Search

Using the method of, this study constructs a tail risk predictor of the international commodity market to forecast US stock volatility. The in-sample results show that tail risk contains significant interpretive ability for stock volatility. Being of our interest, the tail risk predictor can successfully predict the US stock volatility from both statistical and economic viewpoints. The results of controlling 12 popular macroeconomic variables suggest that tail risk contains incremental information for stock volatility. To further confirm our findings, we examine the forecasting performance of the tail risk predictor for 12 industrial portfolios. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Finding suitable safe haven opportunities to protect emerging investments, such as cryptocurrencies, from external factors, such as Geopolitical risk, is a major concern for investors. Recognizing safe havens for these assets can help investors and traders manage risk, stabilize their portfolios, diversify their investments, and preserve capital against Geopolitical risk. To find the safe havens for cryptocurrencies regarding Geopolitical risk, this study proposes an approach to identifying the most suitable safe havens for cryptocurrencies highly affected by Geopolitical risk. First, the study identifies the cryptocurrencies that are more influenced by Geopolitical risk than others; by this, the assets that require hedging are discovered. Then, a new method, quantile-on-quantile regression, is employed to test the hedging ability of multiple assets from different markets. Once the outcomes of the quantile-on-quantile regression are cleared, the hedge effectiveness index by dynamic conditional correlation GARCH is calculated to validate the results. Both methods yield similar results, suggesting that the Forex market and stock indexes are the most suitable options as safe havens for cryptocurrencies. The study also finds that assets from the energy sector of the commodity market, such as Crude Oil and Natural Gas, are the weakest safe haven options. [ABSTRACT FROM AUTHOR]

While numerous studies investigate volatility transmission across commodity markets, particularly oil and agricultural markets, uncertainty diffusion across commodity markets remains absent from the literature. This circumstance is primarily related to the lack of appropriate measures of commodity price uncertainty, which differs from volatility. This study focuses on measuring commodity price uncertainty and how it is transferred from one commodity market to another. Our contributions are twofold. (i) We construct an aggregate predictability-based measure of uncertainty for each group of commodity markets and different maturities, and (ii) we analyse uncertainty diffusion across different commodity markets using a vector autoregressive model. Our findings clearly demonstrate a bi-causal uncertainty transfer between agriculture, energy, and industrial markets, excluding precious metals markets. Additionally, the industrial commodity market is assumed to be the transmission channel of commodity uncertainty spread, given its close link with global economic activity. Notably, we validate the efficacy of using industrial uncertainty as a proxy for macroeconomic uncertainty. Finally, our confirmation of precious metals' insensitivity to other markets' shocks reinforces its nature as a safe haven. [ABSTRACT FROM AUTHOR]

This article investigates the linear and non-linear dependence structures of risk contagions between global crude oil futures markets and China's agricultural futures markets based on a regime switching skew-normal (RSSN) model. We examine the oil-agriculture relationships and identify the contagion channels under the calm and turbulent oil market conditions. The directions of contagions are further identified with the directed acyclic graph (DAG) from the linear non-Gaussian acyclic models algorithm. The empirical results of contagions tests show the significance of correlation and covariance contagions across the oil and agriculture futures returns, especially under the turbulent oil market condition. The breaks in the variances through the moment-based break tests are found to be most significant, followed by the mean and skewness breaks. In addition, the DAG results support the volatility contagions from world oil future markets to China's agricultural commodity futures markets. Our empirical results have important policy implications for the government to take effective measures to stabilize China's commodity market and promote the development of alternative energy in China, as well as for market participants to best manage the market risks. [ABSTRACT FROM AUTHOR]

Using annual data for Botswana from 1960 to 2012, we examine the responses of macroeconomic variables to four generalized positive terms of trade shocks – global demand, globalizing, sector-specific and global supply. A sign-restricted structural vector autoregression model with a penalty function is estimated to identify the four possible shocks. While positive global demand and globalization shocks are both expansionary, they have opposite effects on inflation. A positive commodity market specific shock dampens real GDP growth and is inflationary, suggesting a possible Dutch disease response. A negative global supply shock suppresses both output growth and inflation. All but the last shock leads to a significant declining interest rate. Monetary policy contraction is recommended for the first shock and expansion for the others. [ABSTRACT FROM PUBLISHER]

