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

optimal pricing shipment and payment policy for an integrated supplier buyer inventory model with two part trade credit abstract in this article we develop an integrated supplier buyer inventory model with the assumption that the market demand is sensitive to the retail price and the supplier adopts a trade credit policy the trade credit policy discussed in this paper is a two part strategy cash discount and delayed payment that is if the buyer pays within m1 the buyer receives a cash discount otherwise the full purchasing price must be paid before m2 where m 2 m 1 0 the objective of this research is to determine the optimal pricing ordering shipping and payment policy to maximize the joint expected total profit per unit time an iterative algorithm is established to obtain the optimal strategy furthermore numerical examples and sensitivity analysis are presented to illustrate the results of the proposed model and to draw managerial insights

the joint economic lot sizing problem review and extensions with the growing focus on supply chain management firms realize that inventories across the entire supply chain can be more efficiently managed through greater cooperation and better coordination this paper presents a comprehensive and up to date review of the joint economic lot sizing problem jelp and also provides some extensions of this important problem in particular a detailed mathematical description of and a unified framework for the main jelp models are given additionally a comparative empirical study of the main policies proposed for jelp is conducted the focus of this study is on assessing the deviation of these policies from the optimal solution studying the performance of different models provides additional insights that will help in justifying their use in more complex supply chain models that involve more stages or other practical considerations of interest

joint economic procurement production delivery policy for multiple items in a single manufacturer multiple retailer system abstract this paper proposes an analytical model to effectively integrate and synchronize the procurement production and delivery activities in a supply chain consisting of a single raw material supplier a single manufacturer and multiple retailers the manufacturer produces multiple items on a single facility utilizing common raw material under a common rotation cycle policy of not incurring shortages at any retailers this problem is formulated as a variant of the classical economic lot scheduling problem the objective is to find the production sequence of multiple items the common production cycle length and the delivery frequencies and quantities that minimize the average total cost an efficient heuristic algorithm is presented to solve the proposed problem through numerical tests we show that the proposed heuristic gives quite satisfactory solutions

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

optimal ordering and transfer policy for an inventory with stock dependent demand abstract this paper deals with an ordering transfer inventory model to determine the retailer s optimal order quantity and the number of transfers per order from the warehouse to the display area it is assumed that the amount of display space is limited and the demand rate depends on the display stock level the objective is to maximize the average profit per unit time yielded by the retailer the proposed models and algorithms are developed to find the optimal strategy by retailer numerical examples are presented to illustrate the models developed and the sensitivity analysis is also reported

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

note comment on a generalized quantity discount pricing model to increase supplier s profits lee and rosenblatt lee h l m j rosenblatt 1986 a generalized quantity discount pricing model to increase supplier s profits management sci 32 9 1177 1185 considered the joint problem of ordering and offering discount by a supplier to his sole buyer the objective of the supplier being to induce the buyer to alter his order quantities in order to increase the supplier s yearly profit they determined the optimal ordering and pricing policy for the supplier under the constraint on the amount of discount offered to the purchaser this restriction on the amount of price discount seems unreasonable when the objective of the supplier in all likelihood is to increase his own profits it is possible that higher discounts in purchase price may lead to greater economies for the supplier in this note a much simpler approach is being offered for determining the optimal ordering and pricing policy for the supplier

a generalized quantity discount pricing model to increase supplier s profits in this paper the joint problem of ordering and offering price discount by a supplier to his sole major buyer is analyzed the objective is to induce the buyer to alter his order schedule and size so that the supplier can benefit from lower set up ordering and inventory holding costs we generalize the quantity discount pricing model of monahan monahan j p 1984 a quantity discount pricing model to increase vendor profits management sci 30 6 720 726 to 1 explicitly incorporate constraints imposed on the amount of discount that can be offered and 2 relax the implicit assumption of a lot for lot or order for order policy adopted by the supplier an algorithm is developed to solve the supplier s joint ordering and price discount problem

