the replacement problem abstract a prototypical vintage capital model of economic growth is developed where the decision to replace old technologies with new ones is modeled explicitly technological change is investment specific depreciation in this environment is an economic not a physical concept the vintage capital economy s balanced growth paths and transitional dynamics are analyzed the transitional dynamics are markedly different from the standard neoclassical growth model

the incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market abstract this paper aims to investigate whether investor fear gauge ifg contains incremental information content for forecasting the volatility of crude oil futures for this purpose we use oil volatility index ovx to measure the ifg adding the ifg to existing heterogeneous autoregressive har models we develop many har models with ifg subsequently we employ these har models to predict the volatility of crude oil futures the results from the parameter estimation and out of sample forecasting show that the in sample and out of sample performances of har models with ifg are significantly better than their corresponding har models without ifg the results are robust in different ways thus the har models with ifg are more beneficial to the decision making of all participants including financial traders manufacturers and policymakers in the crude oil futures market more importantly the results suggest that the investor fear gauge has a significant positive effect on volatility forecasting and can help improve the performances of almost all the existing har models

forecasting crude oil price volatility and value at risk evidence from historical and recent data abstract this paper adopts the markov switching multifractal msm model and a battery of generalized autoregressive conditional heteroscedasticity garch type models to model and forecast oil price volatility extending previous work by wei et al 2010 and wang et al 2016 we evaluate the forecasting performance of all these models via a superior predictive ability spa test we go beyond previous research by i considering oil price volatility in the nineteenth century along with recent data ii applying different types of msm models and iii considering value at risk predictions besides our forecasting of volatility confirming its successful performance in other studies the new msm model comes out as the model that most often across forecasting horizons and subsamples cannot be outperformed by other models this superiority also applies to forecasting of value at risk

productivity growth and environmental efficiency of the nonferrous metals industry an empirical study of china abstract this study intends to provide an insight into china s nonferrous metals industry production based on the analysis of the environmental efficiency the malmquist productivity index mpi and the malmquist luenberger productivity index mlpi the empirical experiment based on the annual data of 27 regions including provinces autonomous regions and municipalities of china during 2003 2009 shows the following results first the industry s environmental efficiency in the east area is mostly higher than that of the other area second the industry s average annual change of mpi and mlpi in china were 4 4 and 0 9 respectively this indicated that the total factor productivity growth of the industry was overestimated if undesirable outputs were ignored third the industry s productivity was mainly affected through technological advances rather than endogenous factors such as improvements in managerial practices finally during the worldwide financial crisis occurred in 2008 the industry s mlpis exceeded the mpis in most regions through measures such as adjustment of the product structure and elimination of backward production capacity

jumps and stochastic volatility in crude oil futures prices using conditional moments of integrated volatility we evaluate alternative models of the volatility of commodity futures prices based on high frequency intraday data from the crude oil futures markets for the october 2001 december 2012 period these models are implemented with a simple gmm estimator that matches sample moments of the realized volatility to the corresponding population moments of the integrated volatility models incorporating both stochastic volatility and jumps in the returns series are compared on the basis of the overall fit of the data over the full sample period and subsamples we also find that jumps in the returns series add to the accuracy of volatility forecasts

tracking mercury emission flows in the global supply chains a multi regional input output analysis abstract mercury emissions from nonferrous metal production have overtaken that from energy consumption as the leading contributor of global anthropogenic mercury emissions though minamata convention has put restrictions on import or export of mercury added products the inter connected global economy that features an intensive correlated supply chain still has large impacts on mercury emissions therefore this study aims to track global nonferrous metal related mercury emission flows among 186 individual economies for the year of 2010 by applying an empirically validated multi regional input output mrio model the total amount of direct mercury emissions is 974 tonnes to which gold production contributed a dominant proportion however a spectacular 2 3 of mercury emissions from nonferrous metal production were traded internationally primarily as exports from emerging economies such as mainland china and colombia to wealthy economies including the usa and germany through global supply chains understanding the redistribution of mercury emissions along the global supply chains can facilitate international efforts to reduce mercury emissions from nonferrous metal production

equipment investment and growth in developing countries abstract differences in equipment investment or equipment prices account for large variations in growth rates across countries an important task is to understand the economic mechanism underlying the equipment growth nexus and its policy implications in order to study this issue this paper develops a model in which growth is driven by the adoption of technologies that are embodied in equipment i show that this model can quantitatively account for the observed cross country relationships between equipment investment equipment prices and growth i find that the competitive equilibrium is characterized by inefficiently low levels of learning and too slow growth and study which policies are able to remedy this inefficiency

answering the skeptics yes standard volatility models do provide accurate forecasts a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using arch and stochastic volatility models while most of these studies have documented highly significant in sample parameter estimates and pronounced intertemporal volatility persistence traditional ex post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts contrary to this contention we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications new methods for improved ex post interdaily volatility measurements based on high frequency intradaily data are also discussed

analytical evaluation of volatility forecasts estimation and forecasting for realistic continuous time stochastic volatility models is hampered by the lack of closed form expressions for the likelihood in response andersen bollerslev diebold and labys econometrica 71 2003 579 625 advocate forecasting integrated volatility via reduced form models for the realized volatility constructed by summing high frequency squared returns building on the eigenfunction stochastic volatility models we present analytical expressions for the forecast efficiency associated with this reduced form approach as a function of sampling frequency for popular models like garch multifactor affine and lognormal diffusions the reduced form procedures perform remarkably well relative to the optimal infeasible forecasts

vintage capital and the dynamics of the ak model this paper analyzes the equilibrium dynamics of an ak type endogenous growth model with vintage capital the inclusion of vintage capital leads to oscillatory dynamics governed by replacement echoes which additionally influence the intercept of the balanced growth path these features which are in sharp contrast to those from the standard ak model can contribute to explaining the short run deviations observed between investment and growth rates time series to characterize the optimal solutions of the model we develop analytical and numerical methods that should be of interest for the general resolution of endogenous growth models with vintage capital