This paper explores the dynamic return and volatility connectedness for the three most relevant agricultural and livestock commodity indexes (Softs, Grains and Livestock) and a media sentiment index as the Coronavirus Media Coverage Index (MCI). To that purpose, we apply the fresh time-varying parameter vector autoregression methodology during the sample period between 1 January 2020 and 30 April 2021, that is, covering the three waves of the COVID-19 pandemic crisis. Interesting results are found in this research. First, dynamic total return and volatility connectedness fluctuate over time, reaching a peak during both the first and the third waves of the global pandemic crisis. Second, in the dynamic connectedness TO the system, we observe significant differences between markets at the level of the return connectedness measure. However, in the dynamic volatility connectedness TO, there are very few differences between some elements of the system. The Coronavirus MCI appears as the less relevant receiver FROM the system, not only in terms of dynamic return connectedness but also in volatility. Finally, regarding the net dynamic total connectedness, the Coronavirus MCI shows the highest values in return and volatility, during most of the sample period analysed. [ABSTRACT FROM AUTHOR]

The recent expansion of trade measures across countries in sub-Saharan Africa provides market opportunities for the agri-food sector. However, price signals and changes across domestic and regional continental markets are a factor in boosting the success and performance of these markets. Examining commodity market adjustments to price shocks is essential for insights to boost trade performance. Using prominent food categories of the agricultural sector in this region, the study examines market dynamics between pulses, exports, and other staple convenience food. Spatial analysis evaluates market inter-dependencies between regional and domestic markets using a vector error correction model. The findings suggest heterogeneous market effects across commodities horizontally and vertically for value-added product forms in the food chain. In domestic intra-regional markets, price transmission is about as high for regional continental markets, while the extent for inter-regional domestic markets varies by the commodity niche on the value chain. Tailored market development policies can better the overall functioning of agri-food markets and boost the convergence of markets as well as trade integration and expansion. [ABSTRACT FROM AUTHOR]

The role of economic policy uncertainty in the risk transmission between crude oil and stock market cannot be ignored. However, it is unclear whether economic policy uncertainty always amplifies the impact of oil price shocks on stock market over time. This study employs the time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model to examine the dynamic relationship among different types of oil price shocks, economic policy uncertainty, and China's stock market returns at the aggregate and industry levels. The empirical results are as follows: First, different types of oil price shocks and economic policy uncertainty have significant time-varying impacts on stock market returns, which mainly occur in the short term. During periods of increased economic policy uncertainty, the stock market is more sensitive to oil price shocks. Second, economic policy uncertainty provides a transmission channel for the propagation between oil price shocks and stock markets, but how does economic policy uncertainty connect oil-stock nexus depends on the origins of oil price shocks. Third, the response patterns of stock market to oil price shocks and economic policy uncertainty are heterogeneous in different industries. Our results provide important implications for policymakers and investors. [ABSTRACT FROM AUTHOR]

This article investigates the time-frequency connectedness of categorical policy uncertainty, geopolitical risk and Chinese commodity markets by applying the vector autoregression method for the period from August 2004 to March 2021. Specifically, our research employs rolling window analysis of wavelet decomposition series to uncover the dynamic properties of connectedness with a time-frequency framework. The results indicate that heterogeneity exists across time scales for policy-specific uncertainty, geopolitical risk and commodities throughout the study period. In particular, the directional connectedness shows that the commodity markets are most closely related to monetary policy uncertainty, followed by exchange rate policy uncertainty, fiscal policy uncertainty and trade policy uncertainty, and finally geopolitical risk. In addition, connectedness exhibits an obvious changing trend during the crisis period, and the spillover effects of policy uncertainty and geopolitical risk increase dramatically. Finally, the long-term connectedness between policy uncertainty, geopolitical risk and commodities are stronger than that in the short-term periods. Overall, our findings provide valuable implications that policymakers and investors should pay attention to dynamic and time-frequency features of connectedness when making decisions. [ABSTRACT FROM AUTHOR]

The article explores the indirect link between the trade war between China-US and deforestation in Brazil. China imposed tariffs that have eliminated American soy exports by November 2018. Higher soybean prices usually increase deforestation in Brazil. We estimate nonlinear autoregressive distributed lag models combined with multiple breakpoint tests to analyze price transmission changes over time. We show that market power emerges in the short run, while long-run price pass-through is close to complete. Extra profits from unexpected market power should induce land clearing for expanding soy production, a problem compounded by lax regulation, and reduced budgets for combating deforestation in Brazil. Results also suggest that effects on deforestation rates should be temporary. Given that the covid19 pandemic brings about a similar shock to global food markers, particularly demand for Brazilian soy, we expect a similar pattern of emergence of market power in the short but not long-run. [ABSTRACT FROM AUTHOR]

