marshall s scale economies using panel data this paper estimates plant level production functions for machinery and high tech industries that allow for scale externalities from other plants in the same industry locally and from the scale or diversity of local economic activity outside the own industry the paper finds that the count of other own industry plants representing a count of local information spillover sources has strong productivity effects in high tech but not machinery industries single plant firms both benefit more from and generate greater external benefits than corporate plants given their greater reliance on external environments on dynamic externalities high tech single plant firms benefit also from the scale of past own industry activity i find little evidence of economies from the diversity or scale of local economic activity outside the own industry

electricity market integration decarbonisation and security of supply dynamic volatility connectedness in the irish and great britain markets abstract this study investigates the volatility connectedness between the irish and great britain electricity markets and how it is driven by changes in energy policy institutional structures and political ideologies we assess various aspects of this volatility connectedness including static unconditional vs dynamic conditional symmetric vs asymmetric characteristics between 2009 and 2018 we find that the volatility connectedness is time varying and it is significantly affected by important events policy reforms or market re designs such as brexit oil price slump an increasing share of renewables and fluctuations in the exchange rates our asymmetric analysis shows that magnitude of the good volatility connectedness is marginally larger than that of the bad volatility connectedness our result suggests that good volatility levels would be even higher once the irish market adopts the carbon price floor therefore supporting renewable generation by setting an appropriate price of carbon in interconnected wholesale electricity markets will improve market integration

magnitude and persistence of extreme risk spillovers in the global energy market a high dimensional left tail interdependence perspective abstract this paper studies the magnitude and persistence of extreme risk spillovers among stock returns of 124 energy companies worldwide between january 2006 and june 2019 as well as the corresponding firm specific determinants of firms extreme risk spillovers the high dimensional nonparametric method the coefficient of tail interdependence cti enables us to make better use of available information and to evaluate risk spillovers more precisely moreover we use spatial panel models that consider spatial heterogeneity among firms to explore the determinants of the risk spillovers the empirical findings from a study of energy firms risk spillover effects verify the necessity of persistence measurement also the most systemically risky energy companies are not necessarily the largest and some small firms can also generate large risk spillovers when they are in distress which indicates that determinants other than firm size could also affect the spillover effect such as business complexity and geographic location our regression results suggest that the extreme risk spillover of the energy companies exhibits significant heterogeneity in terms of business and region which deserves more attention for energy risk management the estimates can be used for making portfolio decisions and designing regulatory policies

asymmetric volatility spillovers between oil and stock markets evidence from china and the united states abstract the relationship between oil and stock markets is a hot topic but little research has focused on the time varying asymmetric volatility spillover in a quantitative manner in this study we use a new spillover directional measure and asymmetric spillover measures to investigate the dynamic asymmetric volatility spillover between oil and stock markets during the period of 2007 to 2016 using the intra day data of wti future prices the sp the results also show strong evidence of asymmetries in volatility shocks between the oil and stock markets due to bad volatility

hedging downside risk of oil refineries a vine copula approach abstract the financial health of an oil refinery greatly depends on its refining margin or the difference between the prices of its refined products typically gasoline and heating oil and the cost of crude oil the refinery may hedge against the downside risk of unfavorable price movements using crude oil gasoline and heating oil futures this paper examines the use of a vine copula approach to estimate multiproduct hedge ratios that minimize the downside risk of the refinery the advantage of the vine copula approach is that it allows us to capture important characteristics of petroleum price changes including skewness and fat tailedness in the marginal distributions of individual price change series as well as heterogeneous tail dependence patterns between different pairs of price changes the out of sample hedging effectiveness of two popular classes of vine copula models canonical c and drawable d vine copula models are evaluated and compared with that of the widely used nonparametric method and three standard multivariate copula models the empirical results reveal that the d vine copula model is a good and safe choice in managing the downside risk of the refinery

