value at risk estimation with the optimal dynamic biofuel portfolio abstract in the past petroleum companies only paid attention to hedging the variation in the crude oil price and volatility however they have now expanded their analysis to encompass renewable sources such as corn and soybeans under the current low carbon biofuel obligations this paper employs garch 1 1 and arji models to estimate the one day ahead value at risk var of the optimal dynamic biofuel portfolio which consists of crude oil corn and soybeans the optimal blended standard is subject to the dual limitations of minimum production costs and the lowest biofuel using requirements our empirical findings confirm that the arji model is more suitable than the garch 1 1 model and further captures the discontinuous jump behavior from the in the sample data the results of out of sample forecasts also are represented that our models play important roles in var estimation and risk management for biofuel portfolio we therefore suggest that the petroleum companies should simultaneously pay attention to jump risk in hedging material costs in the prices of energy related crops

portfolio optimization with tracking error constraints this article explores the risk and return relationship of active portfolios subject to a constraint on tracking error volatility tev which can also be interpreted in terms of value at risk such a constrained portfolio is the typical setup for active managers who are given the task of beating a benchmark the problem with this setup is that the portfolio manager pays no attention to total portfolio risk which results in seriously inefficient portfolios unless some additional constraints are imposed the development in this article shows that tev constrained portfolios are described by an ellipse on the traditional mean variance plane this finding yields a number of new insights because of the flat shape of this ellipse adding a constraint on total portfolio volatility can substantially improve the performance of the active portfolio in general plan sponsors should concentrate on controlling total portfolio risk

evaluating interval forecasts a complete theory for evaluating interval forecasts has not been worked out to date most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage consequently i set out to build a consistent framework for conditional interval forecast evaluation which is crucial when higher order moment dynamics are present the new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management

estimating value at risk of crude oil price and its spillover effect using the ged garch approach estimation has been carried out using garch type models based on the generalized error distribution ged for both the extreme downside and upside value at risks var of returns in the wti and brent crude oil spot markets furthermore according to a new concept of granger causality in risk a kernel based test is proposed to detect extreme risk spillover effect between the two oil markets results of an empirical study indicate that the ged garch based var approach appears more effective than the well recognized hsaf i e historical simulation with arma forecasts moreover this approach is also more realistic and comprehensive than the standard normal distribution based var model that is commonly used results reveal that there is significant two way risk spillover effect between wti and brent markets supplementary study indicates that at the 99 confidence level when negative market news arises that brings about a slump in oil price return historical information on risk in the wti market helps to forecast the brent market conversely it is not the case when positive news occurs and returns rise historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other these results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets

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

optimal portfolio selection in a value at risk framework abstract in this paper we develop a portfolio selection model which allocates financial assets by maximising expected return subject to the constraint that the expected maximum loss should meet the value at risk limits set by the risk manager similar to the mean variance approach a performance index like the sharpe index is constructed furthermore when expected returns are assumed to be normally distributed we show that the model provides almost identical results to the mean variance approach we provide an empirical analysis using two risky assets us stocks and bonds the results highlight the influence of both non normal characteristics of the expected return distribution and the length of investment time horizon on the optimal portfolio selection

oil and the macroeconomy since world war ii all but one of the u s recessions since world war ii have been preceded typically with a lag of around three fourths of a year by a dramatic increase in the price of crude petroleum this does not mean that oil shocks caused these recessions evidence is presented however that even over the period 1948 72 this correlation is statistically significant and nonspurious supporting the proposition that oil shocks were a contributing factor in at least some of the u s recessions prior to 1972 by extension energy price increases may account for much of post opec macroeconomic performance

modeling and forecasting extreme commodity prices a markov switching based extreme value model abstract we propose a markov switching multifractal peaks over threshold msm pot model to capture the dynamic behavior of the random occurrences of extreme events exceeding a high threshold in time series of returns this approach allows introducing changes of regimes in the conditional mean function of the inter exceedance times i e the time between two consecutive extreme events in order to admit the presence of short and long term memory patterns further through its multifractal structure the msm pot approach is able to capture the typical stylized facts of extreme events observed in financial time series such as temporal clustering of the size of exceedances and temporal behavior of tail thickness we compare the performance of the msm pot model with competing self exciting models and a garch evt approach in an in and out of sample var forecasting exercise based on the extreme returns of six daily commodity futures prices i e brent and wti crude oil cocoa cotton copper and gold empirical results suggest that the var estimates generated by the msm pot model for the returns analyzed produce the most accurate forecasts