This study investigates the impact of COVID-19 on the seasonality of gold returns by means of an asymmetric EGARCH model (Exponential GARCH). We find that the so-called 'autumn effect', or the traditional seasonal increase in gold returns in fall, vanishes and even shows a reverse pattern during the COVID-19 pandemic. We ascribe this phenomenon to the decaying demand for gold, which substantially decreased in the third quarter of 2020. In contrast, we find no evidence of seasonal effects in gold volatility, which is in line with earlier researches on this topic. Our results also confirm the positive asymmetric effect of gold volatility. [ABSTRACT FROM AUTHOR]

We examine the spillovers and resource allocation characteristics of a portfolio of precious metal commodities and global/regional equity markets using a directional spillover index and portfolio optimization methods. Spillover index results show that the largest spillovers among precious metals occur between gold and silver and between zinc and lead. The largest spillovers of the world, Americas, Europe and Asia Pacific equity indices are on palladium and copper. Copper and zinc most largely spillover on the world and Americas equity indices. Copper and lead most largely spillover on the Europe equity index, while copper and silver most largely spillover on the Asia Pacific equity index. Portfolio optimization results indicate that nickel and lead add the most risk to total portfolio risk, whereas gold, platinum and aluminium add the least risk to the portfolio of commodities. Gold and aluminium are the precious metals most desirable for investment. [ABSTRACT FROM AUTHOR]

This study examines the impact of structural oil demand and supply shocks on the prices of four food-grains: corn, rice, soybean and wheat. We first derive two oil demand shocks-one is due to the change in the global economic condition and the other is oil-market-specific-and an oil supply shock that reflects the change in global oil production. The structural shocks are then used in the linear, and nonlinear Markov-switching models to examine their effects on the four food-grain prices. The results show that an unanticipated oil supply shock does not affect price of any of the four food-grains significantly. An increase in the demand for oil, which is not induced by the change in global economic condition, increases only the corn price in the less volatile corn market. An improvement of global economic condition impacts wheat and corn prices in high volatility regimes. However, oil shocks that are older than one month usually do not affect the food-grain prices. [ABSTRACT FROM AUTHOR]

In China's 2019 VAT reform, the VAT rate for manufacturing was adjusted from 16% to 13%. This inevitably promotes manufacturing production and triggers a substantial increase in carbon emissions. Would carbon tax be an effective policy tool to offset the negative externalities of the VAT reform on carbon emissions? We construct a multi-regional dynamic-recursive computable general equilibrium (CGE) model to evaluate this possibility and to investigate the potential impacts on the economy, energy, and environment arising from this reform. The scenarios set includes the VAT reform policy, a carbon tax, and three combined policies. The results show that while China's VAT reform is a positive fiscal policy that can boost long-lasting macroeconomic development, it has a negative impact on environmental protection. A carbon tax can significantly curb traditional energy consumption and emissions, but it would hinder economic development. Combined policies yield 'double dividends', that is, a long-run increase in macroeconomy and emissions reductions will be achieved, helping China to attain its Intended Nationally Determined Contributions goal. The combination of VAT reform and a stepped carbon tax maintains a more stable economic growth while sustaining carbon emission abatement. [ABSTRACT FROM AUTHOR]

This research describes the industries' development and efficiency distribution, investigates the process of industry efficiency influence of these industries' agglomeration effect on total factor productivity (TFP) change based China's science and technology service industries from 2010 to 2019 data. We analyse the main factors influencing TFP change and the stage effect difference of significant factors through using linear and non-linear regression equations by construct the panel regression equations. The empirical results show:1) the overall trend of science and technology service industry agglomeration in China is declining; 2) Provinces and regions exhibits a trend of respective agglomeration within the economic belt; 3) the different location entropies of the five regions lead to obvious differences in the development stages; 4) the influences of technology progress and foreign trade on TFP efficiency changes are generally significant; 5)Science and technology service industry have improved industrial efficiency in the central and western regions and made it easier for these regions to break through bottlenecks. We conclude that industrial efficiency improvements should be based on technology upgrading and expansion in infrastructure allocation, also offering more realistic solutions to promote system construction and interregional policy coordination. [ABSTRACT FROM AUTHOR]

