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

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

does opec influence crude oil prices testing for co movements and causality between regional crude oil prices using high frequency data the co movements among crude oil prices are analysed in order to address the question of regionalization of the world crude oil market time series econometrics in the form of error correction modelling is applied for daily crude oil price data covering the time period 1988 to 2004 and in this framework topics like weak and strong exogeneity among three major oil prices represented by brent opec and texas wti are addressed the empirical results are that causality is most likely bi directional among these crude oil prices and hence rejecting a regionalization hypothesis of the global oil market and also an influence from the opec oil price towards bent and wti which are usually claimed to have a benchmark role

a note on liquidity risk management when a firm is unable to roll over its debt it may have to seek more expensive sources of financing or even liquidate its assets this paper provides a normative analysis of minimizing such rollover risk through the optimal dynamic choice of the maturity structure of debt the objective of a firm with long term assets is to maximize the effective maturity of its liabilities across several refinancing cycles rather than to maximize the maturity of the current bonds outstanding an advantage of short term financing is that a firm while in good financial health can readjust its maturity structure more quickly in response to changes in its asset value this abstract was borrowed from another version of this item

returns to scale and damages to scale on u s fossil fuel power plants radial and non radial approaches for dea environmental assessment abstract this study proposes a new use of data envelopment analysis dea for environmental assessment paying attention to a methodological bias i e different methods produce different results dea is analytically classified into radial and non radial approaches the radial approach determines the level of unified operational and environmental efficiency by measuring an inefficiency score the score indicates the distance of a projection from an observed performance to an efficiency frontier in contrast the non radial approach determines the level of unified efficiency by measuring a total amount of slacks because each slack indicates inefficiency to avoid the methodological bias this study considers the use of radial and non radial approaches in this study we consider a production process where all organizations produce not only desirable good but also undesirable bad outputs as a result of their business operations to unify the two types of outputs this study discusses the concept of disposability which is separated into natural and managerial disposability the natural disposability indicates negative adaptation to a regulation change on undesirable outputs in contrast the managerial disposability indicates corporate strategy by which a firm considers the regulation change as a new business opportunity a firm attempts to improve its unified efficiency by utilizing new environmental technology and or new management this type of strategy indicates positive adaptation to the regulation change under the two disposability concepts this study discusses how to measure rts returns to scale under natural disposability and dts damages to scale corresponding to rts on undesirable outputs under managerial disposability the two scale measures are analytically discussed by the proposed radial and non radial approaches with scscs or without scscs where scscs indicate strong complementary slackness conditions an illustrative example on u s fossil fuel power plants indicates a policy implication that they need to introduce new technology for environmental protection this study also discusses a necessity of examining a methodological bias in energy studies empirical findings identified in this study document the practicality of the proposed approaches to measure rts dts

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

a literature study for dea applied to energy and environment abstract this study systematically summarizes previous research efforts on data envelopment analysis dea applied to energy and environment in the past four decades including concepts and methodologies on dea environmental assessment industrial developments are very important for all nations in terms of their economic prosperities a problem is that the development produces various pollutions on air water and other types of contaminations all of which are usually associated with our health problems and climate changes thus it is necessary for us to consider how to make a balance between economic success and pollution mitigation to maintain a high level of social sustainability in the world it is widely considered that dea is one of the methodologies to examine the level of sustainability this study examines a recent research trend on dea applications from 1980s to 2010s nowadays many researchers have paid serious attention on how to combat various difficulties in the areas of energy and environment as a result the number of articles on dea applications on energy and environment has dramatically increased particularly after 2000s however it is true that dea has strengths and drawbacks in the applications therefore it is very important for us to carefully use dea for guiding large policy issues and business strategies such as the global warming and climate change an underlying premise of this study is that technology innovation in engineering and natural science may solve various problems by linking it with political and managerial efforts the use of dea provides a methodological linkage among them so enhancing the practicality in mitigating problems due to climate change and environmental pollutions this literature study along with a summary on conceptual and methodological developments provides us with guidelines for our future research works on dea on energy and environment issues

oil prices fundamentals and expectations abstract this paper empirically investigates the relationship between oil prices traditional fundamentals and expectations informational frictions may force a wedge between oil prices and supply and or demand shocks especially during periods of elevated risk aversion and uncertainty in such a context expectations can be a key driver of oil price movements and their impact can vary over time overall we find that both traditional oil fundamentals and forward looking expectations matter for oil prices our findings show that the real price of oil responds differently to expectations shocks of business leaders consumers and aggregate markets our tvp var approach provides evidence that business leaders expectations play an important role in terms of oil price fluctuations and the impact is stronger in periods of elevated global oil demand in terms of traditional oil market fundamentals we find that oil prices have been significantly affected by the recent us shale oil boom moreover global oil demand had a positive impact upon oil prices especially from the mid 2000s several alternative model specifications prove the robustness of our analysis

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

liquidity and risk management firms and financial institutions are best viewed as ongoing entities whose project completion may require renewed injections of liquidity this paper proposes a contract theoretic framework integrating three dimensions of corporate financing and prudential regulation a liquidity management b risk management and c capital structure it concludes with a preliminary assessment of recent regulatory approaches to the treatment of market risk