optimal strategy for an integrated system with variable production rate when the freight rate and trade credit are both linked to the order quantity abstract this paper presents an integrated inventory model with variable production rate and price sensitive demand rate the buyer s purchases trade credit linked to the order quantity offered by the supplier in addition the buyer pays the freight charge according to a weight schedule this paper attempts to offer a best policy that aims at maximizing the joint total profit while the trade credit and freight rate are simultaneously linked to the order quantity the same policy also incorporates considerations on the optimal retail price order quantity and delivery decision we provide possible solutions for the buyer and the supplier to collaboratively agree on inventory control warehouse management transportation logistics delivery and billing our study demonstrates that significant profit increase for the entire supply chain can be achieved by linking both trade credit policy and freight rate policy to order quantities an algorithm is furnished to determine the optimal solution in addition numerical examples and sensitivity analysis are presented to illustrate the theoretical results

portfolio optimization using mixture design of experiments scheduling trades within electricity markets abstract deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts financial tools requiring substantial adjustments are usually used to determine risk and return this article presents a novel approach to adjusting the conditional value at risk cvar metric to the mix of contracts on the energy markets the approach uses mixture design of experiments mde in this kind of experimental strategy the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general instead of using traditional linear programming the concept of desirability function is here used to combine the multi response nonlinear objective functions for mean with the variance of a specific portfolio obtained through mde the maximization of the desirability function is implied in the portfolio optimization generating an efficient recruitment frontier this approach offers three main contributions it includes risk aversion in the optimization routine it assesses interaction between contracts and it lessens the computational effort required to solve the constrained nonlinear optimization problem a case study based on the brazilian energy market is used to illustrate the proposal the numerical results verify the proposal s adequacy

competitive and cooperative policies for the vendor buyer system abstract this paper considers a model for decentralized dynamic production distribution control we examine the situation where a vendor produces a product in a batch production environment and supplies it to a buyer under deterministic conditions some conditional games for the vendor and the buyer are defined the games are indexed by numbers of shipments acceptable to both players before the strategies competition begins a construction of nash equilibrium strategies is given in the proof of the existence theorem goyal s numerical example is used to compare our equilibrium solutions with relatively optimal policies in the cooperative case

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

optimal strategy for the integrated vendor buyer inventory model this note is concerned with the integrated vendor buyer inventory model two different strategies have been proposed in the literature for the problem one where the delivery quantity to the buyer at each replenishment is identical and another strategy where at each delivery all the inventory available with the vendor is supplied to the buyer we show that there is no one strategy that obtains the best solution for all possible problem parameters we also present the results of a detailed numerical study that analyses the relative performance of the two strategies for various problem parameters

integrated safety stock optimization for multiple sourced stockpoints facing variable demand and lead time abstract the safety stock placement problem of a multi stage supply chain comprising multiple sourced stockpoints is addressed in this paper each stockpoint faces variability in its downstream demand and suppliers lead time the maximum among these suppliers lead time is determined by employing concepts of order statistics it is required to find the fill rate and safety stocks at each stockpoint that leads to satisfying the end customer service level at minimum safety stock placement cost hence the fill rates and the safety amounts are decided from a global supply chain perspective two models are proposed a decentralized safety stock placement model and a centralized consolidation model the decentralized model finds the safety amounts at each stockpoint required to face its underlying lead time demand variability the consolidation model finds the consolidated safety amounts that will be kept in the relevant consolidation center at each stage a benders decomposition technique is developed to handle the nonlinearity and binary restrictions involved in the safety stock consolidation model strategies proposed by the consolidation model achieve 45 2 62 reduction in safety amounts that results in a cost savings ranging between 22 2 44 2 as compared to the strategies proposed by the decentralized model

crude oil risk forecasting new evidence from multiscale analysis approach fluctuations in the crude oil price allied to risk have increased significantly over the last decade frequently varying at different risk levels although existing models partially predict such variations so far they have been unable to predict oil prices accurately in this highly volatile market the development of an effective predictive model has therefore become a prime objective of research in this field our approach albeit based in part on previous research develops an original methodology in that we have created a risk forecasting model with the ability to predict oil price fluctuations caused by changes in both fundamental and transient risk factors we achieve this by disintegrating the multi scale risk structure of the crude oil market using variational mode decomposition normal and transient risk factors are then extracted from the crude oil price using variational mode decomposition and modelled separately using the quantile regression neural network qrnn model both risk factors are integrated and ensembled to produce the risk estimates we then apply our proposed risk forecasting model to predicting future downside risk level in three major crude oil markets namely the west taxes intermediate wti the brent market and the opec market the results demonstrate that our model has the ability to capture downside risk estimates with significantly improved precision thus reducing estimation errors and increasing forecasting reliability