interaction among china carbon emission trading markets nonlinear granger causality and time varying effect abstract china makes great efforts to reduce carbon emissions and mitigate global greenhouse gas in order to identify the interaction among china cet markets this paper comprehensively investigates nonlinear granger causality and time varying effect in markets by using the hiemstra and jones hj test diks and panchenko dp test and time varying parameter structure vector autoregressive tvp svar model the empirical analysis has demonstrated china major cet markets significantly bidirectional nonlinear granger cause each other as to time varying effect we have obtained convincing findings that time varying impulse responses are among china major cet markets in the short term specifically guangdong hubei and shenzhen cet markets are time varying co movement negatively or positively related to each other over time implying there are deep bases for china national cet market construction furthermore the specific time point impulse effects support our discoveries in time varying impulse responses

multi scale dependence structure and risk contagion between oil gold and us exchange rate a wavelet based vine copula approach abstract this study makes a systemic analysis of dependence and risk contagion among oil gold and the us dollar foreign exchange us fx markets employing the wavelet method and a time varying tri variate vine copula model compared to previous research our empirical findings not only reveal the impact of co variate instead of pairwise analysis but also reveal the patterns of heterogeneity influence in different time horizons both dynamic average dependence and tail dependence show that the three assets are better integrated in the medium run time scales than the short run time scales whereby us fx connects the three assets in the short term while gold does so in the medium term all three multi variate scenarios show that risk contagion is temporal at different time scales the oil market was found to be more sensitive to the upside and downside risk contagion of the gold market in the short run time scales and vice versa asymmetry also shows that both the us fx and gold market are more sensitive to upside and downside risk contagion in the medium run time scales

organizational capital learning by doing and investment volatility this paper addresses the issue of plant level investment volatility in the context of a purely convex model where fluctuations are driven by technological shocks the aim is to assess the role of learning by doing in reproducing the well documented non smooth investment dynamics at the plant level instead of relying on typical non convexities fixed costs or indivisibilities used to account for lumpy investment behavior the concept of organizational capital is essential in the analysis and it provides the channel through which learning affects production our results indicate that learning by doing constitutes a potentially important source of investment volatility at the plant level and that one should not believe that convex models of investment necessarily deliver smooth dynamics

the economics of has beens the evolution of technology causes human capital to become obsolete we study this phenomenon in an overlapping generations setting assuming that technology evolves stochastically and that older workers find updating uneconomic experience and learning by doing may offer the old some income protection but technology advance always turns them into has beens to some degree we focus on the determinants demand elasticities persistence of technology change etc of the severity of the has beens effect it can be large even leading to negatively sloped within occupation age earnings profiles and an occupation dominated by a few young high income workers architecture displays the sort of features the theory identifies as magnifying the has beens effect and both anecdotes and some data suggest that the has beens effect in architecture is extreme indeed

technology adoption learning by doing and economic growth abstract we develop a model in which firms choose which technologies to adopt as well as the timing of such adoptions in between adoptions a firm accumulates expertise in its technology which allows it to operate the technology more efficiently thus there is firm specific learning by doing for certain parameterizations of the model and appropriate initial distributions of technologies and expertise equilibria are characterized by positive and constant growth of per capita output and positive but nonconstant growth of each firm s output we find firms adoption decisions and output growth depend upon the efficiency of capital markets journal of economic literature classification numbers o41 o33

path dependence endogenous innovation and growth the article presents a model of endogenous innovation and growth in which technological change is path dependent the historical pattern of technological development plays a central role in determining the pace of future technological change path dependence is explained using a distinction between fundamental and secondary knowledge the economy moves endogenously between periods of drastic and nondrastic innovation technological lock in is shown to be a special case of path dependence the model provides a rationale for cycles in technological leadership this rationale exists in equilibria with positive levels of fundamental research and in a world with no imitation

forecasting volatility of the u s oil market abstract we examine the information content of the cboe crude oil volatility index ovx when forecasting realized volatility in the wti futures market additionally we study whether other market variables such as volume open interest daily returns bid ask spread and the slope of the futures curve contain predictive power beyond what is embedded in the implied volatility in out of sample forecasting we find that econometric models based on realized volatility can be improved by including implied volatility and other variables our results show that including implied volatility significantly improves daily and weekly volatility forecasts however including other market variables significantly improves daily weekly and monthly volatility forecasts

disruption costs learning by doing and technology adoption abstract we study technology adoption in a dynamic model of price competition adoption involves disruption costs and learning by doing because of disruption costs the adopting firm begins in a market disadvantage which may persist if its rival captures the customers that the adopting firm needs to learn the technology the prospect of future rents by the rival results in i a failure to adopt socially efficient technologies ii an equilibrium preference for technologies that are learned faster but have lower social value and iii more technologies being adopted if more firms enter the market

discrete time volatility forecasting with persistent leverage effect and the link with continuous time volatility modeling we first propose a reduced form model in discrete time for s p 500 volatility showing that the forecasting performance can be significantly improved by introducing a persistent leverage effect with a long range dependence similar to that of volatility itself we also find a strongly significant positive impact of lagged jumps on volatility which however is absorbed more quickly we then estimate continuous time stochastic volatility models that are able to reproduce the statistical features captured by the discrete time model we show that a single factor model driven by a fractional brownian motion is unable to reproduce the volatility dynamics observed in the data while a multifactor markovian model fully replicates the persistence of both volatility and leverage effect the impact of jumps can be associated with a common jump component in price and volatility this article has online supplementary materials

role of oil price shocks on macroeconomic activities an svar approach to the malaysian economy and monetary responses abstract this study examines the impact of oil price uncertainty on malaysian macroeconomic activities and monetary responses we use a structural var svar model based on monthly data over the period 1986 2009 the egarch model estimates show an important asymmetric effect of oil price shocks on the conditional oil price volatility dynamic impulse response functions obtained from the svar model show a prolonged dampening effect of oil price volatility shock on malaysian industrial production we also find that levels of consumer price index cpi decline with a positive shock to oil price uncertainty this is the result of negative demand shock due to the postponement of consumption of big ticket items by individuals households and other sectors of the economy we also found that the malaysian central bank adopts an expansionary monetary policy in response to oil price uncertainty variance decomposition analysis reconfirms that volatility in the oil price is the second most important factor to explain the variance of industrial production after its own shocks these results shed some light on how the central bank of malaysia can use controlling mechanisms to stabilize aggregate output and price level