This study examines causality shifts in the revenue–expenditure nexus in Brazil during the years 1996–2019. The literature usually assumed a time-invariant causality link between government revenues and expenditures. Such assumption becomes often implausible when the sample period covers significant economic, political and policy changes, like the case of Brazil in the last two decades. Based on time-varying Granger causality tests, we found three distinct causality episodes: fiscal synchronization in 2005–2008, spend-and-tax in 2010–2013, and a tax-and-spend in 2015–2018. These episodes are intercalated with periods of no causality that coincides with economic crisis, political turmoil and major shifts in fiscal policy. The findings suggest that the interplay between fiscal policy orientation and primary surplus targeting is an important factor in the revenue–expenditure nexus. The most recent causality episode suggests stronger effects running from revenues to expenditures in the Brazilian primary budget dynamics. In this context, according to the tax-and-spend hypothesis, cutting spending seems to be the right course of action to restore fiscal balance in Brazil. A tax increase should be considered with caution because it may only incentive the government to grow its expenditures. [ABSTRACT FROM AUTHOR]

Recent advances in cointegration tests and error correction models are applied to the analysis of commodity inventory behaviour. Multi-cointegration was considered in inventory series of seven internationally traded products. In contrast to previous works on inventory behaviour which first hypothesize a relationship and then gather empirical evidence to emulate the postulated behaviour, an error correction model was used to represent theoretical inventory relationships which are established by multi-cointegration tests. The results support the use of this approach to determine the optimal stockpiling rules of producers and consumers.
This paper attempts to provide new insights into commodity inventory behaviour based on recent developments in cointegration tests and error correction models. This approach has the special facility to analyse concomitantly both long and short-run aspects of inventory behaviour, a factor crucial to determining long-run commodity market equilibrium, while also explaining short-run stability in the demand for and supply of inventories. More recently, these cointegration models have been extended, based on advances in multi-cointegration, which consider inventory adjustments as a correction to the steady-state relationship between production and consumption, and inventories. The empirical base which has been selected to test the presence of multi-cointegration in this study includes commodity 'stock' and 'flow' data for the international cocoa, copper, coffee, sugar, maize, soybean and wheat markets. [ABSTRACT FROM AUTHOR]

Price and income elasticities are emphasized in the analysis of international trade in theory and practice. Moreover, most of the empirical work undertaken by economists to estimate the differences in elasticities among countries considers the formulation and estimation of demand for exports only. Demand is clearly not equal to supply in some markets because of slow adjustment of prices. These markets will be characterized by either shortages or surpluses. The world trade market is even more vulnearable to political influences than a domestic commodity market and, in addition, is hampered by various obstructions to the flow of international trade. Other than the purely economic reasons of excess demand and excess supply, there are noneconomic factors that contribute to the disequilibrium aspects of the international trade market. Uncertain and costly information resulting from indirect, disguised and sometimes capricious trade policies of foreign countries may keep the export prices from adjusting quickly to the equilibrium values.

This paper explores the heterogeneous impact of R&D on firm growth in Chinese manufacturing industry during the periods 2012–2017. We divide the full sample into sub-samples according to different ownership, firm size and sectors, respectively, which help comprehensive observe the impact of R&D on firm growth. The results indicate that R&D has a significant positive impact on firm growth, and that R&D of private enterprises has a greater impact on firm growth than that of state-owned enterprises across all quantiles. Moreover, we find the R&D effectiveness of non-small and medium-sized enterprises is significantly greater than that of SMEs. Additionally, persuasive evidence proves the existence of an inverted-U relationship between R&D and firm growth, except for higher-growth state-owned SMEs. The results also indicate that R&D plays a more significantly positive role in high-tech industries. Our finding suggests that policymakers should encourage R&D investment in manufacturing industry to promote firm growth. But policymaker must classify firms, observe R&D intensity turning points of firms with different types, formulate meticulous R&D strategies, and maximize R&D utility. [ABSTRACT FROM AUTHOR]

The study aims to systematically examine the role of infrastructure investment on the quality of economic growth by using the regional panel data of 29 Chinese provinces. A comprehensive index is developed using the principal component analysis (PCA) to observe the economic growth quality. Regression results show that China's infrastructure investment has not exceeded the threshold, and the quality of economic growth has improved significantly. The results were robust using the regional average investment level and infrastructure stock as instrumental variables for 2SLS and system GMM testing. Further, the mediation analysis confirms that infrastructure investment improves economic growth through the physical and material circulation of resources, market integration, and knowledge capital evolution. Overall the results provide more profound policy enlightenment with regards to infrastructure investment. [ABSTRACT FROM AUTHOR]