an approach for developing an optimal discount pricing policy this paper addresses the problem of why and how a seller should develop a discount pricing structure even if such a pricing structure does not alter ultimate demand the situation modeled is most appropriate where the seller s product does not represent a major component of the buyer s final product where the demand for the product is derived or where the price is only one of many factors considered in making a purchase decision a model of buyer reaction to any given pricing scheme is developed to show that there exists a unified pricing policy which motivates the buyer to increase its ordering quantity per order thereby reducing the joint buyer and seller ordering and holding costs as a result the seller is able to reduce its costs while leaving the buyer no worse off and often better off the model is extended to handle variable ordering and shipping costs and situations where the seller faces numerous groups of buyers each having different ordering policies finally a case study is presented explicitly showing how the proposed pricing policy can be applied to the situation of a large seller selling to a number of different buyer groups

a bargaining model with asymmetric information for a single supplier single buyer problem abstract banerjee s joint economic lot size jels model represents one approach to minimizing the joint total relevant cost of a buyer and a supplier by using a joint optimal order and production policy the implementation of a jointly optimal policy requires coordination and cooperation should the buyer have the market power to implement his own optimal policy as that one to be used in the exchange process no incentive exists for him to choose a joint optimal policy a joint policy can therefore only be the result of a bargaining process between the parties involved the supplier may make some sort of concession such as a price discount or a side payment in order to influence the buyer s order policy a critical assumption made throughout in supply chain literature is that the supplier has complete knowledge about the buyer s cost structure clearly this assumption will seldom be fulfilled in practice the research presented in this paper provides a bargaining model with asymmetric information about the buyer s cost structure assuming that the buyer has the power to impose its individual optimal policy

the single vendor single buyer integrated production inventory model with a generalised policy abstract this note considers a more general type of policy for the single vendor single buyer integrated production inventory model than has hitherto been presented based on successive shipments to the buyer within a single production batch increasing by a fixed factor

note comments on a quantity discount pricing model to increase vendor profits monahan monahan j p 1984 a quantity discount pricing model to increase vendor profits management sci june 720 726 adapted the quantity discount model of inventory theory to the problem of determining an optimal quantity discount schedule from a vendor s point of view and opened up an important direction of research however his one item one customer one vendor model is based on several implicit assumptions that must be judged unreasonable monahan must account for the vendor s inventory carrying charges and redefine his variable s2 it is shown that a rational vendor s manufacturing frequency would not be identical to the buyer s ordering frequency if the vendor s manufacturing setup costs are substantially larger than the buyer s ordering costs a numerical example presented in this note also questions the practical usefulness of monahan s model even after its theoretical inaccuracies axe corrected monahan s model may explain discounts that are a fraction of 1 of the price of an item but it fails to explain commonly observed magnitudes of quantity discounts such as 10 of the unit price

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

models of joint economic lot sizing problem with time based temporary price discounts abstract in this research we develop mathematical models of joint economic lot sizing problem jelp in a situation when a supplier offers time based temporary price discounts to a buyer during a sale period to respond this the buyer places a special order with higher quantity in literature it has been assumed that the buyer tends to place the special order at the end of the sale period we relax this assumption by considering the time when the buyer places the special order during the sale period i e the sooner the special order took place the higher discount received in our proposed models called joint economic lot sizing problem with time based temporary price discounts jelptpd we devide the sale period into k phases the buyer must place the special order in one of these phases the highest discount will be given when the special order is placed at the first phase while the lowest one will be given when it is placed at the k th phase there are two cases discussed the first case is when the sale period is uniformly divided while the second case is when the sale period is proportionally divided following some rules our numerical experiments showed the behavior of the buyer to respond the temporary price discount offers in major experiments the buyer shifted the decision on placing the special order in the earlier phases instead of the end of the sale period

optimal batch size and raw material ordering policy for a production system with a fixed interval lumpy demand delivery system abstract the paper develops an ordering policy for raw materials to meet the demands of a production facility which supplies a fixed quantity of finished products to outside buyers at a fixed interval of time in this model an optimal multi order policy for procurement of raw materials for a single manufacturing batch is developed to minimize the total cost an integer approximation is adopted to refine the optimal solution a worst case scenario is also analyzed to demonstrate the effect of the setup costs on the total cost of the inventory system

value at risk estimations of energy commodities via long memory asymmetry and fat tailed garch models abstract in this paper we evaluate the value at risk var and the expected shortfalls for some major crude oil and gas commodities for both short and long trading positions classical var estimations as well as riskmetrics and other extensions to cases considering for long range memory asymmetry and fat tail in energy markets volatility were conducted we computed the var for three arch garch type models including figarch fiaparch and hygarch these models were estimated in the presence of three alternative innovation s distributions normal student and skewed student our results show that considering for long range memory fat tails and asymmetry performs better in predicting a one day ahead var for both short and long trading positions moreover the fiaparch model outperforms the other models in the var s prediction these results present several potential implications for energy markets risk quantifications and hedging strategies