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

e pluribus unum macroeconomic modelling for multi agent economies from the macroeconomist s viewpoint agent based modelling has an obvious drawback it makes impossible to think in aggregate terms the modeller in fact can reconstruct aggregate variables only from the bottom up by summing the levels of a myriad of individual variables we propose a modelling strategy which reduces the dimensionality of an agent based framework by replacing the actual distribution with the first and higher moments of the distribution itself we put this strategy at work in a macroeconomic and agent based model m abm of the financial accelerator in which firms heterogeneous degrees of financial robustness affect investment in a greenwald stiglitz setting

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

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

a neoclassical model of unemployment and the business cycle this paper investigates a general equilibrium model of unemployment and the business cycle in which specialization of labor plays a key role a rational expectations equilibrium with fully flexible wages and prices can exhibit unemployment in which the marginal product of employed workers exceeds the reservation wage of those who are without jobs workers are unemployed either because they are in the process of relocating for a better job or because they are waiting for conditions in the depressed sector to improve moreover seemingly small disruptions in the supplies of primary commodities such as energy could be the source of fluctuations in aggregate employment and can exert surprisingly large effects on real output

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

futures based forecasts how useful are they for oil price volatility forecasting oil price volatility forecasts have recently attracted the attention of many studies in the energy finance field the literature mainly concentrates its attention on the use of daily data using garch type models it is only recently that efforts to use more informative intraday data to forecast oil price realized volatility have been made despite all these previous efforts no study has examined the usefulness of futures based models for oil price realized volatility forecasting although the use of such models is extensive for oil price predictions this study fills this void and shows that futures based forecasts based on intra day data provide informative forecasts for horizons that span between 1 day and 66 days ahead more importantly these results hold true even during turbulent times for the oil market such as the global financial crisis of 2007 09 and the oil collapse period of 2014 15

a markov switching model of the conditional volatility of crude oil futures prices abstract this paper examines the temporal behaviour of volatility of daily returns on crude oil futures using a generalised regime switching model that allows for abrupt changes in mean and variance garch dynamics basis driven time varying transition probabilities and conditional leptokurtosis this flexible model enables us to capture many complex features of conditional volatility within a relatively parsimonious set up we show that regime shifts are clearly present in the data and dominate garch effects within the high volatility state a negative basis is more likely to increase regime persistence than a positive basis a finding which is consistent with previous empirical research on the theory of storage e g fama and french 1988a fama and french 1988b and ng and pirrong 1994 the volatility regimes identified by our model correlate well with major events affecting supply and demand for oil out of sample tests indicate that the regime switching model performs noticeably better than non switching models regardless of evaluation criteria we conclude that regime switching models provide a useful framework for the financial historian interested in studying factors behind the evolution of volatility and to oil futures traders interested short term volatility forecasts

evaluating the dynamic performance of energy portfolios empirical evidence from the dea directional distance function abstract in recent years the complex global energy commodity market has led to increased uncertainty for energy investment returns and tremendous challenges for investors to design appropriate energy portfolios therefore we employ four popular portfolio methods to determine energy portfolios based on daily fossil fuel futures prices during 2006 2015 moreover we use the dea window analysis method and dea directional distance function to comprehensively evaluate the dynamic performance of these energy portfolios based on the efficiency perspective the empirical results indicate that first to increase investment returns the mean variance method that exclusively emphasizes the maximization of returns shows the best performance however in order to decrease the volatility and risk of investment returns the mean variance method that aims to resist risk more than make profits and the bootstrap historical simulation value at risk var method have the best performance second when the global financial crisis broke out in the second half of 2008 and energy markets experienced a sharp downturn in the second half of 2014 the dea efficiency of energy portfolios appeared relatively lower than those of their neighboring periods regardless of which portfolio method is employed finally the average dea efficiencies of energy portfolios are all higher than those of single energy investment throughout the sample period except when the equally weighted method and the information entropy comprehensive index method are used meanwhile the mean variance method that prefers profit making to risk resisting possesses the highest average dea efficiency among various methods concerned

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

lapm a liquidity based asset pricing model the intertemporal capm predicts that an asset s price is equal to the expectation of the product of the asset s payoff and a representative consumer s intertemporal marginal rate of substitution this paper develops an alternative approach to asset pricing based on corporations desire to hoard liquidity our corporate finance approach suggests new determinants of asset prices such as the distribution of wealth within the corporate sector and between the corporate sector and the consumers also leverage ratios capital adequacy requirements and the composition of savings affect the corporate demand for liquid assets and thereby interest rates starting with the capital asset pricing model capm derived by sharpe 1964 lintner 1965 and mossin 1966 market finance has emphasized the role of consumers time preference and risk aversion in determining asset prices the intertemporal consumption based asset pricing model e g rubinstein 1976 lucas 1978 breeden 1979 harrison and kreps 1979 cox ingersoll and ross 1985 hansen and jagannathan 1991 predicts that an asset s current price is equal to the expectation conditioned on current information of the product of the asset s payoff and a representative consumer s intertemporal marginal rate of substitution imrs while fundamental this dominant paradigm for pricing assets has some wellrecognized shortcomings see below and there is clearly scope for alternative and complementary approaches this paper begins developing one such approach based on aggregate liquidity considerations 1 our starting point is that the productive and financial spheres of the economy have autonomous demands for financial assets and that their valuations for these assets are often disconnected from the representative consumer s corporate demand for financial assets is driven by the desire to hoard liquidity in order to fulfill future cash needs in contrast with the