new results on the relationship among risk aversion prudence and temperance abstract this note studies the relationships between different aspects of agent s preferences toward risk we show that under the assumptions of non satiation and bounded marginal utility prudence implies risk aversion imprudence implies risk loving and that temperance implies prudence intemperance implies imprudence the implications of these results for comparing risks in the cases of increase in risk increase in downside risk and increase in outer risk are discussed

risk sensitive dividend problems abstract we consider a discrete time version of the popular optimal dividend payout problem in risk theory the novel aspect of our approach is that we allow for a risk averse insurer i e instead of maximising the expected discounted dividends until ruin we maximise the expected utility of discounted dividends until ruin this task has been proposed as an open problem in gerber and shiu 2004 the model in a continuous time brownian motion setting with the exponential utility function has been analysed in grandits et al 2007 nevertheless a complete solution has not been provided in this work instead we solve the problem in discrete time setup for the exponential and the power utility functions and give the structure of optimal history dependent dividend policies we make use of certain ideas studied earlier in bauerle and rieder 2011 where markov decision processes with general utility functions were treated our analysis however includes new aspects since the reward functions in this case are not bounded

on the structure of lost sales inventory models we provide a new approach to the structural analysis of the standard lost sales inventory system this approach is we think easier to work with than the original one we also derive new bounds on the optimal policy then we show that more variable demand leads to higher cost finally we extend the analysis to several important variations of the basic model

on investor preferences and mutual fund separation abstract we extend cass and stiglitz s analysis of preference based mutual fund separation we provide a complete characterization of the general k fund separation we show that some instances of separation with many funds can be constructed by adding inverse marginal utility functions having separation with one or a few funds we also show that there is money separation in which we can choose the riskless asset as one of the funds if and only if there is a fund which may or may not be the riskless asset with a constant allocation as wealth changes in general we do not know how to write the separating utility functions in closed form but we can do so in the special case of sahara utility defined by chen et al and for a new class of gobi preferences introduced here

international portfolio choice and political instability risk a multi objective approach abstract the benefits derived from international portfolio diversification into foreign nations including the less developed countries are well documented yet this practice is discouraged due to market imperfections such as political instability in practice nations may be differentiated further by many aspects such as border controls or political and social trends which constrain private transactions and financial decisions this paper attempts to examine 1 whether the home asset bias in a portfolio holding is associated with higher political instability risk and 2 to what extent international diversification among stocks in the presence of such risk outperforms domestic stock portfolios using alternative instability risk proxies in the context of a discrete time version of mean variance framework we corroborate the impact of this type of risk on international portfolio investment decisions

demand seasonality in retail inventory management abstract we investigate the value of accounting for demand seasonality in inventory control our problem is motivated by discussions with retailers who admitted to not taking perceived seasonality patterns into account in their replenishment systems we consider a single location single item periodic review lost sales inventory problem with seasonal demand in a retail environment customer demand has seasonality with a known season length the lead time is shorter than the review period and orders are placed as multiples of a fixed batch size the cost structure comprises of a fixed cost per order a cost per batch and a unit variable cost to model retail handling costs we consider four different settings which differ in the degree of demand seasonality that is incorporated in the model with or without within review period variations and with or without across review periods variations in each case we calculate the policy which minimizes the long run average cost and compute the optimality gaps of the policies which ignore part or all demand seasonality we find that not accounting for demand seasonality can lead to substantial optimality gaps yet incorporating only some form of demand seasonality does not always lead to cost savings we apply the problem to a real life setting using point of sales data from a european retailer we show that a simple distinction between weekday and weekend sales can lead to major cost reductions without greatly increasing the complexity of the retailer s automatic store ordering system our analysis provides valuable insights on the tradeoff between the complexity of the automatic store ordering system and the benefits of incorporating demand seasonality

optimal capacity investment decisions with two sided fixed capacity adjustment costs in this paper we consider the optimal management of capacity when a firm faces fixed costs and variable costs to purchase capacity the firm can also salvage capacity and receive a variable value per unit capacity salvaged but faces a different fixed cost in this case each period the firm faces a stochastic demand and maintenance costs for capacity that it decides to keep the firm would thus like to decide how much capacity it should purchase or salvage each period we introduce a new concept which we call k1 k2 concavity and show that the profit to go function satisfies this property this enables us to characterize the structure of an optimal policy which is rather complex consisting of multiple regions in which different decisions are made we show how special cases of this problem e g no fixed costs expansion or contraction not allowed reduce to well known results and how k1 k2 concavity is a generalization of concavity k concavity and sym k concavity we also show how different lead times for purchasing or salvaging capacity can be integrated into the model finally we extend the model to the case where demand is markov modulated and a portion of capacity can deteriorate in each period

