a semiparametric approach to short term oil price forecasting abstract in this paper it is shown how the garch properties of oil price changes can be employed to forecast the oil price distribution over short term horizons the forecasting methodology is semiparametric and it is based on the bootstrap approach the results of an out of sample forecasting exercise carried out using the brent oil price series suggest that the forecasting approach can be used to obtain a performance measure for the forward price in addition to compute interval forecasts for the oil price

an empirical exploration of the world oil price under the target zone model abstract this paper investigates the behavior of the world oil price based on the first generation target zone model using anecdotal data during the period of 1988 1999 we found that opec has tried to maintain a weak target zone regime for the oil price our econometric tests suggest that the movement of the oil price is not only manipulated by actual and substantial interventions by opec but also tempered by market participants expectations of interventions as a consequence the non linear model based on the target zone theory has very good forecasting ability when the oil price approaches the upper or lower limit of the band

international evidence on crude oil price dynamics applications of arima garch models abstract we examine the usefulness of several arima garch models for modeling and forecasting the conditional mean and volatility of weekly crude oil spot prices in eleven international markets over the 1 2 1997 10 3 2009 period in particular we investigate the out of sample forecasting performance of four volatility models garch egarch and aparch and figarch over january 2009 to october 2009 forecasting results are somewhat mixed but in most cases the aparch model outperforms the others also conditional standard deviation captures the volatility in oil returns better than the traditional conditional variance finally shocks to conditional volatility dissipate at an exponential rate which is consistent with the covariance stationary garch models than the slow hyperbolic rate implied by the figarch alternative

comparison of historically simulated var evidence from oil prices abstract cabedo and moya cabedo j d moya i 2003 estimating oil price value at risk using the historical simulation approach energy economics 25 239 253 find that arma with historical simulation delivers var forecasts that are superior to those from garch we compare the arma with historical simulation to the semi parametric garch model proposed by barone adesi et al barone adesi g giannopoulos k vosper l 1999 var without correlations for portfolios of derivative securities journal of futures markets 19 5 583 602 the results suggest that the semi parametric garch model generates var forecasts that are superior to the var forecasts from the arma with historical simulation this is due to the fact that garch captures volatility clustering our findings suggest that cabedo and moya s conclusion is mainly driven by the normal distributional assumption imposed on the future risk structure in the garch model

modelling oil price volatility with structural breaks in this paper we provide two main innovations i we analyze oil prices of two prominent markets namely west texas intermediate wti and brent using the two recently developed tests by narayan and popp 2010 and liu and narayan 2010 both of which allow for two structural breaks in the data series and ii the latter method is modified to include both symmetric and asymmetric volatility models we identify two structural breaks that occur in 1990 and 2008 which coincidentally correspond to the iraqi kuwait conflict and the global financial crisis respectively we find evidence of persistence and leverage effects in the oil price volatility while further extensions can be pursued the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling oil price volatility

forecasting volatility of crude oil markets abstract this article investigates the efficacy of a volatility model for three crude oil markets brent dubai and west texas intermediate wti with regard to its ability to forecast and identify volatility stylized facts in particular volatility persistence or long memory in this context we assess persistence in the volatility of the three crude oil prices using conditional volatility models the cgarch and figarch models are better equipped to capture persistence than are the garch and igarch models the cgarch and figarch models also provide superior performance in out of sample volatility forecasts we conclude that the cgarch and figarch models are useful for modeling and forecasting persistence in the volatility of crude oil prices

toward efficiency in the crude oil market the official opec prices of crude oil before the collapse in the oil market in the mid 1980s can be interpreted as contract prices and analysed on the basis of the theory of futures or forward markets this paper uses the generalized method of moments estimation technique to test for efficiency in the relationship between the official prices and the ex post spot prices at the time of delivery efficiency is rejected for the sample period 1978 1985 as a whole but evidence is found of improvements over time further the gmm wald and hansen tests although asymptotically equivalent are shown to differ greatly when applied to a small sample of monthly oil price data