roughing it up including jump components in the measurement modeling and forecasting of return volatility a rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high frequency returns coupled with simple modeling procedures building on recent theoretical results in barndorff nielsen and shephard 2004a 2005 for related bi power variation measures the present paper provides a practical and robust framework for non parametrically measuring the jump component in asset return volatility in an application to the dm exchange rate the s p500 market index and the 30 year u s treasury bond yield we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process moreover many jumps appear directly associated with specific macroeconomic news announcements separating jump from non jump movements in a simple but sophisticated volatility forecasting model we find that almost all of the predictability in daily weekly and monthly return volatilities comes from the non jump component our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling forecasting and pricing the continuous and jump components of the total return variation process

vintage human capital and learning curves abstract i study a vintage human capital model in which long lived workers accumulate human capital following an exogenous learning curve different skill levels inside a vintage are complementary in production this makes the ex ante homogeneous workers enter different vintages the continuous time framework allows me to study the timing decision for the technology phase out differentially and to derive sharp characterization for wages and the distribution of workers in the dying technology i show how to posit and solve a planner s problem and construct equilibrium in this way consistent with empirical evidence i show that the experience premium is always positive but diminishes as a technology ages the connection between workers learning curves and the technology s progress curve is characterized

does productivity growth fall after the adoption of new technology abstract a number of theoretical models of technology adoption have been proposed that imply that measured productivity growth may initially fall and then later rise after the adoption of a new technology this paper investigates whether or not this implication is a feature of plant level data from the colombian manufacturing sector we focus on technology adoption embodied in new equipment we find evidence that the effect of a large equipment purchase is initially to reduce plant level total factor productivity growth

dynamic spillovers among major energy and cereal commodity prices abstract over the past decade the sharp increases in the prices of oil and agricultural commodities have raised serious concerns about the heightened volatility of these markets and the possible negative interactions between them this article deals with the dynamic return and volatility spillovers across international energy and cereal commodity markets it also examines the impacts of three types of opec news announcements on the volatility spillovers and persistence in these markets for this purpose we make use of the var bekk garch and var dcc garch models for the daily spot prices of eight major commodities including wti oil europe brent oil gasoline heating oil barley corn sorghum and wheat our results provide evidence of significant linkages between these energy and cereal markets moreover the opec news announcements are found to exert influence on the oil markets as well as on the oil cereal relationships finally we show that the persistence of volatility decreases increases for the crude oil and heating oil gasoline returns after accounting for the opec announcements in these multivariate garch models however the results are more mixed for the cereal markets overall our results can be used to improve the risk adjusted performance by having more diversified portfolios and also serve to hedge the oil risk more effectively

asymmetric impacts of oil price uncertainty on chinese stock returns under different market conditions evidence from oil volatility index abstract the crude oil volatility index ovx is a direct and more accurate measure of oil price uncertainty this paper uses this kind of implied volatility index of oil prices to investigate the impacts of oil price uncertainty on the aggregate and sectoral stock returns in china this issue is resolved by using a quantile regression which can provide a more detailed examination under different market conditions meanwhile the asymmetric effects of uncertainty shocks are also examined by using the positive and negative changes of the ovx furthermore we assess whether the reform of march 27 2013 affected the ovx stock nexus since this reform was a major step to relax the control of domestic oil prices in china our results reveal that ovx changes mainly show significantly negative effects on the aggregate and sectoral stock returns in the bearish market in particular these effects depend largely on the positive shocks of the ovx rather than the negative shocks of the ovx moreover the reform of march 27 2013 decreased the impacts of the positive ovx shocks on chinese stock returns

a comparison of the effects of exogenous oil supply shocks on output and inflation in the g7 countries a comparison of the effects of exogenous shocks to global crude oil production on seven major industrialized economies suggests a fair degree of similarity in the real growth responses an exogenous oil supply disruption typically causes a temporary reduction in real gdp growth that is concentrated in the second year after the shock inflation responses are more varied the median cpi inflation response peaks after three to four quarters exogenous oil supply disruptions need not generate sustained inflation or stagflation typical responses include a fall in the real wage higher short term interest rates and a depreciating currency with respect to the dollar despite many qualitative similarities there is strong statistical evidence that the responses to exogenous oil supply disruptions differ across g7 countries for suitable subsets of countries homogeneity cannot be ruled out a counterfactual historical exercise suggests that the evolution of cpi inflation in the g7 countries would have been similar overall to the actual path even in the absence of exogenous shocks to oil production consistent with a monetary explanation of the inflation of the 1970s there is no evidence that the 1973 1974 and 2002 2003 oil supply shocks had a substantial impact on real growth in any g7 country whereas the 1978 1979 1980 and 1990 1991 shocks contributed to lower growth in at least some g7 countries jel e31 e32 q43

forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models this paper extends previous studies by investigating the relevance of structural breaks and long memory in modeling and forecasting the conditional volatility of oil spot and futures prices using a variety of garch type models our results can be summarized as follows first we provide evidence of parameter instability in five out of nine garch based conditional volatility processes for energy prices second long memory is effectively present in all the series considered and a figarch model seems to better fit the data but the degree of volatility persistence diminishes significantly after adjusting for structural breaks finally the out of sample analysis shows that volatility models accommodating instability and long memory characteristics of the data provide the best volatility forecasts for most cases

the impact of energy trade patterns on co2 emissions an emergy and network analysis abstract fossil fuel is considered to be the major cause of co2 emissions and it flows across countries through the international energy trade in this paper we analyse the impact of energy trade patterns on co2 emissions for a global sample from 2000 to 2014 we construct an international fossil fuel trade network based on emergy theory and calculate some corresponding structural parameters then we systematically evaluate the impact of energy trade on co2 emissions from the trade volume and trade relationships perspectives we obtain the following results 1 trade strength mainly affects co2 emissions through the scale effect composition effect and technique effect 2 trade security and trade centre status of one country will significantly affect co2 emissions 3 for high economic level he countries concentrating the trade volume on several finite countries will destroy the environment low economic level le countries that are proximal to the important countries of the energy market will experience an increase in pollution this research also discusses some implications for policy makers