Identifying the factors affecting profitability is important from the perspective of market players. One of the most important benchmarks of firm performance is accounting profit and effective factors analysis so that users of accounting information analyse the factors affecting profit, firm performance and various aspects of its performance and according to estimates Done, make your own decision on how to allocate resources. The main purpose of this study is to investigate the impact of some factors of competitiveness, entrepreneurship and business environment indicators on the profitability of the world's top companies. For this purpose, 176 top companies in the world from 2013 to 2018 that were profitable among the top 200 companies each year were selected as the statistical population. World Bank annual reports, Global Competitiveness Index, Global Entrepreneurship Monitor, and Fortune site were used to collect the data. Also the data analysis was done according to the data panel method using Eviews10 software. The results show that in general, there is a positive relationship between competitiveness, entrepreneurship and business environment indicators with financial performance of top companies in the world. On the other hand, the per capita income of the countries in which the top companies belonged was considered as a control variable and the results show that the per capita income has a positive and significant relationship with the financial performance of the top companies in the world. [ABSTRACT FROM AUTHOR]

The components of term structure of interest rate are an important element of the asset pricing models. This article studies the connectedness of the component of the sovereign yield curve across eleven earliest members of the Eurozone comprising six core countries (Germany, Netherlands, Finland, Austria, Belgium, France) and five peripheral countries (Greece, Ireland, Italy, Portugal and Spain) thus enabling us to analyse the short-, medium- and long-term yield curve dynamics of these eurozone economies. We document three distinct phases of connectedness described by the early eurozone period, global financial crisis and the European sovereign debt crises, and the period afterwards. We find a higher level of connectedness between the countries before the global financial crisis, which decreased to its lowest levels during the European debt crisis and is now rising back to higher levels following the European debt crisis. We find that, in general, the core countries are net transmitter of spillover, whereas, the peripheral countries are net receivers of spillover for the three components of the yield curve. [ABSTRACT FROM AUTHOR]

This research examines the relationship between agricultural commodity prices and the local housing market. Previous literature focuses on the unidirectional impacts from commodity prices to the local economy, but we propose that in some cases local asset markets can also influence commodity prices due to the agglomeration of commodity productions and the linkages of financial markets, and thus the causalities between them can be bilateral. In addition, according to a new regional economic model that we develop about local asset market and commodity price shocks, we further predict the causalities between the commodity prices and the local house price are nonlinear. We test these hypotheses using data of the major agricultural commodities of an agriculturally focused region – California Central Valley area. The results are consistent with our expectations: there is no evidence for linear causalities between the price returns of these agricultural commodities and the local housing market, but the nonlinear Granger causalities between them are significant. [ABSTRACT FROM AUTHOR]

We investigate the portfolio allocation and risk contribution characteristics of agricultural commodities, and the volatility spillovers between agricultural commodities and global and regional equity markets. We draw our results by applying a directional spillover index and a nonlinear portfolio optimization method. We find that the largest transmission and reception of spillovers occur among wheat, corn and soybeans, and between sugar cane and sugar beets. All global and regional stock market indices considered most largely spillover on cotton and cocoa. The global and Americas stock market indices are most largely spillovered by corn and soybeans. Also, while the European stock market index is most largely spillovered by cotton, the Asia Pacific stock market index is most largely spillovered by wheat and coffee. The portfolio optimization shows that sugar cane, followed by wheat and corn, are the largest risk contributors to total portfolio risk, whereas, cocoa, followed by lumber and cotton, are the lowest risk contributors to total portfolio risk. Cocoa and lumber are the most desirable for investment. Implications of the results are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a novel GARCH-MIDAS-SK (G-M-SK) model that improves the basic GARCH-MIDAS (G-M) model by incorporating time-varying skewness and kurtosis. We employ our model with data concerning macroeconomic fundamentals to investigate in-sample fit and out-of-sample prediction of volatility in crude oil prices. Empirical results suggest that G-M-SK models produce the better in-sample fit than basic G-M models do. This result is also robust for the subsample of the oil market. It is equally noteworthy that modelling low-frequency macroeconomic variables better reveals the long-term volatility from time-varying skewness and kurtosis. More importantly, G-M-SK model significantly and robustly improves accuracy in predicting oil volatility. In particular, we find that data regarding macroeconomic fundamentals contribute more to forecasting volatility in oil prices than their variance does. Finally, our G-M-SK model more precisely calculates the utility incident to minimizing risk and allocating portfolios. Its results are consistent with out-of-sample forecasting results. These results are beneficial to the decision-making of the crude oil investors and policymakers alike. [ABSTRACT FROM AUTHOR]