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

commodity currencies and commodity prices modelling static and time varying dependence abstractthis article employs the copula approach to study the relationship between exchange rates and commodity prices for large commodity exporters using data for the nominal exchange rates of four commodity currencies australian canadian and new zealand dollars and norwegian krone against the us dollar and the relevant country specific commodity price indices constructed on a daily basis we find 1 a positive dependence between the values of commodity currencies and commodity indices i e a commodity index increases when a respective currency appreciates and provides several explanations for this finding 2 no major asymmetries in the tail dependence for most pairs of exchange rates and commodity indices and 3 a pronounced increase in the time varying tail dependence following the global financial crisis

an empirical model of daily highs and lows of west texas intermediate crude oil prices there is a large collection of literature on energy price forecasting but most studies typically use monthly average or close to close daily price data in practice the daily price range constructed from the daily high and low also contains useful information on price volatility and is used frequently in technical analysis the interaction between the daily high and low and the associated daily range has been examined in several recent studies on stock price and exchange rate forecasts the present paper adopts a similar approach to analyze the behaviour of the west texas intermediate wti crude oil price over a ten year period we find that daily highs and lows of the wti oil price are cointegrated with the error correction term being closely approximated by the daily price range two forecasting models one based on a vector error correction mechanism and the other based on a transfer function framework with the range taken as a driver variable are presented for forecasting the daily highs and lows the results show that both of these models offer significant advantages over the naive random walk and univariate arima models in terms of out of sample forecast accuracy a trading strategy that makes use of the daily high and low forecasts is further developed it is found that this strategy generally yields very reasonable trading returns over an evaluation period of about two years

regime switching stochastic volatility evidence from the crude oil market this paper incorporates regime switching into the stochastic volatility sv framework in an attempt to explain the behavior of crude oil prices in order to forecast their volatility more specifically it models the volatility of oil return as a stochastic volatility process whose mean is subject to shifts in regime the shift is governed by a two state first order markov process the bayesian markov chain monte carlo method is used to estimate the models the main findings are first there is clear evidence of regime switching in the oil market ignoring it will lead to a false impression that the volatility is highly persistent and therefore highly predictable second incorporating regime switching into the sv framework significantly enhances the forecasting power of the sv model third the regime switching stochastic volatility model does a good job in capturing major events affecting the oil market

daily seasonality in crude oil returns and volatilities abstract in this article we test for the existence of daily seasonality in returns and volatilities of crude oil using a dummy augmented garch specification for the period from may 1987 to october 2013 our key findings are as follows i volatilities on mondays are significantly higher than on all other weekdays providing the important insight that seasonal effects should be considered when forecasting crude oil volatility ii returns on the other hand tend to be lower on mondays than on other weekdays suggesting profitable investment strategies based on this seasonal pattern in fact the analysis of a simple long short trading rule based on the monday effect provides some evidence that it can outperform a passive buy and hold approach however it cannot do so to an extent that is statistically significant iii our seasonality results are fairly robust to the choice of other frequently used garch model variants like garch m tgarch and cgarch

modeling the price dynamics of co2 emission allowances abstract in this paper we analyze the short term spot price behavior of carbon dioxide co 2 emission allowances of the new eu wide co 2 emissions trading system eu ets after reviewing the stylized facts of this new class of assets we investigate several approaches for modeling the returns of emission allowances due to different phases of price and volatility behavior in the returns we suggest the use of markov switching and ar garch models for stochastic modeling we examine the approaches by conducting an in sample and out of sample forecasting analysis and by comparing the results to alternative approaches our findings strongly support the adequacy of the models capturing characteristics like skewness excess kurtosis and in particular different phases of volatility behavior in the returns

analysis of real oil prices via trend cycle decomposition abstract the recent fluctuations in the oil prices have intensified the discussion on the dynamics and causes of real oil price changes while the long run component of real oil prices seems to have a stochastic trend global real economic activity has been thought to generate important changes in real oil prices based on this argument in this paper we analyze the real oil prices within a trend cycle decomposition framework where we impose a stochastic trend and assume the cyclical term to be affected by global economic conditions we also let the parameters vary over time to see whether shocks to trend and the cycle have changing effects on the real oil prices as a result we find that shocks to trend are more persistent recently in that sense this paper contributes to the literature by offering an explanation for the increased volatility in oil prices in addition we show that global economic activity contributed also to the previous oil price shocks which were regarded mainly as supply side driven