a nonparametric garch model of crude oil price return volatility the use of parametric garch models to characterise crude oil price volatility is widely observed in the empirical literature in this paper we consider an alternative approach involving nonparametric method to model and forecast oil price return volatility focusing on two crude oil markets brent and west texas intermediate wti we show that the out of sample volatility forecast of the nonparametric garch model yields superior performance relative to an extensive class of parametric garch models these results are supported by the use of robust loss functions and the hansen s 2005 superior predictive ability test the improvement in forecasting accuracy of oil price return volatility based on the nonparametric garch model suggests that this method offers an attractive and viable alternative to the commonly used parametric garch models

a data envelopment analysis based framework for the relative performance evaluation of competing crude oil prices volatility forecasting models abstract forecasts of crude oil prices volatility are important inputs to many decision making processes in application areas such as macroeconomic policy making risk management options pricing and portfolio management despite the fact that a large number of forecasting models have been designed to forecast crude oil prices volatility so far the relative performance evaluation of competing forecasting models remains an exercise that is unidimensional in nature to be more specific most studies tend to use several criteria and their measures to assess the relative performance of these models but competing models are always ranked by performance measure thus leading in general to different rankings for different criteria and to a situation where one cannot make an informed decision as to which model performs best with respect to all criteria under consideration the purpose of this paper is to propose a single ranking that takes account of several criteria using a data envelopment analysis framework our empirical results reveal that the unidimensional rankings for different criteria might differ significantly and that the multidimensional ranking of some models could be substantially different from their unidimensional rankings which highlights the importance of the proposed performance evaluation tool

the interaction between food prices and oil prices this paper provides a statistical methodology to estimate the impact of oil price uncertainty on food prices in doing so it examines the joint impact of oil price and food price uncertainties and their correlation on the food price also the theoretical model was applied to the oil based trinidad and tobago and the empirical results confirm the theoretical predictions the empirical results indicate that a higher oil price increases food price also a higher oil price volatility yields a higher food price moreover an increase in the oil supply reduces the food price

oil price dynamics 2002 2006 abstract oil price dynamics during 2002 2006 have been characterized by high volatility high intensity jumps and strong upward drift and were concomitant with underlying fundamentals of oil markets and world economy namely pressure on oil prices resulting from rigid crude oil supply and expanding world demand for crude oil a change in the oil price process parameters would require a change in underlying fundamentals market expectations extracted from call and put option prices anticipated no change in underlying fundamentals in the short term markets expected oil prices to remain volatile and jumpy and with higher probabilities to rise rather than fall above the expected mean

how to effectively estimate the time varying risk spillover between crude oil and stock markets evidence from the expectile perspective abstract with the integration and financialization of world economy massive hot money has frequently flowed between crude oil and stock markets and has brought significant extreme risks and their spillover for this reason this paper develops the arch expectile model with embedded conditional autoregressive structure namely car arche model and expectile based var evar approach and investigates the time varying risk spillover between wti futures market and us uk japanese and global stock markets respectively the results indicate that for one thing the evar approach based on car arche model is more adequate than the conventional quantile based var qvar approach based on ged garch for wti and stock markets which is due to the evident advantages of expectile compared to quantile for another the unidirectional downside risk spillover effects from wti to the four stock markets and vice versa are only remarkable during major events and present variations with jumps but the bidirectional downside risk spillover effects between them are significant for each time point during the in sample period which indicate that the simultaneous risk spillover between wti and stock markets are fairly pronounced

volatility in crude oil futures a comparison of the predictive ability of garch and implied volatility models the wti future contract quoted at the nymex is the most actively traded instrument in the energy sector this paper compares the predictive ability of two approaches which can be used to forecast volatility garch type models where forecasts are obtained after estimating time series models and an implied volatility model where forecasts are obtained by inverting one of the models used to price options although the main scope of the research discussed here is to evaluate which model produces the best forecast of volatility for the wti future contract evaluated according to statistical and regression based criteria we also investigate whether volatility of the oil futures are affected by asymmetric effects whether parameters of the garch models are influenced by the distribution of the errors and whether allowing for a time varying long run mean in the volatility produces any improvement on the forecast obtained from garch models

experience vs obsolescence a vintage human capital model abstract i introduce endogenous human capital accumulation into an infinite horizon version of chari and hopenhayn s 1991 4 vintage human capital model returns to skill and tenure premia are highest in young vintages where skill is scarcest and agents accumulate human capital fastest as the vintage ages the skill premium decreases and vanishes entirely upon vintage death workers run through cycles of human capital accumulation their wages rise as they accumulate skill undergo downward pressure as the technology ages and finally drop sharply when the worker switches to a new technology the results are in line with german linked employer employee data tenure premia are highest in young establishments as well as in fast growing industries occupations and establishments a calibration exercise suggests that human capital accumulation is the most important determinant of workers wage profiles whereas changes to the price of skill and vintage productivity gains play a smaller quantitative role

modeling and forecasting crude oil markets using arch type models this study investigates the time varying volatility of two major crude oil markets the west texas intermediate wti and europe brent a flexible autoregressive conditional heteroskedasticity arch model is used to take into account the stylized volatility facts such as clustering volatility asymmetric news impact and long memory volatility among others the empirical results indicate that the intensity of long persistence volatility in the wti is greater than in the brent it is also found that for the wti the appreciation and depreciation shocks of the wti have similar impact on the resulting volatility however a leverage effect is found in brent although both the estimation and diagnostic evaluations are in favor of an asymmetric long memory arch model only the wti models provide superior in the out of sample forecasts on the other hand from the empirical out of sample forecasts it appears that the simplest parsimonious generalized arch provides the best forecasted evaluations for the brent crude oil data