hedging crude oil using refined product a regime switching asymmetric dcc approach abstract in this paper we explore the strategy on hedging crude oil using refined product we develop a regime switching asymmetric dcc rs adcc model by taking into account both of regime switching and asymmetry in correlations our out of sample findings indicate that rs adcc displays greater hedging effectiveness than some conventional multivariate garch heating oil can better hedge crude oil than gasoline

a test for volatility spillovers abstract this paper proposes a new procedure for analyzing volatility links between different markets based on a bivariate markov switching model an empirical application of this procedure to three emerging markets is examined and discussed

welfare implications of price stabilization with monopolistic trade the welfare effects of domestic and international price stabilization are examined and then compared employing a two country model where one country exercises market power through continuous optimal trade restriction while the other behaves competitively the two types of stabilization have quite different implications on the distribution of welfare between and within countries the country exercising market power gains from domestic price stabilization regardless of the source of instability but the government and private producers and consumers are affected differently the country facing trade restriction can exercise some countervailing power by stabilizing international price fluctuations resulting from internal disturbances early studies of the welfare effects of price stabilization have adopted a perfectly competitive framework massell 1969 demonstrated that while price stabilization increases welfare to society its effects on individual groups depend crucially on the source of instability consumers producers gain from price stabilization if price fluctuations arise from

macro determinants of volatility and volatility spillover in energy markets abstract we analyze the time varying volatility and spillover effects in crude oil heating oil and natural gas futures markets by incorporating changes in important macroeconomic variables and major political and weather related events into the conditional variance equations we allow asymmetric responses to random disturbances in each market as well as to good and bad economic news related to the overall economy results show the presence of asymmetric effects in both random disturbances and macroeconomic variables a bidirectional volatility spillover effect is found between natural gas and crude oil and between the natural gas and heating oil markets crude oil volatility is found to increase following major political financial and natural events seasonality and day of the week effects are found in the crude oil and heating oil markets

risk transmission mechanism between energy markets a var for var approach abstract the global financial crisis gfc of 2007 2009 that originated in the us has revealed the need for measuring and monitoring the transmission of extreme downside market risk this paper investigates the risk transmission mechanism between the oil and natural gas markets we apply the recently introduced test statistics based on cross quantilogram function and the multivariate quantile regression model var for var to the us oil and natural gas prices which are independently formed our results show two asymmetric patterns first the shocks in the oil market substantially increase the value at risk var in the natural gas market but the reverse impact does not exist second we highlight the significant asymmetric response of gains and losses transmission in energy markets cautioning about the underlying weakness of adopting volatility to measure risk in the energy market moreover an extreme market risk is more easily transmitted across markets than moderate risks our results are in general robust in application to other regional energy markets such as europe and asia but the heterogeneities in responses are underpinned by the different role of natural gas in regions the findings in this paper have important implications for academic researchers policy makers in gas dependent economies and business practitioners in light of projected increases in the use of natural gas worldwide as well as the development of independent gas on gas competitive hub prices in asia and europe

analyzing and forecasting volatility spillovers asymmetries and hedging in major oil markets crude oil price volatility has been analyzed extensively for organized spot forward and futures markets for well over a decade and is crucial for forecasting volatility and value at risk var there are four major benchmarks in the international oil market namely west texas intermediate usa brent north sea dubai oman middle east and tapis asia pacific which are likely to be highly correlated this paper analyses the volatility spillover and asymmetric effects across and within the four markets using three multivariate garch models namely the constant conditional correlation ccc vector arma garch varma garch and vector arma asymmetric garch varma agarch models a rolling window approach is used to forecast the 1 day ahead conditional correlations the paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series in addition the forecast conditional correlations between pairs of crude oil returns have both positive and negative trends moreover the optimal hedge ratios and optimal portfolio weights of crude oil across different assets and market portfolios are evaluated in order to provide important policy implications for risk management in crude oil markets