arima models to predict next day electricity prices price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets both for spot markets and long term contracts price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize benefit this paper provides a method to predict next day electricity prices based on the arima methodology arima techniques are used to analyze time series and in the past have been mainly used for load forecasting due to their accuracy and mathematical soundness a detailed explanation of the aforementioned arima models and results from mainland spain and californian markets are presented

unbiasedness and time varying risk premia in the crude oil futures market abstract this paper presents some empirical evidence on market efficiency and unbiasedness in the crude oil futures market and some related issues on the basis of monthly observations on spot and futures prices of the west texas intermediate wti crude oil several tests are carried out on the relevant hypotheses the evidence suggests that futures prices are neither unbiased nor efficient forecasters of spot prices furthermore a garch m 1 1 model reveals the existence of a time varying risk premium

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

central government versus private sector wages and cognitive skills evidence using endogenous switching regression the importance of estimation techniques that allow for nonrandom selection of workers into the public and private sectors has been established in the theoretical and empirical literature a separate body of work has explored the contribution of cognitive and other basic skills to earnings this article brings together these two strands of empirical literature using adult literacy and lifeskills all survey data for norway and bermuda in the case of norway results from both ordinary least squares ols and a switching regression model agree that cognitive skills are rewarded more in the public sector and that in both sectors the main effect is the direct effect of skills on earnings in the case of bermuda however switching regression estimates are substantially different with respect to the how skills affect earnings furthermore controlling for cognitive skills changes the nature of selection and hence the estimates of sector wage differentials

do opec announcements influence oil prices abstract this paper investigates the effect of opec production decisions increase cut maintain on both wti and brent crude oil prices between q1 1991 and q1 2015 by employing the event study methodology and by using two indices as benchmarks bci and s p gsci we employ an egarch model to take into account the high volatility of oil prices and some stylized facts characterizing this volatility we find that the impact of opec s announcements on oil prices i evolves over time and among decisions ii is more significant for production cut and maintain iii is different for wti and brent prices and iv is sensitive to the benchmark index moreover opec s decisions depend on the exploration and extraction cost of more expensive unconventional oil resources

evaluating information in multiple horizon forecasts the doe s energy price forecasts abstract the united states department of energy s doe quarterly price forecasts for energy commodities are examined to determine the incremental information provided at the one through four quarter forecast horizons a direct test for determining information content at alternative forecast horizons developed by vuchelen and gutierrez vuchelen j and gutierrez m i a direct test of the information content of the oecd growth forecasts international journal of forecasting 21 2005 103 117 is used the results suggest that the doe s price forecasts for crude oil gasoline and diesel fuel do indeed provide incremental information out to three quarters ahead while natural gas and electricity forecasts are informative out to the four quarter horizon in contrast the doe s coal price forecasts at two three and four quarters ahead provide no incremental information beyond that provided for the one quarter horizon recommendations of how to use these results for making forecast adjustments is also provided

caviar based forecast for oil price risk abstract as a benchmark for measuring market risk value at risk var reduces the risk associated with any kind of asset to just a number amount in terms of a currency which can be well understood by regulators board members and other interested parties this paper employs a new var approach due to engle and manganelli engle r f manganelli s 2004 caviar conditional autoregressive value at risk by regression quantiles journal of business and economic statistics 22 367 381 to forecasting oil price risk in doing so we provide two original contributions by introducing a new exponentially weighted moving average caviar model and developing a mixed data regression model for multi period var prediction

sharing cities and sustainable consumption and production towards an integrated framework calls for a transformation towards more sustainable consumption and production scp have been intensifying as urban populations swell across the planet cities are faced with increasing pressure on infrastructure economic and ecological systems yet with their high population densities and ubiquity of information and communication technologies cities are becoming breeding grounds for a new circular economy driven by emerging and long standing sharing activities this research provides a comprehensive view of scp systems in cities by integrating and examining sharing economy activities in the context of two continuums i e scp and private public orientation based on these two analytical dimensions the paper evaluates and plots five groups of 18 sharing activities to create a sharing cities scp typology comprised by five ideal types each of these five types represents a unique form of scp activity with the potential to directly impact scp systems in the context of urban environments by enabling diversity and hybridity in the scp analysis we allow for a theoretical expansion of scp models and a new way of understanding how they may play out in cities