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

cheap talk games may have unique informative equilibrium outcomes abstract we demonstrate that cheap talk games can have unique informative equilibrium outcomes by providing an example of an infinite action bayesian game which absent cheap talk does not possess an equilibrium

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

portfolio applications in electricity markets review private investor and manager perspective trends abstract the private sector plays a major role in the expansion and operation of power systems in most countries especially those running liberalized electricity markets policymakers have the task of inducing private agents through their regulatory designs to make decisions that point toward social welfare maximization conversely it is a task of private agents to protect themselves against the risks of the sector including regulatory risks international fuel price uncertainty climate change policies natural resource availability electricity demand uncertainty co2 clearance prices etc instead of hiding all of these risks within the total project costs and losing competitiveness private agents can use diversification as a strategy to deal with them this paper presents a review of the main applications voids and challenges of portfolio optimization for two key agents of the private sector investors and managers the problem of the investor is to design a technology portfolio to invest in that maximizes its expected returns and limits risks while the manager has to design a portfolio of financial physical instruments long term contracts futures etc to sell buy electricity and hedge against price risks we have found two fundamental issues in the literature the first and most important is excessive confidence in historical data and statistical analysis for predicting future price behavior for a changing future in detriment of more structural analysis structural analysis can include particularities of modern power systems such as future transmission changes congestion operational constraints ramps new entrants new technologies and new demand grow patterns that cannot be taken into account by simply analyzing price historical values the second is the omission of renewable complementarities which is a proven characteristic of dispersed renewable plants that may have important risk mitigation effects although it has largely been ignored in portfolio analysis due to insufficient data modeling limitations and computational complexity

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

an operational policy for a three stage distributive supply chain system with retailers backorders abstract this research deals with a production inventory problem consisting of three stage tree type single producer multi distributor and multi retailer supply chain network where a model has been developed for achieving the lowest total cost for operating a supply chain system with allowable shortage in this research the shortage is assumed to occur in a form of backorder the refrigerator manufacturing can suitably be used to illustrate the scenario which makes the situation more rational and realistic by assumptions the customers will not go somewhere else the cost of lost sale is not included in this case the total cost of this tree type distributive supply chain system is comprised of setup costs and holding costs at all echelons and the backorder cost at retailer level only a replenishment policy is sought to operate the system at a minimum cost the problem is formulated as an unconstrained mixed integer programming problem and a newly developed doubly hybrid meta heuristic algorithm is adopted as the solution procedure the solutions which determine the desired replenishment policy for the producer distributors and retailers are obtained to minimize the total system cost a sensitivity analysis is performed to evaluate the outcome of the proposed solution procedure presented in this research numerical results are generated to demonstrate the solution procedure and future research is indicated for further study

an exact policy for enhancing buyer supplier linkage in supply chain system abstract kim s l and ha d 2003 a jit lot splitting model for supply chain management enhancing buyer supplier linkage international journal of production economics 86 1 10 proposed a novel cooperative method for synchronizing supply with actual customer demand in a just in time scenario however all decision variables obtained using their model may not be integers making it difficult to be implemented in fixed cycle applications i e a planning horizon of one time period in addition their model can only be used to solve joint optimization for single buyer and single supplier furthermore problems arise when resource constraints are added to their model because traditional inventory models do not allow constraints to be added by the decision maker arbitrarily to improve the practical utility of the model of kim and ha 2003 we derive a mixed integer optimization approach which not only can be applied to the joint optimization for the multi buyer and single supplier but also all decision variables obtained are executable integers for the planning horizon of one time period to suit real world situations infinite planning horizon scenario is also considered in this study in addition illustrative examples are included to demonstrate the usefulness of the proposed models in which the integrated purchase policy being superior to independent optimization can be clearly seen moreover the analytical superiority of the proposed models in terms of execution time can be seen through a computational experiment conduced on a set of logical number of buyers in the multi buyer and single supplier problem finally the performance of various approaches i e proposed models and genetic algorithm is also examined to provide valuable insight into the practical problem