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

modelling futures price volatility in energy markets is there a role for financial speculation this paper models volatility in four energy futures markets adopting garch models the variance equation is enriched with alternative measures of speculation based on cftc data the market share of non commercial traders the working s t index and the percentage of net long positions of non commercials over total open interest in future markets it also includes a control for market liquidity we consider four energy commodities light sweet crude oil heating oil gasoline and natural gas over the period 2000 2014 analysed at weekly frequency we find that speculation presents a negative and significant sign the robustness exercise shows that i results remain unchanged through different model specifications garch in mean egarch and tarch ii results are robust to different specifications of the mean and variance equation

risk assessment of oil price from static and dynamic modelling approaches 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

commodity and equity markets some stylized facts from a copula approach abstract in this paper we propose to identify the dependence structure that exists between returns on equity and commodity futures and its development over the past 20 years the key point is that we do not impose any dependence structure but let the data select it to do so we model the dependence between commodity metal agriculture and energy and stock markets using a flexible approach that allows us to investigate whether the co movement is i symmetrical and frequent ii a symmetrical and mostly present during extreme events and iii asymmetrical and mostly present during extreme events we also allow for this dependence to be time varying from january 1990 to february 2012 our analysis uncovers three major stylised facts first we find that the dependence between commodity and stock markets is time varying symmetrical and occurs most of the time as opposed to mostly during extreme events second not allowing for time varying parameters in the dependence distribution generates a bias towards an evidence of tail dependence similarly considering only tail dependence may lead to false evidence of asymmetry third a growing co movement between industrial metals and equity markets is identified as early as 2003 this co movement spreads to all commodity classes and becomes unambiguously stronger with the global financial crisis after fall 2008

learning by drilling interfirm learning and relationship persistence in the texas oilpatch author s kellogg ryan m abstract production in many industries such as construction and heavy manufacturing relies on inputs from both lead firms and contractors these firms joint productivity often hinges on their ability to share information and coordinate activities suggesting that they have strong incentives to learn about each other s personnel procedures and expertise this learning differs from standard learning by doing in that it is relationship specific its benefits are not appropriable outside the relationship in which the learning takes place in this paper i empirically examine the importance of relationship specific learning using high frequency data from oil and gas drilling i find that the joint productivity of a lead firm and its drilling contractor is enhanced significantly as they accumulate experience working together this result is robust to other relationship specificities i also find that firms appear to recognize the benefits of joint experience controlling for other specificities lead firms are more likely to work with contractors with which they have substantial prior experience than those with which they have worked relatively little

the pass through effects of oil price shocks on china s inflation a time varying analysis abstract using a time varying parameter structural vector autoregression with stochastic volatility tvp svar sv model we decompose the structural shocks of oil price fluctuations into four types oil supply shocks global demand shocks domestic demand shocks and oil specific demand shocks we then analyze the time varying effects of these oil price shocks on china s inflation at the import production and consumption stages using monthly data from january 1999 to december 2016 the results show that the pass through effects of the four types of oil price shocks on china s inflation at each stage are time varying and that there are significant differences at different time horizons and points in time the analysis of the variance decomposition shows that the effects of oil price shocks on china s inflation at each stage are incomplete and decrease along the price chain the increase in oil prices driven by oil specific demand shocks is the most important cause of china s inflation at the import and production stages during the full sample period while china s inflation at the consumption stage is mainly affected by domestic demand shocks in addition the inflationary effects of oil price shocks have been dramatically weaker since the international financial crisis compared with before the crisis

the impacts of nonferrous metal price shocks on the macroeconomy in china from the perspective of resource security abstract in recent years the price of international nonferrous metals has undergone drastic fluctuations which could exert significant shock effects on macroeconomic variables based on the perspective of resource security this paper reveals the relationship between the nonferrous metal price shocks and china s macroeconomic variables by establishing a dynamic stochastic general equilibrium dsge model embedded with nonferrous metal consumption and means of production blocks the model is based on the optimal decision making behaviours of three departments that satisfy multiple constraints to realize optimal policy making furthermore the structural vector autoregression svar method is applied to verify the shock effects of nonferrous metal price and obtain more robust results the bayesian results show that there is consistency among nonferrous metal price shocks consumer reference shocks wage bonus shocks technical shocks and price adjusted shocks the impulse response function results indicate that the stimulation of an international nonferrous metal price increase would have significant positive impacts on the macroeconomic variables of investment money supply consumption and total output but negative effects on labour demand in addition the impulse responses of wage levels and the rate of inflation to nonferrous metal price shocks present obvious lagging effects

solving optimal growth models with vintage capital the dynamic programming approach this paper deals with an endogenous growth model with vintage capital and more precisely with the ak model proposed in r boucekkine o licandro l a puch f del rio vintage capital and the dynamics of the ak model j econ theory 120 1 2005 39 72 in endogenous growth models the introduction of vintage capital allows to explain some growth facts but strongly increases the mathematical difficulties so far in this approach the model is studied by the maximum principle here we develop the dynamic programming approach to the same problem by obtaining sharper results and we provide more insight about the economic implications of the model we explicitly find the value function the closed loop formula that relates capital and investment the optimal consumption paths and the long run equilibrium the short run fluctuations of capital and investment and the relations with the standard ak model are analyzed finally the applicability to other models is also discussed

the optimal timing of adoption of a green technology we study the optimal timing of adoption of a cleaner technology and its effects on the rate of growth of an economy in the context of an ak endogenous growth model we show that the results depend upon the behavior of the marginal utility of environmental quality with respect to consumption when it is increasing we derive the capital level at the optimal timing of adoption we show that this capital threshold is independent of the initial conditions on the stock of capital implying that capital poor countries tend to take longer to adopt also country specific characteristics as the existence of high barriers to adoption may lead to different capital thresholds for different countries if the marginal utility of environmental quality decreases with consumption a country should never delay adoption the optimal policy is either to adopt immediately or if adoption costs are too high to never adopt the policy implications of these results are discussed in the context of the international debate surrounding the environmental political agenda

