Financialization of agricultural commodities: Evidence from China

Speculation in the commodity futures market distorts commodity prices, driving them away from rational levels. This phenomenon, which is known as the financialization of commodities, has raised significant concerns in recent years. Particularly, in the agricultural market, ‘financialized’ commodities have been blamed for high world food prices. In this paper, we examine the financialization of agricultural commodities in China. To do so, a time-varying copula is employed to investigate the dependence structure between commodities and stock markets. Four insightful results are obtained. First, positive correlations between agricultural commodities and stock markets demonstrate the financialization of agricultural commodities. Second, the identified correlations are time-varying and idiosyncratic with respect to products. Third, the agricultural commodity market is more closely correlated with the domestic stock market than with the overseas market. Fourth, a growing dependence between commodities and the stock markets is detected and the co-movement became stronger after the global financial crisis.     

Financialization of food. Modelling the time-varying relation between agricultural prices and stock market dynamics

This article studies the correlation of agricultural prices with stock market dynamics. We discuss the possible role of financial and macroeconomic factors in driving this time-varying relation, with the aim of understanding what caused positive correlation between agricultural commodities and stocks in recent years. While previous works on commodity-equity correlation have focused on broad commodity indices, we study 16 agricultural prices, in order to assess patterns that are specific to agricultural commodities but also differences across markets. We show that an explanation based on a combination of financialization and financial crisis is consistent with the empirical evidence in most markets, while global demand factors don’t appear to play a significant role. The correlation between agricultural prices and stock market returns tends to increase during periods of financial turmoil. The impact of financial turmoil on the correlation gets stronger as the share of financial investors in agricultural derivatives markets rises. Our findings suggest that the influence of financial shocks on agricultural prices should decrease as global financial tensions settle down but also that, as long as agricultural markets are ‘financialized’, it might rise again when it is less needed, i.e. in the presence of new financial turmoil.     

Should emerging market investors buy commodities?

One reason that investors hold commodities is to receive diversification benefits. However, while an extensive set of existing studies demonstrate diversification benefits when investors hold international stocks or bonds, they are generally silent on the implications of holding commodities. Using an asset pricing framework, we investigate the benefits to investors from holding commodities, both individually and in portfolios. Generally, commodity and stock markets are integrated, although there are time-varying benefits to investors that are subject to sample period selection and investment horizon. We show that Asian investors receive positive risk adjusted returns in gold and rice markets but not in any of the other commodity markets investigated. The risk adjusted returns are time-varying: during the Asian financial crisis risk adjusted returns were negative – a penalty for investing in commodities – whereas during the global financial crisis the reverse was true and investors earned positive excess returns. The time-varying nature of the benefits that arise from diversification in commodities and their breakdown during periods of crisis, highlight the problems that investors may face when using commodities for long-term investment in addition to traditional holdings of stocks and bonds.     

Financialization and commodity prices – an empirical analysis for coffee,cotton, wheat and oil

Commodity prices have crucial implications for developing countries. The question whether the financialization of commodity derivative markets has contributed to high and volatile commodity prices has been controversially debated. Building on limitations in the empirical literature, we estimate a multivariate Vector Autoregressive (VAR) model to assess the effect of different groups of financial investors (index investors and money managers) as well as fundamental and macroeconomic variables on the prices of coffee, cotton, wheat and oil. We find that, in contrast to index investors, money managers’ net long positions have a large statistically significant effect on commodity prices. This calls for policy interventions as commodity derivative markets may cease to perform their fundamental developmental roles.     

On the dynamic effects of global commodities on stock market blocks in Africa

This article explores the commodity–equity links in the Africa markets by distinguishing between short- to long-run co-movements driven by market shocks. Using the value-weighted average method, available Africa’s stock markets are aggregated into four market blocks. Global oil and gold returns are used as proxies for commodities. Coherency between pairs of markets is examined with the use of continuous Morlet wavelet transform. Results reveal abstemiously high degree of co-movements between the commodity–equity markets in the short- to medium-term frequencies with nonhomogenous lead–lag nexuses, signifying greater benefits of diversification in the long-term. These findings provide investors with relevant strategies for hedging.     

Global and Extreme Dependence Between Investor Sentiment and Stock Returns in European Markets

The authors investigate the global and extreme dependence structure between investor sentiment and stock returns in 7 European stock markets (Belgium, France, Germany, Greece, the Netherlands, Portugal, and the UK), over the period 1985–2015. Global dependence refers to the correlation of changes in sentiment and stock returns over the whole range of these 2 variables, and extreme dependence refers to the local correlation of high (i.e. asymptotic) changes in sentiment and high stock returns. Using copula models and a bootstrap procedure, 6 statistical tests are performed for this purpose. Among the results of the tests, the authors highlight those that provide evidence of contemporaneous lower extreme dependence and contemporaneous upper extreme independence between sentiment and returns. As policy implications, these results suggest that financial stability can be promoted if regulators consider the impact of their decisions on investor sentiment. Also, the results seem to support the arguments in favor of short selling ban during turmoil periods. Finally, overall, the results are relevant for both investors and regulators and reinforce the importance of considering investor sentiment to better understand the behavior of financial markets.     

