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.     

The relationship between developed equity markets and the Pacific Basin's emerging equity markets

Using a trivariate vector autoregression (VAR) model with a proper control for heteroscedasticity, this paper investigates the relationships between the two largest equity markets in the world—the U.S. and Japan—and the four Asian emerging equity markets: Hong Kong, Korea, Singapore, and Taiwan. Evidence indicates that the links between the developed markets and the Asian emerging markets (AEMs) began to increase after the stock market crash in October 1987, and have significantly intensified since the outbreak of the Asian financial crisis in July 1997.     

Assessing the impacts of oil price fluctuations on stock returns in emerging markets

This paper investigates the effects of oil price shocks on stock market returns in emerging countries. It differs from previous works in three main aspects: i) we distinguish three groups of countries, the largest net-oil importing countries, the moderately oil-dependent countries, and the largest net-oil exporting countries; ii) The potential influence of bullish and bearish market conditions on the causal relationship between oil and stock returns is controlled for in our analysis; iii) The empirical investigation is based on an analysis of long-term correlation and a conditional multifactor pricing model. Using data from twenty-five emerging countries, our results suggest that oil price risk is significantly priced in emerging markets, and that the oil impact is asymmetric with respect to market phases.     

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.     

Exogenous shocks,dynamic correlations,and portfolio risk management for the Asian emerging and other global developed and emerging stock markets

ABSTRACT

This study examines the potential influence of exogenous shocks on time-varying correlations and portfolio strategies between the Asian emerging and other global stock markets including developed and other emerging markets. Using the ARMA-cDCC-FIEGARCH model with and without exogenous shocks, our results highlight the usefulness of including other global stock assets in the traditional portfolio for Asian emerging market investors. However, investors have limited opportunities to diversify their assets during the global financial crisis. Moreover, the shocks from the U.S. stock market have a greater influence on global stock markets compared to that from U.S. economic policy. Fortunately, the model with exogenous shocks improves its accuracy, which plays the same role of controlling structural breaks in the model. More importantly, incorporating exogenous shocks in our model also provides better value-at-risk performance results and hedging effectiveness. These results have several important implications for investors, researchers, and policymakers.     

考虑价格因素的原油进口多元化路径研究

价格风险是我国原油进口面临的主要风险之一,通过构建我国原油进口的价格-风险模型,量化研究了我国原油进口来源国的最优风险结构。结论显示,中东地区依然是我国最重要的原油进口来源地,进口更多来自政治稳定地区的原油,可以有效地分散我国原油的供应风险。从长期来看,我国需要积极拓展更多的石油供应渠道,进一步提高从阿联酋、美国、澳大利亚、加拿大、哈萨克斯坦、埃及以及卡塔尔的进口量,保证我国的原油进口安全。     

Investment coordinates in the context of housing and stock markets nexus

This study examines the causal relationship between Chinese housing market (HM) and stock market (SM), using the bootstrap Granger full-sample causality test and subsample rolling-window estimation test. The results show that stock price (SP) has both positive and negative impacts on housing price (HP) in several sub-periods, and HP has the same effects on SP. The substitution effect drives their adverse consequences. Meanwhile, the positive effect indicates that SP has a wealth effect on HP, and HP has a credit-price effect on SP. Results provide information to Chinese financial institutions and individual investors for constructing investment portfolios within these asset markets.     

Trade openness and the informational efficiency of emerging stock markets

This paper examines the empirical link between trade openness and the informational efficiency of stock markets in 23 developing countries. Our fixed effects panel regression results document a significant negative relation between trade openness and stock return autocorrelations only when the de facto measure is used. On this basis, we argue that a greater level of de facto trade openness is associated with a higher degree of informational efficiency in these emerging stock markets because the former signals higher future firm profitability, and investors tend to react faster to information when there is less uncertainty about a firm's future earnings or cash flows. Further analyses find no significant association between the extent of financial openness and the degree of informational efficiency.     

Covariance breakdowns and connectedness of crude oil futures markets with non-synchronous data

ABSTRACT

This article identifies the breakdowns in the covariance of three benchmark crude oil futures markets (WTI, Brent and Dubai) and investigates the changes of market connectedness across the breakdown periods. As the crude oil futures are traded in different regions, this article eliminates the non-synchronous trading data by employing the Vector Moving Average structure and the Bayesian data augmentation approach, which keeps the integrity of original data without changing its properties. The results show that there are significant breaks in the covariance structure of crude oil futures markets. The breakdown periods are consistent with the periods when the market volatilities are at high level and the returns are volatile. The changes of market connectedness are independent of the covariance states, which supports the globalization hypothesis for the crude oil market. The results also suggest that there is more information flow out of the WTI than to the WTI during the sample period, particularly during the breakdown periods in 2008–2009.     

The heterogeneous dependence between global crude oil and Chinese commodity futures markets: evidence from quantile regression

This paper explores the dependence between global crude oil and Chinese commodity futures markets across different quantiles of the return distributions. Based on weekly data from 11 June 2004 to 7 July 2017, we address this issue by applying a quantile regression method. This technique provides a more detailed investigation of the dependence. Moreover, considering the structural breaks caused by market turmoil or financial crises, we divide the full period of every commodity sector market into sub-periods based on these break dates to further explore the dependence changes. The empirical results indicate that the dependence between global crude oil and Chinese commodity futures markets is different across quantiles in different commodity sectors. The dependence is significantly positive, except in markets with high expected returns. Additionally, the effects caused by structural breaks are distinctly heterogeneous across quantiles. The effect of the same break on the degree of dependence exhibits an increasing tendency as the quantile level increases, which suggests that markets with high expected returns are more susceptible to crises. Finally, we apply a prediction analysis to further verify the heterogeneity of the commodity sectors, which may be the cause of the heterogeneous dependence.     