oil and the macroeconomy since the 1970s economists have long been intrigued by empirical evidence that suggests that oil price shocks may be closely related to macroeconomic performance this interest dates back to the 1970s the 1970s were a period of growing dependence on imported oil unprecedented disruptions in the global oil market and poor macroeconomic performance in the united states thus it was natural to suspect a causal relationship from oil prices to u s macroeconomic aggregates since then a large body of work has accumulated that purports to establish this link on theoretical grounds and to provide empirical evidence in its support we do not attempt a comprehensive survey of this literature but rather provide an idiosyncratic synthesis of what we view as the key issues in this debate and the insights gained over the last 30 years the timing seems right for such an account although the experience of the 1970s continues to play an important role in discussions of the link between oil and the macroeconomy there have been a number of new oil price shocks since the 1970s notably the 1986 collapse of oil prices and the 2000 boom in oil prices as well as the oil price increases associated with the 1990 1991 gulf war and the 2003 iraq war given this richer case history we are arguably in a better position than two decades ago to distinguish the idiosyncratic features of each oil crisis from the systematic effects increases in oil prices have been held responsible for recessions periods of excessive inflation reduced productivity and lower economic growth in this paper we review the arguments supporting such views first we highlight some of the conceptual difficulties in assigning a central role to oil price shocks in explaining

interaction between oil and us dollar exchange rate nonlinear causality time varying influence and structural breaks in volatility abstractthis article examines the nonlinear granger causality and time varying influence between crude oil prices and the us dollar usd exchange rate using the hiemstra and jones hp test the diks and panchenko dp test and the time varying parameter structural vector autoregression model by applying the iterated cumulative sums of squares icss algorithm and the dcc garch model the effects of structural breaks in volatility of the two markets are also investigated the empirical analysis indicates that first crude oil prices are the nonlinear granger cause of the usd exchange rate but not vice versa second the usd exchange rate exerts a stronger and more stable negative influence on crude oil prices in the short term and the influence gradually weakens after 2012 finally ignoring structural breaks can increase the negative volatility correlation between the oil and usd exchange rate markets which is particularly remarkable during the financial crisis

investment age and dynamic productivity growth in the spanish food processing industry this article analyzes the relation between investment age measured as the number of years since investment spike and dynamic productivity growth and its components which include dynamic technical change dynamic inefficiency change and dynamic scale inefficiency change the empirical application focuses on firm level data for the spanish food processing industry covering the period from 1996 to 2011 this investigation of the impact of firms investment decisions on productivity growth employs a dynamic production framework and analyzes the impact of these decisions on the components of dynamic productivity growth our findings show that dynamic productivity growth is negatively affected by investment spikes in both the meat processing and oils and fats industries and that dynamic inefficiency change initially falls just after the infusion of large investment for oils and fats firms but then grows as the firms acquire experience with this investment we further find that investment spikes lead to improvements in dynamic technical change and worsening in dynamic technical inefficiency change in the meat processing industry while dynamic scale inefficiency change was negatively impacted in both industries

forecasting volatility in the biofuel feedstock markets in the presence of structural breaks a comparison of alternative distribution functions abstract the need for research on commodity volatility has grown considerably due to the important role and financialization of commodities in global asset markets this paper examines the volatility forecasting performance of a wide variety of garch based models in the context of biofuel feedstock markets in the presence of structural breaks our sample is also extended to several non renewable energy commodities to evaluate comparatively the volatility forecasting performance across various commodity markets the model specifications allow for different conditional distribution functions in the rolling window estimations a break detection algorithm finds significant evidence of structural breaks in the unconditional variance of all commodity returns under study the out of sample analysis which is based on an up to date model comparison testing procedure reveals that volatility models accommodating structural breaks in the data provide the best volatility forecasts for most cases regarding the relevance of distribution functions the skewed normal distribution dominates in the model confidence sets nevertheless the complex distribution functions do not always outperform simpler ones although true return distribution is asymmetric and heavy tailed

news good or bad and its impact on volatility predictions over multiple horizons we examine whether the sign and magnitude of intra daily returns have impact on expected volatility the next day or over longer future horizons we first let the data speak namely with minimal interference we capture the mapping between intra daily returns and future volatility we revisit the concept of news impact curves introduced by engle and ng 1993 overall we find that moderately good intra daily news reduces volatility the next day while both very good news unusual high intra daily positive returns and bad news negative returns increase volatility with the latter having a more severe impact the asymmetries disappear over longer horizons we also introduce a new class of parametric models which feature asymmetries and with close ties to arch type models albeit applicable to a mixture of high and low frequency data models featuring asymmetries dominate especially during the 2007 2008 financial crisis

technical change and irreversible investment under risk abstract a stochastic dynamic model was constructed to analyze investment decisions of an individual farmer under risk in the presence of irreversibilities embedded technical change and indivisible capital an analytical solution was obtained and its local behavior studied by numerical methods optimal investment is obtained by regulating the difference between the desired and actual capital stocks between two barriers that define an inaction interval while the desired capital drifts between the barriers no action is taken if the desired capital touches the upper barrier the farmer invests pushing the average efficiency of the actual capital stock up this in turn raises the desired capital even higher and contracts the inaction interval if these effects are strong enough the farmer will invest again until the potential gains of the technological package are exhausted if the desired capital falls enough the farmer disinvests pushing down the average productivity and expanding the inaction interval disinvestment continues until it stops either because the inaction interval becomes so wide that it is no longer optimal to disinvest or because the actual capital stock is so small that it is no longer profitable to produce

forecasting crude oil market volatility further evidence using garch class models abstract this paper extends the work of kang et al 2009 we use a greater number of linear and nonlinear generalized autoregressive conditional heteroskedasticity garch class models to capture the volatility features of two crude oil markets brent and west texas intermediate wti the one five and twenty day out of sample volatility forecasts of the garch class models are evaluated using the superior predictive ability test and with more loss functions unlike kang et al 2009 we find that no model can outperform all of the other models for either the brent or the wti market across different loss functions however in general the nonlinear garch class models which are capable of capturing long memory and or asymmetric volatility exhibit greater forecasting accuracy than the linear ones especially in volatility forecasting over longer time horizons such as five or twenty days