from value at risk to stress testing the extreme value approach this article presents an application of extreme value theory to compute the value at risk of a market position in statistics extremes of a random process refer to the lowest observation the minimum and to the highest observation the maximum over a given time period extreme value theory gives some interesting results about the distribution of extreme returns in particular the limiting distribution of extreme returns observed over a long time period is largely independent of the distribution of returns itself in financial markets extreme price movements correspond to market corrections during ordinary periods and also to stock market crashes bond market collapses or foreign exchange crises during extraordinary periods an approach based on extreme values to compute the var thus covers market conditions ranging from the usual environment considered by the existing var methods to the financial crises which are the focus of stress testing univariate extreme value theory is used to compute the var of a fully aggregated position while multivariate extreme value theory is used to compute the var of a position decomposed on risk factors 2000 elsevier science b v all rights reserved

extreme value theory and value at risk application to oil market recent increases in energy prices especially oil prices have become a principal concern for consumers corporations and governments most analysts believe that oil price fluctuations have considerable consequences on economic activity oil markets have become relatively free resulting in a high degree of oil price volatility and generating radical changes to world energy and oil industries as a result oil markets are naturally vulnerable to significant negative volatility an example of such a case is the oil embargo crisis of 1973 in this newly created climate protection against market risk has become a necessity value at risk var measures risk exposure at a given probability level and is very important for risk management appealing aspects of extreme value theory evt have made convincing arguments for its use in managing energy price risks in this paper we apply both unconditional and conditional evt models to forecast value at risk these models are compared to the performances of other well known modelling techniques such as garch historical simulation and filtered historical simulation both conditional evt and filtered historical simulation procedures offer a major improvement over the parametric methods furthermore garch 1 1 t model may provide equally good results as well as the combining of the two procedures

value at risk estimation of energy commodities a long memory garch evt approach abstract in this paper we evaluate value at risk var and expected shortfall es for crude oil and gasoline market we adopt three long memory models including figarch hygarch and fiaparch to forecast energy commodity volatility by capturing some volatility stylized fact such as long range memory heteroscedasticity asymmetry and fat tails then we consider extreme value theory which concentrates on the tail distribution rather than the entire distribution evt is considered as a potential framework for the separate treatment of tails of distributions which allows for asymmetry our results show that the fiaparch model with extreme value theory performs better in predicting the one day ahead var using the fitted long memory garch model and a simulation approach to estimate var for horizons over than one day backtesting results show that our approach still performs for lower estimation frequencies overall our findings confirm that taking into account long range memory asymmetry and fat tails in the behavior of energy commodity prices returns combined with filtering process such as evt are important in improving risk management assessments and hedging strategies in the high volatile energy market

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

estimating oil price value at risk using the historical simulation approach abstract in this paper we propose using value at risk var for oil price risk quantification var provides an estimation for the maximum oil price change associated with a likelihood level and can be used for designing risk management strategies we analyse three var calculation methods the historical simulation standard approach the historical simulation with arma forecasts hsaf approach developed in this paper and the variance covariance method based on autoregressive conditional heteroskedasticity models forecasts the results obtained indicate that hsaf methodology provides a flexible var quantification which fits the continuous oil price movements well and provides an efficient risk quantification

co regulation as a possible model for food safety governance opportunities for public private partnerships public concern about food safety is placing increasing pressure on government agencies to be more prescriptive and proactive in their regulation of the food industry however given the scarcity of public sector resources concerns about the impact of regulation on competitiveness and the scale of the task at hand there is growing interest in co regulation with public and private sectors working hand in hand to deliver safer food at lower regulatory cost this paper explores the scope for the co regulation of food safety in the uk and north america where there are distinct differences in the established regulatory processes the authors conclude that opportunities clearly exist to varying degrees in the different countries analysed but that considerable obstacles remain to the widespread adoption of co regulatory practices in the area of food safety