non cooperative strategies for production and shipment lot sizing in one vendor multi buyer system abstract this paper considers a decentralized dynamic production distribution control a discrete deterministic model in which a vendor produces a product and supplies it to the buyer is considered several papers on vendor buyer integrated production inventory management assume that policies are set by a central decision maker to optimize total system performance although vendor and buyer may agree to minimize the total cost at least one of them has a private incentive to deviate from the agreement in the competitive situation the objective is to determine schedules which minimize the individual average total cost of production shipment and stockholding we assume that the division of shipment costs is centrally coordinated or negotiated initially it leads to a class of non cooperative constrained games indexed by two parameters connected with partitions of shipment costs non cooperative strategies are considered as feasible strategies in a restricted non cooperative game some properties of equilibrium strategies are investigated as acceptable equilibrium strategies of subgames in the game

an empirical analysis of the risk of crude oil imports in china using improved portfolio approach abstract this paper quantifies the diversification index of china s crude oil imports during the period 1996 2004 and explores the relationship between the monthly prices and brent crude oil cash prices accordingly we calculate the systematic and specific risks using portfolio theory of china s crude oil import over the period 1996 2004 because china s crude oil import increased rapidly since 1996 we improve upon the traditional portfolio theory and develop a risk index model of portfolio theory for crude oil imports in order to explore objectively the changes in china s crude oil import risks the results show that china s crude oil import risk is affected extensively by the fluctuation of international oil prices so the traditional portfolio theory is insufficient to measure china s crude oil import risk the improved portfolio theory risks index model reflects the effect of international oil prices diversification imports and geopolitics factors etc on crude oil import risk and changes in crude oil import risk therefore the risk index model of portfolio theory provides greater theoretical and methodological robustness as an indicator of china s crude oil import security than that offered from the application of traditional measures of dependence

communication in bargaining over decision rights abstract this paper develops a model of bargaining over decision rights between an uninformed principal and an informed but self interested agent we introduce two different bargaining mechanisms tacit and explicit bargaining in tacit bargaining an uninformed principal makes a take it or leave it price offer to the agent who then decides whether to accept or reject the offer in the equilibrium of the game the principal inefficiently screens out some agent types so that the agent s private information cannot be fully utilized when the decision is made in explicit bargaining in which parties can communicate explicitly via cheap talk before tacit bargaining however an equilibrium with no such inefficient screening exists even when the conflict of interest is arbitrarily large we also follow a mechanism design approach showing that under certain conditions explicit bargaining is an optimal bargaining mechanism that maximizes the joint surplus of the parties

the scheduling of economic lot sizes on volume flexible production systems abstract previous efforts on solving the classical economic lot scheduling problem elsp assume pre determined and inflexible production rates production rates in many cases such as orders filled by a machine can be changed moreover unit production cost of an item depends on its production rate in this paper we extend the elsp model to cases where production rates are decision variables unit production cost for each item becomes a function of its production rate we propose an algorithm to find a solution to the modified economic lot scheduling problem for special unit production cost functions and illustrate the results with numerical examples

a one vendor multi buyer integrated inventory model abstract we consider a one vendor multi buyer integrated inventory model the vendor seeks to minimize his total annual cost subject to the maximum costs which buyers are prepared to incur in order to implement this model the vendor only needs to know buyer s annual demand and previous order frequency which can be inferred from buyer s past ordering behavior we find the optimal solution for the one vendor one buyer case and present a heuristic approach for the one vendor multi buyer case

the common cycle approach to the elsp problem with insufficient capacity abstract a production facility is used to produce more than a single item in order to maximize its utilization this however introduces a well known phenomenon of interference which gives rise to the class of economic lot scheduling problems in solving this problem researchers have always assumed that the production capacity is high enough to meet the demand of all items that are produced in this paper we relax the capacity constraint and analyze the lot scheduling problem under insufficient capacity we specifically study the two product problem using the common cycle approach and then discuss a special extension that treats any number of products