optimal regime switching under risk aversion and uncertainty abstract technology adoption is key for corporate strategy often determining the success or failure of a company as a whole however risk aversion often raises the reluctance to make a timely technology switch particularly when this entails the abandonment of an existing market regime and entry in a new one consequently which strategy is most suitable and the optimal timing of regime switch depends not only on market factors such as the definition of the market regimes as well as economic and technological uncertainty but also on attitudes towards risk therefore we develop a utility based regime switching framework for evaluating different technology adoption strategies under price and technological uncertainty we assume that a decisionmaker may invest in each technology that becomes available compulsive or delay investment until a new technology arrives and then invest in either the older laggard or the newer technology leapfrog our results indicate that if market regimes are asymmetric then greater risk aversion and price uncertainty in a new regime may accelerate regime switching in addition the feasibility of a laggard strategy decreases increases as price uncertainty in an existing new regime increases finally although risk aversion typically favours a compulsive and a laggard strategy a leapfrog strategy may be feasible under risk aversion provided that the output price and the rate of innovation are sufficiently high

the impact of international price shocks on china s nonferrous metal companies a case study of copper copper is one of the most important nonferrous metals for modern society which should be utilized in a sustainable way because of its non renewable nature this paper addresses the relationship between price shocks from the international copper market and china s listed copper companies international copper market price shocks are disentangled into supply shocks aggregate demand shocks and specific demand shocks using the structural vector autoregression method then the asymmetric impact of those shocks on the stock prices of china s listed copper companies is examined the results indicate that demand shocks are the dominant factor influencing copper price fluctuations with their impact on stock prices being significantly higher than those of supply shocks in the long run supply shocks and demand shocks both have significant asymmetric impacts on stock prices while in the short run specific demand shocks have an asymmetric impact on stock prices

oil prices speculation and fundamentals interpreting causal relations among spot and futures prices abstract a consensus that the world oil market is unified begs the question where do innovations in oil prices enter the market here we investigate where changes in the price of crude oil originate and how they spread by examining causal relationships among prices for crude oils from north america europe africa and the middle east on both spot and futures markets results indicate that innovations first appear in spot prices for dubai fateh and spread to other spot and futures prices while other innovations first appear in the far month contract for west texas intermediate and spread to other exchanges and contracts links between spot and futures markets are relatively weak and this may have allowed the long run relationship between spot and future prices to change after september 2004 together these results suggest that market fundamentals initiated a long term increase in oil prices that was exacerbated by speculators who recognized an increase in the probability that oil prices would rise over time

unspanned stochastic volatility and the pricing of commodity derivatives commodity derivatives are becoming an increasingly important part of the global derivatives market here we develop a tractable stochastic volatility model for pricing commodity derivatives the model features unspanned stochastic volatility quasi analytical prices of options on futures contracts and dynamics of the futures curve in terms of a low dimensional affine state vector we estimate the model on nymex crude oil derivatives using an extensive panel data set of 45 517 futures prices and 233 104 option prices spanning 4082 business days we find strong evidence for two predominantly unspanned volatility factors jel g13

oil shocks competition and corporate investment evidence from china abstract this paper aims to investigate the impact of three classical oil shocks on the chinese corporate investment by using firm level data moreover we assess the role of product market competition in the relationship between oil shocks and corporate investment our empirical results show that oil aggregate demand and specific demand shocks negatively affect corporate investment while oil supply shocks show a positive effect notably compared to the non energy related industry the corporate investment of energy related industry is more sensitive to these oil shocks furthermore we find high competitive pressure can mitigate the impact of oil specific demand shocks on the corporate investment of energy related industry but competition presents a limited effect on the relationship between other oil shocks and corporate investment

learning by doing and the choice of technology the role of patience if agents learn by doing and are myopic less advanced firms might adopt new technologies while more advanced firms would stick with the old technology this kind of overtaking can also occur if agents are forward looking and have high discount rates however overtaking never occurs if agents are sufficiently patient a finite discount rate increases the set of states at which agents adopt new technologies so more patient agents tend to upgrade their technology more frequently journal of economic literature classification numbers d92 o14 o33

forecasting the volatility of crude oil futures using intraday data abstract we use the information in intraday data to forecast the volatility of crude oil at a horizon of 1 66 days using a variety of models relying on the decomposition of realized variance in its positive or negative semivariances part and its continuous or discontinuous part jumps we show the importance of these decompositions in predictive in sample regressions using a number of specifications nevertheless an important empirical finding comes from an out of sample analysis which unambiguously shows the limited interest of considering these components overall our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance

good volatility bad volatility signed jumps and the persistence of volatility abstract using estimators of the variation of positive and negative returns realized semivariances and high frequency data for the s p 500 index and 105 individual stocks this paper sheds new light on the predictability of equity price volatility we showthat future volatility is more strongly related to the volatility of past negative returns than to that of positive returns and that the impact of a price jump on volatility depends on the sign of the jump with negative positive jumps leading to higher lower future volatility we show that models exploiting these findings lead to significantly better out of sample forecast performance

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

investment decisions in manufacturing assessing the effects of real oil prices and their uncertainty summary we investigate the effects of real oil prices and their uncertainty on investment decisions making use of plant level data we estimate dynamic discrete choice models that allow modeling investment inaction under different assumptions related to initial conditions and unobserved heterogeneity we find that increases in real oil price changes and in real oil price uncertainty significantly reduce the likelihood of investment action in line with the predictions of irreversible investment theory we also document that investment decisions exhibit strong pure state dependence and are also significantly affected by initial conditions copyright 2012 john wiley sons ltd

international oil price uncertainty and corporate investment evidence from china s emerging and transition economy we develop and estimate a dynamic model of investment to investigate the impact of international oil price uncertainty on corporate investment expenditures in china s emerging and transition economy we further examine whether state ownership affects the relationship between oil price uncertainty and corporate investment consistent with the model s prediction the main finding is that oil price uncertainty exerts a negative impact on corporate investment expenditures in addition compared with state owned listed companies the negative influence of oil price uncertainty on corporate investment is more significant for non state owned listed companies our further analysis using the market oriented reform of refined oil pricing in 2008 as a quasi natural event shows the variation between the low degree marketization period and the high degree one in terms of the relationship between international oil price uncertainty state ownership and corporate investment expenditures