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.     

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.     

Jumps in the convenience yield of crude oil

The potential presence of jumps and time-varying volatility in convenience yields can lead to abnormally fat tails, which has implications for investment in storage capacity, leasing and drilling for crude oil. In this paper we evaluate the potential for these features in convenience yields. To that end, we analyze the rate of change in convenience yields for five futures prices time horizons (1, 3-, 6-, 9- and 12-month ahead), allowing for the both jumps and time-varying volatility. We find that both features exert a statistically important effect on convenience yields, for each of the five time horizons. We also calculate the implied probability that at least one jump would occur on any date, which reveals a period of relative calm at the start of the fracking boom, when large stockpiles built up at the trading hub for West Texas Intermediate, and a period of considerable churn, after the ban on exporting crude oil was lifted. Both elements underscore a linkage between inventory holdings and convenience yields.     

Industry-level determinants of the linkage between credit and stock markets

This paper examines the relationship between US credit default swaps (CDS) and stock returns on an industry-wide basis across a number of investment horizons, with particular focus on the major determinants of such a relationship. Wavelet analysis is first applied to extract the CDS–stock wavelet correlation for each US industry. Then, Bayesian Model Averaging is employed to identify the key driving factors of the industry CDS–stock wavelet correlations at short- and long-term horizons. The empirical results indicate that the wavelet correlations between the industry CDS and stock returns are primarily negative over time and across time scales. Moreover, the CDS–stock correlation at longer horizons exhibits a much more stable pattern than its counterpart at shorter time frames. The results also demonstrate that the volatility of US Treasury and stock markets, as measured by the MOVE and VIX indices, respectively, the volatility of volatility, as captured by the VVIX index, and US economic policy uncertainty, as measured by the EPU index, are the most robust determinants of the correlation between CDS and stock returns at shorter and longer horizons for most US industries. In contrast, the Fama–French systematic equity factors exhibit a practically negligible explanatory power on the CDS–stock link.     

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.     

Country and industry factors in tests of Capital Asset Pricing Models for partially integrated emerging markets

Existing literature has produced broadly inconclusive evidence about the asset pricing model which best fits partially integrated markets. This paper examines whether industry and country factors are independent factors helping to determine returns in emerging stock markets, or are derived from the stocks’ risk-return characteristics. We link the country-industry decomposition framework to the local and the Global CAPM in a new and more direct way. The results show that country factors are additional independent sources of cross-sectional variation in stock returns before 1996 particularly under the Global CAPM. After 1996, the results suggest partial integration: industry and country factors are both additional independent determinants of cross-sectional variations in stock returns. .     

Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops

This study elucidates plausible correlation between crude oil and agricultural commodities. We assess whether the conditional correlation of crude oil with energy crops (e.g., corn and soybeans) is different from that of food crops (e.g., oats and wheat). We find a stronger correlation of about 20 percent between returns of crude oil and energy crops. However, the correlation coefficient value for oil-oats and oil-wheat is as low as eight percent. We add to the literature by exploring correlation in a dynamic context using three different GARCH models and found that conditional correlation between crude oil and energy corps is relatively high. In order to reduce risk associated with crude oil price fluctuations, this study also examined hedging possibilities against crude oil by investment in agricultural commodities. Although hedging effectiveness is low with all underlying agricultural commodities, soybeans provide relatively better hedging possibilities compared to other agricultural crops.     

Interaction between oil and US dollar exchange rate: nonlinear causality,time-varying influence and structural breaks in volatility

This article examines the nonlinear Granger causality and time-varying influence between crude oil prices and the US dollar (USD) exchange rate using the Hiemstra and Jones (HP) test, the Diks and Panchenko (DP) test and the time-varying parameter structural vector autoregression model. By applying the iterated cumulative sums of squares (ICSS) algorithm and the DCC-GARCH model, the effects of structural breaks in volatility of the two markets are also investigated. The empirical analysis indicates that, first, crude oil prices are the nonlinear Granger-cause of the USD exchange rate, but not vice versa. Second, the USD exchange rate exerts a stronger and more stable negative influence on crude oil prices in the short term, and the influence gradually weakens after 2012. Finally, ignoring structural breaks can increase the negative volatility correlation between the oil and USD exchange rate markets, which is particularly remarkable during the financial crisis.     

Testing the efficiency of the futures market for crude oil in the presence of a structural break

The efficiency of the futures market for crude oil has been the subject of significant study, with the basis regression representing a popular methodology. However, the parameters of this model are subject to a structural break, casting doubt on any conclusion regarding the efficiency of the futures market. To address this problem, this article employs a simple generalization which is capable of testing the efficiency of a futures market in the presence of a structural break. Using this approach, strong evidence of inefficiency is found in the one month futures contract for West Texas Intermediate for the period between 1985 and 2013, which is otherwise not detected.     

The effectiveness of index futures hedging in emerging markets during the crisis period of 2008-2010: Evidence from South Africa

This article provides an assessment of the comparative effectiveness of four econometric methods in estimating the optimal hedge ratio in an emerging equity market, particularly the South African equity and futures markets. The article bases the effectiveness of hedging on volatility reduction and minimization of the coefficient of variation of hedged returns as well as risk-aversion-based utility maximization. The empirical analysis shows that the vector error-correction method and multivariate generalized autoregressive conditional heteroscedasticity methods are most effective over relatively long horizon, weekly and monthly hedging periods.