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

energy risk management through self exciting marked point process abstract crude oil is a dynamically traded commodity that affects many economies we propose a collection of marked self exciting point processes with dependent arrival rates for extreme events in oil markets and related risk measures the models treat the time among extreme events in oil markets as a stochastic process the main advantage of this approach is its capability to capture the short medium and long term behavior of extremes without involving an arbitrary stochastic volatility model or a prefiltration of the data as is common in extreme value theory applications we make use of the proposed model in order to obtain an improved estimate for the value at risk in oil markets empirical findings suggest that the reliability and stability of value at risk estimates improve as a result of finer modeling approach this is supported by an empirical application in the representative west texas intermediate wti and brent crude oil markets

an incremental discount pricing schedule with multiple customers and single price break abstract this paper analyzes how a supplier can formulate the terms of a quantity discount pricing schedule assuming a single incremental discount system a model is developed from which an algorithm is derived for an optimal discount schedule the cases are investigated in which both the discount rate and the break point are unknown and either one is prescribed a numerical example is presented to illustrate the algorithm developed

multi buyer discount pricing abstract this article gives an exact optimal solution to the problem of finding the optimal discount price and price break quantity for a seller dealing with one buyer it also gives a method for solving the problem when one seller offers a single quantity discount schedule to many buyers the discount is of the all quantity type and the model of the cost structure was originally proposed by crowther

optimal production and shipment models for a single vendor single buyer integrated system abstract this paper develops a more general production inventory model for a single vendor single buyer integrated system unlike the hitherto existing production inventory models for the vendor buyer system the present model neither requires the buyer s unit holding cost greater than the vendor s nor assumes the structure of shipment policy secondly the model is extended to the situation with shortages permitted based on shortages being allowed to occur only for the buyer thirdly the paper also presents a corresponding production inventory model for a deteriorating item for the integrated system the solution procedures are provided for finding the optimal production and shipment policies and illustrated with numerical examples three significant insights are shown 1 no matter whether the buyer s unit holding cost is greater than the vendor s or not the present model always performs best in reducing the average total cost as compared to the hitherto existing models 2 if the buyer s unit holding cost is less than the vendor s the optimal shipment policy for the integrated system will only comprise shipments with successive shipment sizes increasing by a fixed factor it is different from that obtained by hill hill r m 1999 the optimal production and shipment policy for the single vendor single buyer integrated production inventory problem international journal of production research 37 2463 2475 for the opposite case 3 when designing a single vendor single buyer integrated system making the buyer s unit holding cost lower than the vendor s is more beneficial to the system if shortages are not permitted to occur otherwise it just reverses

an optimal batch size for integrated production inventory policy in a supply chain abstract this study presents a new integrated production inventory policy under a finite planning horizon and a linear trend in demand we assume that the vendor makes a single product and supplies it to a buyer with a non periodic and just in time jit replenishment policy in a supply chain environment the objective is to minimize the joint total costs incurred by the vendor and the buyer in this study first we develop a mathematical model and prove that it has the optimal solution then we describe an explicit solution procedure for obtaining the optimal solution finally we provide two numerical examples to illustrate both increasing and decreasing demands in our proposed model and we show that the performance of the integrated consideration is better than the performance of any independent decision from either the buyer or the vendor

note on a quantity discount pricing model to increase vendor profits monahan monahan james p 1984 a quantity discount pricing model to increase vendor profits management sci 30 june 720 726 develops a model for establishing an optimal quantity discount schedule from a vendor s viewpoint in this note we show that this model is limited to the case where the vendor buys from another supplier incorporating vendor s inventory carrying costs we develop a generalized version of monahan s model and demonstrate its equivalence with the joint economic lot size approach suggested by banerjee banerjee avijit 1986 a joint economic lot size model for purchaser and vendor decision sci 17 summer 292 311

forecasting the var of crude oil market do alternative distributions help abstract accurate modeling of the empirical distribution of crude oil market returns is extremely important in estimating risk measures in addition to several commonly used distributions alternative distributions are explored in this study some of which account for the asymmetry and heavy tails simultaneously found in distributions and contain more tail parameters to separately depict the right and left tails when forecasting the value at risk var of crude oil markets during highly volatile periods seven backtests are also conducted to compare the var forecasting accuracy among different distributions the empirical results indicate that a highly volatile environment challenges the commonly used distributions and the four risk models based on commonly used distributions are rejected about 27 to 38 of the time the alternative distributions i e skewed general error distributions sged generalized hyperbolic skewed student t distributions ghst and generalized asymmetric student t gast distributions generally produce more accurate var measurement and gast gives the best measurement accuracy the empirical results imply that risk managers or policymakers should further consider more flexible distributions such as sged ghst or gast in particular when quantifying or managing the risk in turbulent market times