forecasting the good and bad uncertainties of crude oil prices using a har framework abstract good or bad uncertainty is the volatility that is associated with positive or negative innovations to asset prices this paper proposes new heterogeneous autoregressive type har type models to forecast the good and bad uncertainties of crude oil prices in this paper we investigate the effects of lagged bad and good uncertainties daily positive and negative signed jump variations and leverages on predicting good and bad uncertainties by in sample and out of sample analysis the in sample results show that bad and good uncertainties have long memory property and the predictability of long term good and bad uncertainties is stronger than that of short and mid term good and bad uncertainties the out of sample results indicate that lagged bad or good uncertainties daily positive signed jump variation and daily negative signed jump variation contain incremental out of sample information for forecasting good or bad uncertainties and in most cases lagged leverages also play indispensable roles in forecasting the good and bad uncertainties in the crude oil market moreover the results of out of sample analysis remain robust across using the other estimation window other har type models and the other sample

crude oil equity and gold futures open interest co movements abstract the study is unique in its investigation of the co movements between trading activity on the equity crude oil and gold futures market proxied by open interest it provides empirical evidence that stock and crude oil futures demand for hedging is positively related but reacts negatively to sudden shocks in open interest on the other market furthermore gold futures open interest reacts positively to shocks in the crude oil futures trading activity the level of instantaneous linkage is related to external market conditions during periods of unstable financial markets the correlation between equity and energy futures open interest decreases and the correlation of the open interest on the equity and gold futures market turns weak negative this indicates hedging funds allocation toward gold market in periods of stock market uncertainty

jumps and stochastic volatility in oil prices time series evidence abstract in this paper we examine the empirical performance of affine jump diffusion models with stochastic volatility in a time series study of crude oil prices we compare four different models and estimate them using the markov chain monte carlo method the support for a stochastic volatility model including jumps in both prices and volatility is strong and the model clearly outperforms the others in terms of a superior fit to data our estimation method allows us to obtain a detailed study of oil prices during two periods of extreme market stress included in our sample the gulf war and the recent financial crisis we also address the economic significance of model choice in two option pricing applications the implied volatilities generated by the different estimated models are compared and we price a real option to develop an oil field our findings indicate that model choice can have a material effect on the option values

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

the dynamic volatility spillover between european carbon trading market and fossil energy market abstract with the rapid spread of carbon trading in the world the interaction of carbon prices and fossil energy prices has raised growing attention but little research has discussed their time varying correlation and dynamic volatility spillover this paper employs the threshold dynamic conditional correlation dcc generalized autoregressive conditional heteroscedasticity garch model and the full baba engle kraft and kroner bekk garch model to explore these issues for the daily data of european carbon futures prices and the three fossil energy prices coal natural gas and brent oil from january 2 2008 to september 30 2014 the results indicate that first there is significant unidirectional volatility spillover from coal market to carbon market and from carbon market to natural gas market whereas there exists no significant volatility spillover between carbon market and brent oil market second carbon market and fossil energy markets have significantly positive correlation across time specifically among the three fossil fuels coal market has the highest correlation with carbon market followed by natural gas and brent oil markets finally as for the three fossil fuels their price decrease may have stronger impact on carbon price volatility than their price increase with the same degree while there is asymmetric impact of carbon price increase and decrease only on brent oil price volatility these results may help investors to well configure their portfolios and manage their investment risks and help emission trading installations to join in carbon market in a cost effective way

technology adoption with finite horizons the purpose of this paper is to study the relation between the age of an agent and her decisions about adopting new technologies to this end i analyze the optimal sequence of technology upgrades by an agent who lives for a finite period of time other characteristics of the environment are the existence of technology specific learning by doing technology growth and adoption costs a finite planning horizon implies that the technology adoption problem is non stationary and the frequency of adoptions changes over time this paper provides results for the computation of the optimal plan and explores numerically the life cycle pattern of technology switches adoptions may become more frequent as the agent grows older however the sign of the association between age and the adoption of new technologies is sensitive to variation in parameters this is not at odds with the findings of recent empirical studies

optimal regime switching and threshold effects we consider a general control problem with two types of optimal regime switch the first one concerns technological and or institutional regimes indexed by a finite number of discrete parameter values and the second features regimes relying on given threshold values for given state variables we propose a general optimal control framework allowing to derive the first order optimality conditions and in particular to characterize the geometry of the shadow prices at optimal switching times if any we apply this new optimal control material to address the problem of the optimal management of natural resources under ecological irreversibility and with the possibility to switch to a backstop technology

the linkages between oil market uncertainty and islamic stock markets evidence from quantile on quantile approach abstract in recent years islamic finance has become increasingly influential especially islamic stocks which have created huge investment attractiveness at the same time the financialization of oil has made the international oil market increasingly uncertain and more likely to affect other markets to effectively understand the correlation between the two markets we empirically analyze the cases of four typical countries from the perspective of oil market uncertainty this paper utilizes ovx as an accurate measure of oil market uncertainty and applies quantile on quantile approach to detect the asymmetric and heterogeneous relations between the variables our results show overall negative linkages between ovx changes and islamic stock returns and there is indeed asymmetry namely the effects of oil market uncertainty will be more pronounced when it is at higher quantiles further comparing the results of the selected four countries we find some heterogeneities oil importing countries are more sensitive than oil exporting countries and islamic countries are more sensitive than non islamic countries the findings of this article about the linkages between oil market uncertainty and islamic stock markets is meaningful to the research and financial practice in related fields

mergers and the market for organization capital abstract in this paper mergers are an equilibrium outcome in which acquirers marry targets so as to gain access to their organization capital firms with lower learning costs about the new technology are not necessarily those that manage it best once it is mature since there are gains from trade a market for organization capital can arise through mergers this model generates a merger wave after a shock to technology and is consistent with several other stylized facts on mergers documented in the literature