Small island spaces are confronted with significant disadvantages that ultimately result in strong economic vulnerability. The conventional literature emphasizes the main role of agriculture in generating structural vulnerability. Specifically, the higher the weight of agriculture compared to other sectors is, the more structurally vulnerable an economy is. However, the recent food crises revealed that the economic dependence on agriculture is not a problem on its own, but the issue is rather the efficiency of this sector along with the orientation of domestic production towards diversification and food self-sufficiency. In this paper, we thus propose a new structural economic vulnerability indicator based on the assumption that promoting the local agriculture could boost development. We insert the share of the agriculture sector in the GDP proxied by imported food dependency into the 'official' economic vulnerability index. Moreover, for robustness, the proposed indicator is obtained based on an endogenous weighting system derived from data envelopment analysis. Finally, our simulations for a sample of 131 developing economies point out that considering food dependency reduces dramatically the exposure of small island economies to structural vulnerability. [ABSTRACT FROM AUTHOR]

The relationship between macroeconomic uncertainty and entrepreneurial activities has been the subject of intense debate among researchers. However, existing empirical studies report mixed findings. By examining the mediating role of cultural traits, we attempt to reconcile the conflicting results concerning the direction of the relationship between macroeconomic uncertainty and entrepreneurial activities. Specifically, we argue that the effect of macroeconomic uncertainty on entrepreneurial activities varies across the cultural trait of uncertainty avoidance. In countries where the prevailing culture is overwhelmingly characterized by low uncertainty avoidance, macroeconomic uncertainty is positively associated with entrepreneurial activities. By contrast, in countries where the prevailing culture is overwhelmingly characterized by high uncertainty avoidance, macroeconomic uncertainty is negatively related to entrepreneurial activities. Using data on 36 countries over the 2006–2016 period and employing the negative binomial regression technique, we find empirical support for our hypotheses. A series of robustness tests confirm the reliability of our empirical results. [ABSTRACT FROM AUTHOR]

Recent research has found the language sentiment in financial news to be a substantial driver of prices in financial markets, though there are two diametrically opposed interpretations for this: either markets perceive news sentiment as fundamental information (thus leading to changes in the valuation of assets) or news sentiment conveys a noise signal (thus contributing to the stochastic component of prices). The opposite roles are resolved in the context of crude oil prices by decomposing price movements into two components referring to fundamental and noise trading. Contrary to theoretical arguments in prior literature, we find empirical results supporting both interpretations. [ABSTRACT FROM AUTHOR]

In this study, we propose a new GO-GARCH-EVT-copula combined approach to estimate minimum quantile risk hedge ratios. We examine the hedging effectiveness of the proposed model in comparison with three other competing models. In doing so, we consider thirty-five pairs of daily spot and futures price series data from various stock, currency, and commodity markets across the world. The evidence suggests that the proposed combined approach performs best in estimating minimum quantile risk hedge ratios. The superior performance is likely due to the combined approach's ability to appropriately capture the statistical features of the data. [ABSTRACT FROM AUTHOR]

Using exchange-traded fund (ETF) options data, we examine the predictive power of variance risk premium on returns of four commodities: crude oil, natural gas, gold and silver. We also analyze the predictive power of upside and downside variance risk premiums using a decomposition model conditional on the direction of the underlying market movement. We find that both the undecomposed and decomposed variance risk premiums are able to predict commodity prices. The decomposed variance risk premiums, however, outperform the undecomposed premium. The importance of upside and downside variance risk premiums differs across markets, related to hedging demand. In energy markets, both upside and downside premiums have strong predictive power, while in precious metal markets, only the upside premium is predictive. [ABSTRACT FROM AUTHOR]