the minimum cvar strategy with semi parametric estimation in carbon market hedging problems abstract effective hedging strategies are important in reducing price volatility risk for business investors and companies participating into carbon markets in this paper we investigate the risk triggered by price fluctuation of european union allowance eua a semi parametric approach with cornish fisher expansion which approximates the quantile using the higher moments of the distribution is provided to estimate hedging ratios using cvar as risk objective function the approach can successfully capture the features of higher moments with the heavy tailed and higher kurtosis distribution of the eua returns which tends to be neglected the hedging performances of minimum cvar model we proposed and the conventional minimum variance model are evaluated and compared our empirical results show that minimum cvar hedging strategy generally outperforms the other in sample using all the effectiveness criteria while it is not consistent out of sample the proposed semi parametric minimum cvar strategy with cornish fisher expansion is advisable in carbon market hedging problems

the joint economic lot size problem a review abstract this article reviews lot size models which focus on coordinated inventory replenishment decisions between buyer and vendor and their impact on the performance of the supply chain these so called joint economic lot size jels models determine order production and shipment quantities from the perspective of the supply chain with the objective of minimizing total system costs this paper first describes the problem studied introduces the methodology of the review and presents a descriptive analysis of the selected papers subsequently papers are categorized and analyzed with respect to their contribution to the coordination of different echelons in the supply chain finally the review highlights gaps in the existing literature and suggests interesting areas for future research

environmental performance impacts of vendor buyer coordination abstract effective coordination is a hallmark of successful supply chain management without such coordination vendors and buyers will act independently to make decisions that optimize their own objectives e g maximize their respective profits or minimize their costs this non coordinated approach is unlikely to be optimal when one considers the supply chain as a whole most vendor buyer coordination research concentrates only on an objective of minimizing total system costs but with the increasing environmental awareness in business and the general public many organizations acknowledge that strategies and practices which incorporate environmental considerations are essential to acquire a competitive advantage the objectives of this research are concerned not only with the economic impact of vendor buyer coordination on the organizations involved but also with the wider effects on society such as the effects of pollution on the environment this research demonstrates how to effectively incorporate environmental issues into vendor buyer coordination first we study the impacts of cost minimizing vendor buyer coordination models on environmental performance when compared with independent non coordinated optimization second we develop a single vendor multi buyer coordination model that includes both costs and environmental performance measures in its objective function a numerical example and a real case study show how both the total system cost and the environmental performance can be simultaneously improved

energy risk management and value at risk modeling abstract the value of energy trades can change over time with market conditions and underlying price variables the rise of competition and deregulation in energy markets has led to relatively free energy markets that are characterized by high price shifts within oil markets the volatile oil price environment after opec agreements in the 1970s requires a risk quantification value at risk has become an essential tool for this end when quantifying market risk there are various methods for calculating value at risk the methods we introduced in this paper are historical simulation arma forecasting and variance covariance based on garch modeling approaches the results show that among various approaches the hsaf methodology presents more efficient results so that if the level of confidence is 99 the value at risk calculated through hsaf methodology is greater than actual price changes in almost 97 6 percent of the forecasting period

a single vendor single manufacturer integrated inventory model with stochastic demand and variable production rate abstract this paper investigates an alternative way to react to demand uncertainty in an integrated inventory model namely the variation of the production rate that enables the manufacturer to reduce lead times and the corresponding demand uncertainty to investigate the impact of variable production rates on the supply chain this paper considers a single vendor single manufacturer integrated inventory model where the vendor ships finished products in multiples of full truckloads to the manufacturer the objective of the model is to coordinate both production and distribution of the product in such a way that the total costs of the supply chain are minimized a solution procedure is suggested and the behaviour of the model is analysed in numerical examples obviously the total supply chain cost is reduced when the manufacturer s production rate is included as a decision variable in the model these savings can generally benefit both the vendor and the manufacturer however in situations where coordinated decision making is initially not beneficial to the vendor the supply chain members can benefit from a revenue sharing contract that supports the sharing of the total savings the model proposed in the paper at hand supports both the determination of an optimal production rate as well as the distribution of coordination benefits among the supply chain members