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.     

DYNAMICS BETWEEN NORTH AMERICAN AND EUROPEAN AGRICULTURAL FUTURES PRICES DURING TURMOIL AND FINANCIALIZATION

North American and European agricultural futures markets faced significant changes in recent years, i.e., the financialization which originated in the USA, the increase of futures trading in Europe and the recent price turmoils in international commodity markets. We analyse the long‐ and short‐run dynamics between North American and European agricultural futures prices during these institutional changes. The empirical results show that the US markets lead in terms of price transmissions and volatility spillovers. US markets, however, predominantly react to deviations from the long‐run equilibrium which indicates a rising impact of European agricultural markets on a global scale.     

How are gold returns related to stock or bond returns in the U.S. market? Evidence from the past 10-year gold market

Although the gold market over the past decade has been soaring relative to its prior history, there have been few studies on the relationship between the gold market and other major financial markets based on the past decade of data. To re-investigate how the gold market interacts with the stock market and the bond market, we re-visit economic and financial characteristics of gold using the past 10-year data in terms of co-integration, causality, predictive power, and extreme returns. We find that while gold returns are not co-integrated with stock returns and bond returns, gold returns have a unidirectional causality with both of them. Also, we discover that gold returns have some predictive power on subsequent short-term stock returns. Under extreme market scenarios, it turns out that gold returns tend to deteriorate more simultaneously with bond returns than stock returns. This means that gold can better serve as a safe haven for stock in a relative sense during temporary market downturns.     

Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis

This paper examines the short term and long term dependencies between stock market returns for the Gulf Cooperation Council (GCC) Countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) during the period 2005–2010. Our empirical investigation is based on the wavelet squared coherence which allows us to assess the co-movement in both time-frequency spaces. Our results reveal frequent changes in the pattern of the co-movements especially after 2007 for all the selected GCC markets at relatively higher frequencies. We further note an increasing strength of dependence among the GCC stock markets during the last financial crisis signifying enhanced portfolio benefits for investors in the short term relative to the long term. On the financial side, we uncover that the strength of co-movement between GCC markets may impact the multi-country portfolio's value at risk (VaR) levels. These findings provide potential implications for portfolio managers operating in the GCC region who are invited to consider co-movement through both frequencies and time when designing their portfolios.     

Asymmetric spillover effects between the Shanghai and Hong Kong stock markets: evidence from quantile lagged regression

This article surveys the asymmetric spillover effects between the mainland China-based Shanghai Composite Index (SCI) and the Hong Kong based Hang Seng Index (HSI) using a quantile lagged regression model. Compared to previous studies, this article, based on data before and after the 2008 global financial crisis, presents a more detailed analysis, as we investigate the spillovers in terms of returns, volatilities and exchange rates between the renminbi (RMB) and the Hong Kong dollar (HKD) throughout the entire conditional return distribution, including the central quantiles, which are closely related to the normal circumstances, and the extreme quantiles, which correspond to the bear and bull markets. First, we find that the return spillovers from its lagged returns or from the other index not only vary across time but also depend on stock state. Second, while return volatility may boost the stock market in a bull market, it accelerates the decline in a bear market. Third, the depreciation of the RMB relative to the HKD does not significantly affect current returns for the HSI, while it negatively affects current returns for the SCI in a bad state after the crisis. The findings presented in this article will facilitate investors’ understanding of the two stock markets.     

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.     

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997–98 and 2008–09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992–June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time‐varying co‐volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.     

Bull or bear markets: A wavelet dynamic correlation perspective

In this paper, we contribute to the literature on the international stock market co-movements and contagion, especially during the recent subprime crisis, by researching the interconnections between international stock markets in time-frequency domain.Our innovative approach consists on carrying out a wavelet decomposition of return time series before investigating the correlation dynamics across stock markets during the recent financial crisis. It thus enables us to show how the contagion dynamics between international stock market returns are changing across time scales corresponding to investors with heterogeneous time horizons. Moreover, our results reveal that the contagion dynamics depends on the bull or bear periods of stock markets, on stock markets maturity, and on regional aspects. Therefore, all these finding should be considered from an international portfolio diversification perspective.     