beyond portfolio theory the next frontier logically investment theory s next frontier is to put into practice the rich set of tools that academia has bestowed on the investment community starting with harry markowitz s seminal article on portfolio selection in 1952 or is it in fact the next frontier lies beyond simply engineering the implementation of new investment decision tools the time has come to integrate the powerful insights offered by information theory and principal agent theory into a holistic comprehensive theory of investing only such an expanded theory offers any material hope of improving the economic prospects of the millions of clients beneficiaries of today s mutual funds pension funds endowments and foundations

a variance equality test of the icapm on philippine stocks post asian financial crisis period the study examines whether fama s discrete version of merton s intertemporal capm icapm can explain the negative market risk premium and the cross sectional variability of philippine stock returns after the onset of the asian financial crisis in july 1997 the change in foreign exchange rate in addition to the change in market risk premium is used as a state variable of hedging concern to investors the relationship of fama s multifactor minimum variance mmv portfolio to the markowitz minimum variance mv portfolio is characterized in terms of the equality of the return variances for the same expected return a test due to basak et al 2002 is then used to verify the equality of the return variance of a derived tangency portfolio along the mmv frontier to an mv portfolio with the same sample mean return the results do not reject the icapm during the period covered by the study thus the model provides a plausible explanation both for the cross sectional variability of stock returns and the nega

reassessing marketing boards as hybrid arrangements evidence from canadian experiences in this article we reassess the role of marketing boards and similar arrangements that have played an important role in numerous agro food sectors of developed countries over almost a century referring to transaction cost economics and to more recent contributions on the allocation of decision and property rights we interpret these arrangements as hybrid modes of governance we hypothesize that uncertainty is the leading force pushing toward these organizational solutions and we explore forms of uncertainty at stake and their impact in shaping various types of hybrids we also explore the role of institutional embeddedness in providing marketing boards and the like their legitimacy using numerous examples from canadian marketing boards we discuss the benefits and point out flaws of these arrangements we conclude on the need to assess comparatively the role of these solutions with respect to for example a system of bilateral contracts

optimal mean variance portfolio selection using cauchy schwarz maximization fund managers highly prioritize selecting portfolios with a high sharpe ratio traditionally this task can be achieved by revising the objective function of the markowitz mean variance portfolio model and then resolving quadratic programming problems to obtain the maximum sharpe ratio portfolio this study presents a closed form solution for the optimal sharpe ratio portfolio by applying cauchy schwarz maximization and the concept of kuhn tucker conditions an empirical example is used to demonstrate the efficiency and effectiveness of the proposed algorithms moreover the proposed algorithms can also be used to obtain the optimal portfolio containing large numbers of securities which is not possible or at least is complicated via traditional quadratic programming approaches

public private partnerships in food industries a road to success recent food safety crises have led to the development of new collaborations between public authorities and food operators in monitoring food safety to date most of the literature has analyzed these collaborations as linked to a regulatory process and as a mean to comply with regulatory standards in this paper we take another stand and consider them as specific embedded institutions meso institutions analysing them as public private partnership specific to food safety provision this new perspective allows us to take into account both information asymmetries and the industry wide dimension of such programmes our overall intention is to provide a general enriched theoretical framework to highlight aligned incentive mechanisms in such partnerships we then apply our framework to two case studies in order to better understand the main mechanisms at work that could explain their specific functioning and resilience the two case studies are the cattle traceability system in quebec canada and monitoring programmes for pesticide residues in the french imports industry of fresh produce

public private partnerships and collective action in high value fruit and vegetable supply chains accessing developed country food markets entails meeting stringent food safety requirements food retailers impose protocols relating to pesticide residues field and pack house operations and traceability to enable smallholders to remain competitive in such a system new institutional arrangements are required in particular public private partnerships can play a key role in creating farm to fork linkages that can satisfy market demands for food safety while retaining smallholders in the supply chain furthermore organized producer groups monitoring their own food safety standards through collective action often become attractive to buyers who are looking for ways to ensure traceability and reduce transaction costs this paper compares the ways in which small producers of fruits and vegetables in kenya and india have coped with increased demands for food safety from their main export markets

estimation of value at risk for energy commodities via fat tailed garch models the choice of an appropriate distribution for return innovations is important in var applications owing to its ability to directly affect the estimation quality of the required quantiles this study investigates the influence of fat tailed innovation process on the performance of one day ahead var estimates using three garch models garch n garch t and garch ht daily spot prices of five energy commodities wti crude oil brent crude oil heating oil 2 propane and new york harbor conventional gasoline regular are used to compare the accuracy and efficiency of the var models empirical results suggest that for asset returns that exhibit leptokurtic and fat tailed features the var estimates generated by the garch ht models have good accuracy at both low and high confidence levels additionally mrsb indicates that the garch ht model is more efficient than alternatives for most cases at high confidence levels these findings suggest that the heavy tailed distribution is more suitable for energy commodities particularly var calculation