forecasting the volatility of crude oil futures using har type models with structural breaks abstract we introduce sixteen har type volatility models with structural breaks and estimate their parameters by applying 5 min high frequency transaction data for wti crude oil futures we find significant structural breaks in the volatility of crude oil futures additionally the historical realized volatility continuous sample path variation negative realized semivariance signed jump signed semi jump and leverage components contain substantial and salient information for forecasting the volatility of crude oil futures then we use loss functions to assess the forecasting performance of these sixteen new models and finally rank these models using the promethee ii method our results indicate that different models exhibit different predictive power in forecasting the 1 day 1 week and 1 month volatility of crude oil futures of the new har type models the new har rsv model performs best at forecasting the 1 day and 1 month volatilities whereas the new har cj best forecasts the 1 week volatility

forecasting realized volatility of crude oil futures with equity market uncertainty this paper examines whether the equity market uncertainty emu index contains incremental information for forecasting the realized volatility of crude oil futures we use 5 min high frequency tran

time varying granger causality tests for applications in global crude oil markets abstract this paper proposes time varying granger causality tests based on the tests developed by hong 2001 and two dynamic correlation estimators i e rolling correlation and dynamic conditional correlation multivariate garch here called the rolling hong and dcc mgarch hong tests respectively the proposed tests are used to examine time varying information spillover among global crude oil markets the results provide empirical evidence of time varying information spillover in particular the instantaneous causal effects of dubai and tapis crudes on brent and wti become stronger when a major event or events occur in major oil producing countries such events include the iraq war in march 2003 opec s announcement of a record production cut in december 2008 and the libyan civil war in early 2011 and consistent with previous studies wti and brent play dominant roles in global crude markets impulse response analysis shows that market information has a positive influence on the spillover effect in global crude oil markets moreover the dcc mgarch hong test consistently leads the rolling hong test which indicates that the former performs better

some recent developments in futures hedging the use of futures contracts as a hedging instrument has been the focus of much research at the theoretical level an optimal hedge strategy is traditionally based on the expected utility maximization paradigm a simplification of this paradigm leads to the minimum variance criterion although this paradigm is quite well accepted alternative approaches have been sought at the empirical level research on futures hedging has benefited from the recent developments in the econometrics literature much research has been done on improving the estimation of the optimal hedge ratio as more is known about the statistical properties of financial time series more sophisticated estimation methods are proposed in this survey we review some recent developments in futures hedging we delineate the theoretical underpinning of various methods and discuss the econometric implementation of the methods

volatility spillovers for spot futures and etf prices in agriculture and energy abstract the agricultural and energy industries are closely related both biologically and financially the paper discusses the relationship and the interactions on price and volatility and on the covolatility spillover effects for these two industries the interaction and covolatility spillovers or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset between the energy and agricultural industries is the primary emphasis of the paper although there has already been significant research on biofuel and biofuel related crops only a few published papers have been concerned with volatility spillovers it must be emphasized that there have been numerous technical errors in the theoretical and empirical research which need to be addressed the paper considers futures prices as a widely used hedging instrument and also considers an interesting new hedging instrument etf which is regarded as index futures when investors manage their portfolios in the empirical analysis multivariate conditional volatility diagonal bekk models are estimated for comparing patterns of covolatility spillovers the paper provides a new way of analyzing and describing the patterns of covolatility spillovers which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects

correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies abstract in this paper multivariate garch models are used to model conditional correlations and to analyze the volatility spillovers between oil prices and the stock prices of clean energy companies and technology companies four different multivariate garch models bekk diagonal constant conditional correlation and dynamic conditional correlation are compared and contrasted the dynamic conditional correlation model is found to fit the data the best and generates results showing that the stock prices of clean energy companies correlate more highly with technology stock prices than with oil prices on average a 1 long position in clean energy companies can be hedged for 20 cents with a short position in the crude oil futures market

