trends. Within this theoretical framework, we first propose that prices be distinguished by following stock prices and a random-walk approach, and second, that the analysis of historical prices be broken down by industries. Similarities among price series are extracted through a clustering methodology based on an approach to non-computable Kolmogorov complexity. We model price series by following geometric Brownian motion and compare them to historical series of stock prices. Our first contribution confirms the existence of hidden common patterns in time series of historical prices that are clearly distinguishable from simulated series. The second contribution claims strong connections among firms carrying out similar industrial activities. The results confirm that stock prices belonging to the same industry behave similarly, whereas they behave differently from those of firms in other industries. Our research sheds new light on the stylized feature of the non-randomness of stock prices by pointing at fundamental aspects related to the industry as partial explanatory factors behind price movements.     

Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach

In this paper, we re-examine the relationship between oil price and stock prices in oil exporting and oil importing countries in the following distinct ways. First, we account for possible nonlinearities in the relationship in order to quantify the asymmetric response of stock prices of these two categories to positive and negative oil price changes. Secondly, in order to capture within group differences, we allow for heterogeneity effect in the cross-sections by formulating a nonlinear Panel ARDL model which is the panel data representation of the Shin et al. (2014) model and also analogous to the non-stationary heterogenous panel data model. Thirdly, we evaluate the relative predictability of the linear (symmetric) and nonlinear (asymmetric) Panel ARDL models using the Campbell and Thompson (2008) test. Our results depict that stock prices of both oil exporting and oil importing groups respond asymmetrically to changes in oil price although the response is stronger in the latter than the former. This finding is further corroborated by the out-of-sample forecast results suggesting that the inclusion of positive and negative oil price changes in the predictive model for stock prices will produce better forecast results only for the oil importing countries. Our results are robust to different oil price proxies, lag structure and in-sample periods. Overall, the dichotomy between oil exporting and oil importing countries has implications on oil price-stock nexus.     

Asymmetric determinants of CDS spreads: U.S. industry-level evidence through the NARDL approach

This paper investigates the presence of asymmetries in the short- and long-run relationships between the 5-year CDS index spreads at the U.S. industry level and a set of major macroeconomic and financial variables, namely the corresponding industry stock indices, the VIX index, the 5-year Treasury bond yield and the crude oil price, using the NARDL approach. The empirical results provide significant evidence of both short-run and long-run asymmetries in the linkage between ten industry CDS spreads and the potential driving factors common for all industries, confirming the importance of asymmetric nonlinearity in this context. It is also shown that the industry equity prices, the VIX, the 5-year Treasury bond rate and, to a lesser extent, the crude oil price constitute important asymmetric determinants of these U.S. industry CDS spreads. The findings of this study have relevant implications for investors, speculators, arbitrageurs and policy makers interested in credit risk at the industry level.     

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.     

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.     

Nonlinear effects of oil shocks on stock returns: a Markov-switching approach

Using Markov-switching models, we investigate whether oil price shocks have nonlinear effects on stock returns. Empirical evidence from a set of international stock indexes suggests that an increase in oil prices has a negative and significant impact on stock prices in one state of the economy, whereas this effect is significantly dampened in another state of the economy. Furthermore, it is shown that changes in oil prices or in oil price volatility do not lead to a higher probability of switching between regimes.     

Interest risk and default risk: A conditional volatility study

The aim of this work is to measure the risk-price sensitivity to interest rate changes in the Spanish market and to see if sensitivity is lower with public debt. To contrast this hypothesis, this study presents a model that analyzes the sensitivity of the risky prices before variations in interest rates through duration and convexity, with the purpose of explaining the price of risky bonds. The main advantages of the analysis are the possibility to determine the sensibility of the risky prices before variations of risk-free interest rates in the Spanish market and the construction of a conditional volatility model that overcomes the linearity models of constant variance.     

Have food and financial markets integrated?

This article analyses comovements and discusses possibly greater market integration between aggregate food commodity and stock prices in the period 1990 to 2012. Return correlations, price return distributions, cointegration and Granger-causalities are tested in subsamples on monthly FAO Food Price Index and MSCI World Stock Market Index. Empirical results suggest that while there is only weak indication of greater comovements concurrent with structural changes such as changed agricultural policies, new demand due to growth in emerging markets and energy mandates and the financialization of food markets since the early 2000s, they did start to increase substantially in particular during the financial stress of the Lehman crisis and the Great Recession. While structural changes may have amplified price linkages across markets, results do not suggest that they are the key factors for greater price comovements. Instead, the effects of the late-2000s recession as a time of great economic weakness and uncertainty may have changed concurrently the behaviour of both food and financial market participants, such that different market prices exhibit large comovements.     

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.