Although fluctuations in agricultural commodity prices appear to be a source of risk to the US restaurant sector, the effect that volatility of food price has on the performance (returns) of that sector receives little or no attention in the relevant literature. We fill this gap by modelling the price and returns of corn and wheat and the volatilities of the US restaurant equity sector through a GARCH-jump intensity model. We find evidence indicating that the US restaurant sector is sensitive to food volatility shocks. Food price volatility negatively impacts US restaurant sector equity returns, implying that increases in food price volatility undermine restaurant sector performance. Also, food price volatility is observed to influence the restaurant sector symmetrically, indicating that changes in food volatility (increases and decreases) have homogeneous effects on the US restaurant sector performance. Implications of the results are discussed. [ABSTRACT FROM AUTHOR]

This paper examines whether the grain market of Turkey is cointegrated with the world grain market. Using an error correction model, we analyse the response of producer prices of wheat, barley, maize, soybean and rice to changes in world market prices. Results show that the rice market of Turkey is not cointegrated with the world rice market, while the other commodity markets are weakly cointegrated. Results also show that pass-through of changes in the world prices to the domestic prices is relatively low both in the short run and in the long run, and that adjustment to the new equilibrium following a shock is slow. Government intervention policies both at the border and as domestic price supports seem to be underlying causes of the weak cointegration. Fewer protectionist policies and lower levels of government intervention are necessary to increase the domestic grain market integration with the international grain market. [ABSTRACT FROM AUTHOR]

This paper investigates the price dynamics between a selection of international staple food and cash crop futures prices. This price interaction is particularly relevant for developing countries that rely on cash crop export earnings to finance their staple food import requirements. We employ a multivariate Copula-DCC-GARCH model to characterize the cash crop and staple food price interaction over time and a rolling-sample volatility index to identify the direction of the volatility spillover for staple-cash commodity pairs. Results show that the intensity of interaction varies considerably over the sample time, but is, generally positive, and stronger during the period 2007–2012 associated with high commodity prices and financial market stress. [ABSTRACT FROM AUTHOR]

This article aims to determine what drives the price of Bitcoin. To achieve this aim, a large set of data is analysed using VEC models augmented by factors representing unobservable economic forces. They have been obtained by means of principal component analysis. This method enables us to contribute to the existing literature on Bitcoin in two ways. First, we employ the dimension reduction technique to combine variables from several papers. Second, we estimate several unobservable economic concepts instead of utilizing proxy variables as is usually done. We find that the main factor driving the Bitcoin price is its popularity. Hence, our result not only confirms some previous findings but reinforces them by providing a better definition of popularity. Finally, we conclude that the Bitcoin price is not affected by supply and demand factors in the way that is natural for conventional currencies. [ABSTRACT FROM AUTHOR]

This study compares a range of agricultural commodities over periods of varying economic circumstances. These commodities are examined over three categories, including returns, risk, and contribution to portfolio optimisation. Consistency in these categories is determined over four equal three-year stages which comprise pre-GFC (Global Financial Crisis), GFC, post-GFC and post-post GFC. To demonstrate resilience in the most extreme circumstances, the study uses Conditional Value at Risk (CVaR), which measures extreme risk in the tail of a distribution, as the risk measure and risk-return optimiser. The study thus provides a unique and comprehensive extreme-risk based focus which identifies and ranks the consistency of performance of agricultural commodities over a range of criteria and conditions. Cattle commodities consistently demonstrate the strongest overall performance in the categories examined. [ABSTRACT FROM AUTHOR]

This paper examines whether the market-making system helps to improve the price discovery ability of New Third Board (NTB) market in China. We first estimate the time-varying coefficients error correction models, then apply common factor weight method to quantify the time-varying price discovery contributions, and finally explore the impacts of trading volume and volatility to price discovery contributions. Empirical results show that both markets have time-varying characteristic in terms of the magnitudes and directions of the equilibrium price adjustment due to error correction term. The Shanghai Composite Index, SZSE Component Index, and SME Index are found to lead in price discovery, while NTB exhibits the leadership on the GEM Index. Volume and volatility have significant influence on the price discovery contribution. The NTB contribution is positively related to its own trading activity, negatively related to the trading activity of Shanghai and Shenzhen stock markets, while negatively correlated with the volatility of both markets. In comparison, trading activity of SZSE Component Index and volatility of GEM Index have the greatest negative impacts on the contribution of NTB market. As an important part of China's multi-level capital market, the pricing mechanism of the NTB market needs further to be improved. [ABSTRACT FROM AUTHOR]