oil price fluctuation volatility spillover and the ghanaian equity market implication for portfolio management and hedging effectiveness abstract this study attempts to contribute to the literature on stock markets and energy prices by examining the dynamic volatility and volatility transmission between oil and ghanaian stock market returns in a multivariate setting using the recently developed var garch var agarch and dcc garch frameworks in turn the models results are used to compute and analyze the optimal weights and hedge ratios for oil stock portfolio holdings for comparison purposes and to put the paper more in the perspective of west africa the nigerian stock market is also included in the analysis our findings point to the existence of significant volatility spillover and interdependence between oil and the two stock market returns while spillover effects are stronger for nigeria the transmission of volatility is much more apparent from oil to stock than from stock to oil in the case of ghana also the study demonstrates evidence of short term predictability in oil and stock price changes through time and reveals that conditional volatility changes more rapidly as result of substantial effects of past volatility rather than past news shocks for all market returns moreover we show that there is a slightly more effective hedge in the two stock markets under the dcc garch framework our preferred model compared to the other two models although hedging effectiveness is much greater for ghana on the whole our findings for optimal hedge ratios are consistent with other studies and particularly the view that oil assets should be an integral part of a diversified portfolio of stocks and suggest that a better understanding of volatility links is crucial for portfolio management in the presence of oil price risk finally the existence of multivariate asymmetric effects and dynamic conditional correlations as revealed by the var agarch and dcc garch models make it clear that the assumptions of symmetric effects and constant conditional correlations are not supported empirically

a genetic algorithm for optimal operating parameters of vmi system in a two echelon supply chain abstract this paper deals with the operational issues of a two echelon single vendor multiple buyers supply chain tsvmbsc model under vendor managed inventory vmi mode of operation the operational parameters to the above model are sales quantity and sales price that determine the channel profit of the supply chain and contract price between the vendor and the buyer which depends upon the understanding between the partners on their revenue sharing in order to find out the optimal sales quantity for each buyer in tsvmbsc problem a mathematical model is formulated optimal sales price and acceptable contract price at different revenue share are subsequently derived with the optimal sales quantity a genetic algorithm ga based heuristic is proposed to solve this tsvmbsc problem which belongs to nonlinear integer programming problem nip the proposed methodology is evaluated for its solution quality furthermore the robustness of the model with its parameters which fluctuate frequently and are sensitive to operational features is analysed

quality improvement and setup reduction in the joint economic lot size model abstract the co maker concept has become accepted practice in many successful global business organizations this fact has resulted in a class of inventory models known as joint economic lot size jels models heretofore such models assumed perfect quality production on the part of the vendor this paper relaxes this assumption and proposes a quality adjusted jels model in addition classical optimization methods are used to derive models for the cases of setup cost reduction quality improvement and simultaneous setup cost reduction and quality improvement for the quality adjusted jels numerical results are presented for each of these models comparisons are made to the basic quality adjusted model results indicate that all three policies exhibit significantly reduced total cost however the simultaneous model results in the lowest cost overall and the smallest lot size this suggests a synergistic impact of continuous improvement programs that focus on both setup and quality improvement of the vendor s production process sensitivity analysis indicates that the simultaneous model is robust and representative of practice

supply chain coordination perspectives empirical studies and research directions supply chains sc are generally complex and are characterized by numerous activities spread over multiple functions and organizations which pose interesting challenges for effective sc coordination to meet these challenges sc members must work towards a unified system and coordinate with each other a systematic literature review is presented in this paper to throw light on the importance of sc coordination the objectives of this paper are to report and review various perspectives on sc coordination issues understand and appreciate various mechanisms available for coordination and identify the gaps existing in the literature a framework is suggested indicating scope for further research

optimal production inventory policy for an integrated multi stage supply chain with time varying demand abstract an integrated multi stage supply chain with time varying demand over a finite planning horizon is considered in this paper the objective is to devise the optimal production inventory policy to minimize the total operational cost the model is formulated as a mixed integer nonlinear programming problem the problem is represented as a weighted directed acyclic graph the global minimum total operational cost is computed in polynomial time by the developed algorithm two numerical examples of a seasonal product and a product over its life cycle are studied to illustrate the results a sensitivity analysis of the system parameters is conducted to assist the supply chain decision makers