systemic failure in the provision of safe food abstract many deficiencies in the capacity of a food system to deliver safe products are systemic in nature we suggest a taxonomy of four general ways in which a systemic failure might occur one relates to the connectedness or topology of the system another arises from mistrust on the part of downstream parties concerning signals on product attributes production processes and the performance of regulatory mechanisms a third arises when asymmetric information leads to low incentives for preserving food quality finally inflexibilities in adapting to different states of nature may leave the system vulnerable to failures innovations in information technology and institutional design may ameliorate many problems while appropriate trade industrial organization science and public infrastructure policies may also fortify the system

robust tracking error portfolio selection with worst case downside risk measures abstract this paper proposes downside risk measure models in portfolio selection that captures uncertainties both in distribution and in parameters the worst case distribution with given information on the mean value and the covariance matrix is used together with ellipsoidal and polytopic uncertainty sets to build up this type of downside risk model as an application of the models the tracking error portfolio selection problem is considered by lifting the vector variables to positive semidefinite matrix variables we obtain semidefinite programming formulations of the robust tracking portfolio models numerical results are presented in tracking sse50 of the shanghai stock exchange compared with the tracking error variance portfolio model and the equally weighted strategy the proposed models are more stable have better accumulated wealth and have much better sharpe ratio in the investment period for the majority of observed instances

oil and the macroeconomy when prices go up and down an extension of hamilton s results in an important paper hamilton 1983 demonstrated a strong correlation between oil price changes and gross national product growth in u s data however his study pertained to a period in which all the large oil price movements were upward and thus it left unanswered the question whether the correlation persists in periods of price decline moreover the price variable he used was somewhat distorted by price controls in the 1970s this note investigates whether hamilton s results continue to hold when the sample is extended to include the recent oil market collapse and the oil price variable is corrected for the effects of price controls particular attention is given to the possibility of asymmetric responses to oil price increases and decreases as suggested in the structural employment literature loungani 1986 davis 1987 hamilton 1988 like hamilton i based my investigation on the gnp equation in sims s 1 980b six variable quarterly vector autoregressive model

an mcdm approach to portfolio optimization abstract we propose a model for portfolio optimization extending the markowitz mean variance model based on cooperation with standard and poor s we use five specific objectives related to risk and return and allow consideration of individual preferences through the construction of decision maker specific utility functions and an additive global utility function numerical results using customized local search simulated annealing tabu search and genetic algorithm heuristics show that problems of practically relevant size can be solved quickly

variance vs downside risk is there really that much difference abstract the popularity of downside risk among investors is growing and mean return downside risk portfolio selection models seem to oppress the familiar mean variance approach the reason for the success of the former models is that they separate return fluctuations into downside risk and upside potential this is especially relevant for asymmetrical return distributions for which mean variance models punish the upside potential in the same fashion as the downside risk the paper focuses on the differences and similarities between using variance or a downside risk measure both from a theoretical and an empirical point of view we first discuss the theoretical properties of different downside risk measures and the corresponding mean downside risk models against common beliefs we show that from the large family of downside risk measures only a few possess better theoretical properties within a return risk framework than the variance on the empirical side we analyze the differences between some us asset allocation portfolios based on variances and downside risk measures among other things we find that the downside risk approach tends to produce on average slightly higher bond allocations than the mean variance approach furthermore we take a closer look at estimation risk viz the effect of sampling error in expected returns and risk measures on portfolio composition on the basis of simulation analyses we find that there are marked differences in the degree of estimation accuracy which calls for further research

selecting a portfolio with skewness recent evidence from us european and latin american equity markets abstract polynomial goal programming in which investor preferences for skewness can be incorporated is utilized to determine the optimal portfolio from latin american us and european capital markets the empirical findings suggest that the incorporation of skewness into an investor s portfolio decision causes a major change in the resultant optimal portfolio the empirical evidence indicates that investors do trade expected return of the portfolio for skewness