We investigate the presence of bubbles in the US house price-income ratio at the State level by applying the recent time series-based econometric test to data from January 1975 to December 2014. We find evidence of bubbles in several States in the 1980s (i.e. California, Hawaii, Massachusetts, New York, etc.), which coincides with some existing studies that investigate housing bubbles or booms and busts using a range of alternative approaches. Our results show the existence of a housing bubble that originates in the early 2000s and collapses in the mid-2000s in more than 20 States and the District of Columbia concluding that the bubbles of the 2000s were more widespread than the 1980s, which is of special interest and importance. Our results seem to be in agreement with the talk given by Alan Greenspan in 2005, who suggest no sign of a nationwide housing bubble but a lot of local bubbles. We also study the importance of the regression model specification with/without an intercept and the regression model with an intercept could lead to false-positive identification of bubbles. [ABSTRACT FROM AUTHOR]

In this article, we empirically study the time-varying bilateral causality between commodity prices, inflation and output in China. We first perform a series of parameter stability tests and find strong evidence of instability in the parameters estimated for Granger causality tests. We then use the bootstrap rolling window approach to test the causality and find that the causality from commodity prices to both inflation and output is time-varying in the entire sample period and asymmetric in different phases of the business cycle. We also find evidence of the causality from both inflation and output to commodity prices in certain sub-periods. Further discussion on the cost-price mechanism through which the economy fluctuates cyclically suggests that the dynamic causality between commodity prices and inflation contributes to understanding the nature of economic fluctuations and to forecasting economic crises. Overall, our results provide a new perspective to disentangle economic fluctuations. [ABSTRACT FROM PUBLISHER]

We study the relationship between Bitcoin and commodities by assessing the ability of Bitcoin to act as a diversifier, hedge, or safe haven against daily movements in commodities in general, and energy commodities in particular. We focus on energy commodities because energy, in the form of electricity, is an essential input in the Bitcoin production. For the entire period, results show that Bitcoin is a strong hedge and a safe-haven against movements in both commodity indices. We further examine whether that ability is also present for non-energy commodities and our analysis show insignificant results when energy commodities are excluded from the general commodity index. We also account for the December 2013 Bitcoin price crash and our results reveal that Bitcoin hedge and safe-haven properties against commodities and energy commodities are only present in the pre-crash period, whereas in the post-crash period Bitcoin is no more than a diversifier. In addition to uncovering the time-varying role of Bitcoin, we highlight the dissimilarity in the dynamic correlations between the extreme downward and extreme upward movements. [ABSTRACT FROM AUTHOR]

The presence of investor sentiment pushes asset prices away from the equilibrium level justified by underlying fundamentals. While sentiment is not directly observable, identifying appropriate proxies and, quantifying the impact of sentiment on asset prices is an important topic. Asset prices that do not appropriately reflect fundamental values may result in inefficient allocation of capital – impacting portfolio allocation decisions and the cost of capital. Utilizing a number of sentiment proxies, over the period 1990–2015, we demonstrate a strong relationship between investor sentiment and stock returns that is consistent with theoretical explanations of sentiment. We determine that implied volatility index (VIX) is the preferred measure of sentiment in terms of improving model fit and adding explanatory power. Causality tests suggest that investor fear (VIX) drives returns across firm-size and value, and also across industry. We also illustrate that firms that are more subjective to value, or face limits to arbitrage, such as small-cap stocks, or those in the business equipment (technology) or telecoms industry, are most responsive to changes investor sentiment. Finally, we demonstrate that sentiment has a greater influence on market returns during recession, when sentiment is at its lowest ebb, and this is particularly true for those stocks most susceptible to speculative demand. [ABSTRACT FROM AUTHOR]

The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns. [ABSTRACT FROM PUBLISHER]

In recent years, the U.S.A. natural gas market has seen enormous changes. The expectations of abundant supply of shale gas and the slow U.S.A. economic recovery have pushed gas prices below US$ 4 MMBtu. Although shale gas is a new promising source of unconventional energy, investors face uncertain investment plans. In this study, we investigate the risk premium by comparing behaviour before and after the change point in agents risk perception. Unlike traditional empirical research on risk premium, we use the parametric, two-factor model of Schwartz and Smith (2000) to evaluate the implied risk premium term structure from futures prices traded on the New York Mercantile Exchange (NYMEX). We compare our findings with other empirical results and find that the change point lies at the beginning of the low-price regime. When we compare periods before and after the change point, we observe that the risk premium changed, not only in sign, but also in magnitude. [ABSTRACT FROM PUBLISHER]