Daily market news sentiment and stock prices

In recent years there has been a tremendous growth in readily available news related to traded assets in international financial markets. This financial news is now available through real-time online sources such as Internet news and social media sources. The increase in the availability of financial news and investor’s ease of access to it has a potentially significant impact on market stock price movement as these news items are swiftly transformed into investors sentiment which in turn drives prices. In this study, we use the Thomson Reuters News Analytics (TRNA) data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index constituents. We use these daily DJIA market sentiment scores to study the influence of financial news sentiment scores on the stock returns of these constituents using a multi-factor model. We augment the Fama–French three-factor model with the day’s sentiment score along with lagged scores to evaluate the additional effects of financial news sentiment on stock prices in the context of this model using Ordinary Least Square (OLS) and Quantile Regression (QR) to analyse the effect around the tail of the return distribution. We also conduct the analysis using the seven-day simple moving average (SMA) of the scores to account for news released on non-trading days. Our results suggest that even when market factors are taken into account, sentiment scores have a significant effect on Dow Jones constituent returns and that lagged daily sentiment scores are often significant, suggesting that information compounded in these scores is not immediately reflected in security prices and related return series. The results also indicate that the SMA measure does not have a significant effect on the returns. The analysis using Quantile Regression provides evidence that the news has more impact on left tail compared to the right tail of the returns.     

Does economic policy uncertainty matter for commodity market in China? Evidence from quantile regression

ABSTRACT

This paper investigates the effect of economic policy uncertainty (EPU) on China’s agricultural and metal commodity futures returns across quantiles. We address this issue using the panel quantile regression approach, which allows for a more complete analysis of various conditions in the commodity market (i.e. bearish, normal, and bullish markets). Our empirical results reveal that domestic EPU shocks have a significantly negative effect on agricultural futures returns in bearish markets and a significantly positive effect on metal futures returns in bullish markets. The impacts of both domestic and U.S. EPU shocks on commodity markets are heterogeneous across quantiles and are sector specific. Additionally, by isolating positive and negative EPU shocks, the regression and test results indicate an asymmetric response of commodity futures prices in bullish markets. Moreover, our findings indicate that the metal futures market has a higher financialisation level than the agricultural futures market. The findings can be utilized by policymakers and investors.     

Financial contagion and volatility spillover: An exploration into Indian commodity derivative market

This study measures the extent of financial contagion in the Indian asset markets. In specific it shows the contagion in Indian commodity derivative market vis-à-vis bond, foreign exchange, gold, and stock markets. Subsequently, directional volatility spillover among these asset markets, have been examined. Applying DCC-MGARCH method on daily return of commodity future price index and other asset markets for the period 2006–16, time varying correlation between commodity and other assets are estimated. The degree of financial contagion in commodity derivative market is found to be the largest with stock market and least with the gold market. A generalized VAR based volatility spillover estimation shows that commodity and stock markets are net transmitters of volatility while bond, foreign exchange and gold markets are the net receivers of volatility. Volatility is transmitted to commodity market only from the stock market. Such volatility spillover is found to have time varying nature, showing higher volatility spillover during the Global Financial Crisis and during the period of large rupee depreciation in 2013–14. These results have significant implication for optimal portfolio choice.     

Global Liquidity and Commodity Prices

While monetary easing and increasing participation of financial institutions in commodity trading have enhanced the financialization of commodity markets, this paper investigates empirically whether the impact of global liquidity on commodity prices has grown since the crisis. For each commodity group, this paper uses a structural vector autoregression (SVAR) model to address the short‐run relationship between global liquidity and commodity prices. The key finding is that the effect of global liquidity on commodity prices becomes more salient since the global financial crisis. This paper also suggests a price‐based liquidity indicator has a greater explanatory power for the commodity price dynamics than monetary aggregates.     

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.     

Googling Investor’s Sentiment: Powerful Measure in Conventional and Islamic MENA Financial Markets

ABSTRACT

The objective of this paper is to investigate whether investors' sentiment measured by the Internet search behavior constitutes a valid measure of investor’s sentiment on Islamic and conventional indexes of emerging and frontier financial markets in MENA countries. In fact, we examine the relation between googling investor’s sentiment and monthly Islamic and conventional index returns during the period 2004–2016. Using the Dynamic Conditional Correlation, the BEKK-GARCH and the wavelet coherence models, we confirm that googling investor’s sentiment is a perfect indicator of investor’s sentiment measure. Indeed, we find that this measure has the ability to reflect major events such as subprime financial crisis, oil crisis and Arab spring revolution affecting MENA Islamic and conventional index markets. Our finding indicates that investors can use googling investor’s sentiment as an indicator to predict returns and volatility of emerging and frontier markets since it reflects the behavior and emotions of investors in MENA financial markets.