analyzing time varying volatility spillovers between the crude oil markets using a new method abstract the spillover effect is an important factor affecting the volatility of crude oil price basing on the study of diebold and yilmaz 2009 2012 2014 we propose a new method that calculates the time varying volatility spillover indexes by the generalized forecast error variance decomposition of tvp var sv model then using the new method we study the time varying volatility spillovers between four major crude oil markets wti brent oman tapis from november 29 2002 to july 13 2018 by comparing the results of our new method and traditional rolling window method we verify the superiority of our new method the results show that the volatility spillovers calculated by the new method are clearer more stable and not outlier sensitive from the estimated results of time varying volatility spillovers we find that the volatility spillover between crude oil markets is slowly increasing but there are obvious cyclical changes and from the correlation analysis and the granger causality test we find that the volatility and volatility spillovers are positively correlated and are two way granger causality which supported for the market infection hypothesis of king and wadhwani 1990

short and long run determinants of commodity price volatility to explain price volatility in the u s agricultural energy and metal futures markets we estimate a model of common and commodity specific high and low frequency factors by building on the spline garch model of engle and rangel 2008 a better model fit results from allowing the unconditional variance to slowly change over time moreover the persistence of volatility shocks is shown to be much weaker than what standard garch models imply combining the volatility results with monthly macroeconomic indicator data we find that decomposing realized volatility into high and low frequency components better reveals the impact of slowly evolving aggregate variables on price volatility moreover over the period 1990 2005 most of the macroeconomic variables had similar effects within the same commodity category e g grain but their effects differed across commodity groups e g grain versus livestock over the period 2006 2009 however commodity specific factors dominated common factors copyright 2013 oxford university press

spillover effects in energy futures markets price discovery in crude oil and refined oil products has been extensively undertaken in organised futures markets for over a decade now there are two dominant such markets today the first one in the new york mercantile exchange and the second in london s international petroleum exchange with the demise of opec as the leading price setter for crude and products nymex light sweet crude and brent crude have usurped the role of benchmark grades for price setting to date considerable work has been done to scrutinise the degree to which these two markets price efficiently but little with regard to the way the two markets interact participants in these markets move with relative ease from one market to the other and usually take positions in both of them it is of interest therefore to investigate the information transmission mechanism by looking at spillover effects and perhaps identify which market is the true price leader this paper is a first attempt to look at such a problem in the energy market although similar studies have been done on stock market indices it is found that substantial spillover effects do exist when both markets are trading simultaneously although ipe morning prices seem to be considerably affected by the close of the previous day on nymex q 2001 elsevier science b v all rights reserved

evolution of the world crude oil market integration a graph theory analysis this paper investigates the evolution of the world crude oil market and the pricing power for major oil producing and oil consuming countries using graph theory a minimal spanning tree for the world crude oil market is constructed and some empirical results are given the integration of the world crude oil market is verified furthermore the world crude oil market is characterised as a geographical and organisational structure the crude oil markets of adjacent countries or regions tend to link together while opec is well integrated we also found that the links in the south and north american region and the african region are relatively stable the crude oil markets in the u s angola and saudi arabia take up the core with a higher betweenness centrality and lower farness whereas the markets in the east and southeast asian countries are on the fringe finally the degree of globalisation for the world crude oil market is becoming further entrenched verified by a decreasing normalised tree length hence its systemic risk may increase due to the future uncertainty of world politics

a characterization of oil price behavior evidence from jump models abstract this paper is concerned with the statistical behavior of oil prices in two ways it firstly applies a combined jump garch model in order to characterize the behavior of daily weekly as well as monthly oil prices secondly it relates its empirical results to implications of hotelling type resource extraction models the empirical analysis shows that oil prices are characterized by garch as well as conditional jump behavior and that a considerable portion of the total variance is triggered by sudden extreme price movements this finding implies that first oil price signals are not reliable and as a consequence both finding optimal extraction paths and decisions regarding the transmission to alternative technologies are likely to be compromised second this behavior is in stark contrast to the notion of deterministic trends in the price of oil

volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory abstract this paper explores the relevance of asymmetry and long memory in modeling and forecasting the conditional volatility and market risk of four widely traded commodities crude oil natural gas gold and silver a broad set of the most popular linear and nonlinear garch type models is used to investigate this relevancy our in sample and out of sample results show that volatility of commodity returns can be better described by nonlinear volatility models accommodating the long memory and asymmetry features in particular the fiaparch model is found to be the best suited for estimating the var forecasts for both short and long trading positions this model also gives for all four commodities the lowest number of violations under the basel ii accord rule given a risk exposure at the 99 confidence level several implications for commodity market risks policy regulations and hedging strategies can be drawn from the obtained results

forecasting energy market volatility using garch models can multivariate models beat univariate models abstract in this paper we forecast energy market volatility using both univariate and multivariate garch class models first we forecast volatilities of individual assets and find that multivariate models display better performance than univariate models second we forecast crack spread volatility and contrast the performance of multivariate models for two underlyings with the alternative of univariate ones for crack spreads directly our evidence shows that univariate models allowing for asymmetric effects display the greatest accuracy we also discuss the hedging strategy based on multivariate models and its implications for market participants

good volatility bad volatility what drives the asymmetric connectedness of australian electricity markets efficient delivery of network services and the electricity infrastructure to meet the long term consumer s interests are the main objectives and the strategies of a national electricity market while the main interests of generators are to maximize their profit through pricing strategies therefore the objective of this study is to explore whether electricity prices across the four australian states display symmetric price volatility connectedness the study is the first attempt in the literature to make use of intraday 5 min australian dispatch electricity prices spanning the period december 8th 1998 to may 5th 2016 to quantify asymmetries in volatility connectedness emerging from good and bad volatility the results provide supportive evidence that the australian electricity markets are connected asymmetrically implying the presence of some degree of market power that is exercised by generators across regional electricity markets

optimal gasoline hedging strategies using futures contracts and exchange traded funds this article employs a variety of econometric models including ols vec var dcc garch and a class of copula based garch models to estimate optimal hedge ratios for gasoline spot prices using gasoline exchange traded funds etfs and gasoline futures contracts we then compare their performance using four different measures from the perspective of both their hedging objectives and trading position using four different measures variance reduction measure utility based measure and two tail based measures value at risk and expected shortfall the impact of the 2008 financial market crisis on hedging performance is also investigated our findings indicate that in terms of variance reduction the static models ols and vec var are found to be the best hedging strategies however more sophisticated time varying hedging strategies could outperform the static hedging models when the other measures are used in addition etf hedging is a more effective hedging strategy than futures hedging during the high

the internet and local wages a puzzle how did the diffusion of the internet affect regional wage inequality we examine the relationship between business investment in advanced internet technology and local variation in us wage growth between 1995 and 2000 we identify a puzzle the internet is widespread but the economic payoffs are not advanced internet technology is only associated with substantial wage growth in the 6 percent of counties that were already highly wealthy educated and populated and had it intensive industry advanced internet and wage growth appear unrelated elsewhere overall advanced internet explains over half the difference in wage growth between already well off counties and all others jel j31 l86 o33 r11 r23

modeling asymmetric comovements of asset returns existing time varying covariance models usually impose strong restrictions on how past shocks affect the forecasted covariance matrix in this article we compare the restrictions imposed by the four most popular multivariate garch models and introduce a set of robust conditional moment tests to detect misspecification we demonstrate that the choice of a multivariate volatility model can lead to substantially different conclusions in any application that involves forecasting dynamic covariance matrices like estimating the optimal hedge ratio or deriving the risk minimizing portfolio we therefore introduce a general model which nests these four models and their natural asymmetric extensions the new model is applied to study the dynamic relation between large and small firm returns article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies