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.     

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.     

The impact of news,oil prices,and global market developments on Russian financial markets1

This paper analyses the impact of news, oil prices, and international financial market developments on daily returns on Russian bond and stock markets. First, regarding returns, energy news affects returns, while news from the war in Chechnya is not significant. Market volatility does not appear to be sensitive to either type of news. Second, a significant effect of the growth in oil prices on Russian stock returns is detected. Third, the international influence on Russian financial markets depends upon the degree of financial liberalization. The higher the degree of financial liberalization, the stronger is the impact of US stock returns on Russian financial markets. In addition, banking reform and interest rate liberalization efforts seem to dictate the globalization of Russian stock markets, while it is the progress in liberalizing securities markets and non‐bank financial institutions that matters more for the globalization of Russian bond markets.     

Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test

This study examines whether a volatility/risk transmission exists between the Dow Jones Islamic stock and three conventional stock markets for the United States, Europe and Asia during the pre- and the in- and post-2008 crisis periods. It also explores the volatility spillover dynamics between those markets and US Monetary policy, oil prices, global financial risk and uncertainty factors. The recently developed Hafner and Herwartz (2006)’s causality-in-variance test provides evidence of risk transfers between these seemingly different equity markets, indicating a contagion between them during the full sample and the subperiods. The volatility structure of these markets is dominated by short-run volatility in the first period and by high long-run volatility in the second period. The volatility impulse response analysis indicates a similar volatility transmission pattern although it is characterized by a more volatile and short-lived structure in the second period. It also appears that the Islamic equity market responds to shocks from the risk factors and not from the oil price and the US economic policy uncertainty index during both periods.     

Housing prices,stock prices and the US economy

This paper studies the relationship between housing prices, stock prices, interest rates and aggregate output in the US using monthly data from 1993 to 2014. Evidence from causality tests and a variance decomposition procedure suggest that stock prices have a much larger effect on aggregate output in the US economy than do either housing prices or interest rates. Instead, the wealth effect created by changes in stock prices has a relatively large impact on US aggregate output. Separate estimations and variance decompositions for the sample periods 1993–2001, 2002–2008 and 2009–2014 show that the impact of housing prices relative to stock prices has been waning over time.     

On the Effects of Asset Purchase Programs on Emerging Stock Markets

ABSTRACT

It is well documented that there has been a relationship between stock markets and unconventional monetary policies. However, most research concentrates on developed economies and analyzes the effects of shocks from such polices on stock prices. This paper is different from this research in that we investigate the impact of surprises from the Fed’s and the ECB’s announcements on the stock returns and volatility in Gulf Cooperation Council (GCC) countries using GARCH models. We find that a positive surprise associated with a fall in the U.S. Treasury yield causes an increase in ADX returns. We show significant effects of the ECB’s shocks on price returns. In particular, announcement that induces a decline in yield spreads in Italian sovereign bonds leads to higher stock prices. We also document a significant impact of surprises both by the Fed and ECB on volatility. However, the estimates are mixed. We note that volatility went down in response to the ECB’s policies, while they increased after the Fed’s asset purchases. Finally, when we distinguish surprises by their sign, the GJR-GARCH model estimates indicate that the effect on the volatility which is, perhaps surprisingly, symmetric for both types of news.     

On the influence of US monetary policy on crude oil price volatility

Forecasting oil prices is not straightforward, such that it is convenient to build a confidence interval around the forecasted prices. To this end, the principal ingredient for obtaining a reliable crude oil confidence interval is its volatility. Moreover, accurate crude oil volatility estimation has fundamental implications in terms of risk management, asset pricing and portfolio handling. Generally, current studies consider volatility models based on lagged crude oil price realizations and, at most, one additional macroeconomic variable as crude oil determinant. This paper aims to fill this gap, jointly considering not only traditional crude oil driving forces, such as the aggregate demand and oil supply, but also the monetary policy rate. Thus, this work aims to contribute to the debate concerning the potential impact of (lagged) US monetary policy as well as the other crude oil future price (COFP) determinants on daily COFP volatility. By means of the recently proposed generalized autoregressive conditional heteroskedasticity mixed data sampling model, different proxies of the US monetary policy alongside US industrial production (proxy of the US aggregate demand) and oil supply are included in the COFP volatility equation. Strong evidence that an expansionary (restrictive) variation in monetary policy anticipates a positive (negative) variation in COFP volatility is found. We also find that a negative (positive) variation of industrial production increases (decreases) COFP volatility. This means that volatility behaves counter-cyclically, according to the literature. Furthermore, the out-of-sample forecasting procedure shows that including these additional macroeconomic variables generally improves the forecasting performance.     

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.     

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.     

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.     

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.     

The effect of quantitative easing on stock prices: a structural time series approach

A structural time series model is estimated and tested to examine the effect of quantitative easing (QE) on US stock prices. The model is estimated by maximum likelihood in a Time-varying parametric (TVP) framework, using the S&P 500 index as the dependent variable and the Fed’s balance as an explanatory variable in addition to the unobserved components accounting for the behaviour of variables that do not appear explicitly in the equation. The results show that QE had a sizeable, but not exclusive, effect on stock prices and that stock prices were also affected by other missing variables and cyclical movements. Several explanations are presented for the rise of the US stock market in the post-QE period, particularly since the election of Donald Trump.     

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.     

Hedging and diversification across commodity assets

ABSTRACT

We investigate the conditional cross effects and volatility spillover between equity markets and commodity markets (oil and gold), Fama and French HML and SMB factors, volatility index (VIX) and bonds using different multivariate GARCH specifications considering the potential asymmetry and persistence behaviours. We analyse the dynamic conditional correlation between the US equity market and a set of commodity prices and risk factors to forecast the transmission of shock to the equity market firstly, and to determine and compare the optimal hedge ratios from the different models based on the hedging effectiveness of each model. Our findings suggest that all models confirm the significant returns and volatility spillovers. More importantly, we find that GO-GARCH is the best-fit model for modelling the joint dynamics of different financial variables. The results of the current study have implications for investors: (i) the equity market displays inverted dynamics with the volatility index suggesting strong evidence of diversification benefit; (ii) of the hedging assets gold appears the best hedge for the US equity market as it has a higher hedge effectiveness than oil and bonds over time; and (iii) despite these important results, a better hedge may be obtained by using well-selected firm sized and profitability-based portfolios.     

OIL PRICE SHOCKS AND STOCK MARKET BOOMS IN AN OIL EXPORTING COUNTRY

This paper analyses the effects of oil price shocks on stock returns in Norway, an oil-exporting country, highlighting the transmission channels of oil prices for macroeconomic behaviour. To capture the interaction between the different variables, stock returns are incorporated into a structural VAR model. I find that following a 10% increase in oil prices, stock returns increase by 2.5%, after which the effect gradually dies out. The results are robust to different (linear and non-linear) transformations of oil prices. The effects on the other variables are more modest. However, all variables indicate that the Norwegian economy responds to higher oil prices by increasing aggregate wealth and demand. The results also emphasize the role of other shocks; monetary policy shocks in particular, as important driving forces behind stock price variability in the short term.     

The macroeconomic effects of fiscal policy

We investigate the macroeconomic effects of fiscal policy using a Bayesian Structural Vector Autoregression (B-SVAR) approach. We identify fiscal policy shocks via a partial identification scheme, but also: (i) include the feedback from government debt; (ii) look at the impact on the composition of output; (iii) assess the effects on asset markets; (iv) use quarterly data; and (v) analyse empirical evidence from the US, the UK, Germany and Italy. The results show that government spending shocks, in general, have a small effect on Gross Domestic Product (GDP); lead to important ‘crowding-out’ effects; have a varied impact on housing prices and generate a quick fall in stock prices. Government revenue shocks generate a mixed effect on housing prices and a small and positive effect on stock prices. The empirical evidence also suggests that it is important to explicitly consider the government debt dynamics in the model.     

The impact of foreign macroeconomic news on financial markets in the Czech Republic, Hungary, and Poland

In this paper, we investigate the effects of euro area and US macroeconomic news on financial markets in the Czech Republic, Hungary, and Poland (CEEC-3) from 1999 to 2006. Using a GARCH model, we examine the impact of news on daily returns of 3-month interest rates, stock market indices, exchange rates versus the euro, and the US dollar. First, both US and European macroeconomic news has a significant impact on CEEC-3 financial markets. Second, the process of European integration is accompanied by an increasing importance of euro area news relative to US news. Third, there are country-specific differences: for example, the Czech stock market is relatively more affected by foreign news since the Copenhagen Summit in December 2002. In general, our results support the hypothesis of a deepening euro area influence on the CEEC-3 over time and a corresponding reduction in the relative importance of US shocks.     

国际石油价格与通货膨胀的溢出效应及动态相关性

国际石油价格大幅波动不可避免地给全球经济带来了一定程度的冲击和影响。文章采用向量自回归、多元GARCH-BEKK和DCC-GARCH模型对中美两国通货膨胀与国际石油价格之间的均值溢出效应、波动溢出效应及动态相关关系进行了实证检验。检验结果表明,国际石油价格与中国通货膨胀不存在任何方向的均值和波动溢出效应,美国通货膨胀与国际油价则存在双向显著的均值和波动溢出效应;中国通货膨胀与国际油价的动态相关关系显著弱于美国,不易受到国际油价的冲击和影响。从整体上看,当前中国通货膨胀与国际石油价格的关联性并不显著,但随着我国石油消费对进口依赖程度的不断提高,石油安全问题在可预见的未来将成为中国需要应对的一个现实挑战。因此,相关部门应及早采取有效措施,应对未来石油冲击对宏观经济的影响。     

Time–frequency relationship between US output with commodity and asset prices

Commodity and asset prices have a well-documented effect on economic growth as manifested through various channels. At the same time, the business cycle influences the commodity and asset prices. Whereas empirical evidence on the effect of commodity and asset prices on the long-run economic growth is ambiguous, most of the previous researches highlight a positive correlation in the short run. The aim of this article is to disentangle the short- and long-run co-movements between US historical business cycles and commodity and asset prices over the period 1859–2013. For this purpose, we use a time–frequency approach and we test the historical influence of oil, gold, housing and stock prices over the output growth. In contrast to other studies, we control for the effect of other prices and monetary conditions, using the wavelet partial coherency. In line with the previous works, we discover that co-movements between economic growth and commodity and assets prices manifest especially in the short run. We also find that stock returns and housing prices have a more powerful effect on the US economic growth rate than the oil and gold prices. The long-run co-movements are documented especially around the World War II. Finally, when controlling for the influence of the interest rate, inflation and other commodity and asset prices, co-movements become weaker in the short run. In general, the oil and housing prices lead the GDP growth, the US output leads the gold prices, while there is no clear causality direction between business cycle and stock prices.