base stock policies for production inventory problems with uncertain capacity levels abstract in this paper we consider a single item stochastic demand production inventory problem where the maximum amount that can be produced or ordered in any given period is assumed to be uncertain inventory levels are reviewed periodically the system operates under a stationary modified base stock policy the intent of our paper is to present a procedure for computing the optimal base stocl level of this policy under expected average cost per period criterion this procedure would provide guidance as to the appropriate amount of capacity to store in the form of inventory in the face of stochastic demand and uncertain capacity in achieving this goal our main contribution is to establish the analogy between the class of base stock production inventory policies that operate under demand capacity uncertainty and the g g 1 queues and their associated random walks we also present example derivations for some important capacity distributions

approximation algorithms for perishable inventory systems we develop the first approximation algorithms with worst case performance guarantees for periodic review perishable inventory systems with general product lifetime for both backlogging and lost sales models the demand process can be nonstationary and correlated over time capturing such features as demand seasonality and forecast updates the optimal control policy for such systems is notoriously complicated thus finding effective heuristic policies is of practical importance in this paper we construct a computationally efficient inventory control policy called the proportional balancing policy for systems with an arbitrarily correlated demand process and show that it has a worst case performance guarantee less than 3 in addition when the demands are independent and stochastically nondecreasing over time we propose another policy called the dual balancing policy which admits a worst case performance guarantee of 2 we demonstrate through an extensive numerical study that both policies perform consistently close to optimal

capacitated multi item inventory systems with random and seasonally fluctuating demands implications for postponement strategies we address multi item inventory systems with random and seasonally fluctuating and possibly correlated demands the items are produced in two stages each with its own lead time in the first stage a common intermediate product is manufactured the production volumes in the first stage are bounded by given capacity limits we develop an accurate lower bound and close to optimal heuristic strategies of simple structure the gap between them evaluated in an extensive numerical study is on average only 0 45 we use the model to investigate the benefits of various delayed product differentiation postponement strategies as well as other strategic questions including i the benefits of flexible versus dedicated production facilities ii the trade off between capacity and inventory investments and iii the trade off between capacity investments and service levels

climate change health care access and regional influence on components of u s agricultural productivity this article examines factors driving three components of total factor productivity change tfpc in u s agriculture technical change tc technical efficiency change tec and scale and mix e

a multi period fuzzy portfolio optimization model with minimum transaction lots abstract in this paper we consider a multi period fuzzy portfolio optimization problem with minimum transaction lots based on possibility theory we formulate a mean semivariance portfolio selection model with the objectives of maximizing the terminal wealth and minimizing the cumulative risk over the whole investment horizon in the proposed model we take the return risk transaction costs diversification degree cardinality constraint and minimum transaction lots into consideration to reflect investor s aspiration levels for the two objectives a fuzzy decision technique is employed to transform the proposed model into a single objective mixed integer nonlinear programming problem then we design a genetic algorithm for solution finally we give an empirical application in chinese stock markets to demonstrate the idea of our model and the effectiveness of the designed algorithm

market failure and control of labour power towards an explanation of structure and change in indian agriculture part 1 1 although existing approaches do on occasion shed light on certain specific aspects of indian agriculture in general they run into problems of methodology or content or more frequently both in particular it is misleading to treat indian agri culture in peasant economy no markets or neoclassical perfect market terms and problematic to view it as semi feudal markets subordinate to extra economic factors 2 analysis of the relationships between farm size land productivity sharecropping and mechanisation suggest the need for an integrated model which emphasises both the unemployment and poverty of poor peasants and the problems of supervision and control of wage labour and tenants 3 proper appreciation of the interlinked role of these factors can help to explain the system s inability to combine the abundant labour of the poor with resources owned largely by the rich it can also go on to explain institutional responses like sharecropping as partial solutions to the problem of intensifying labour use and technological ones such as mechanisation as a means of delinking large farm growth from the need to intensify labour use 4 the tensions and choices between these responses underlie both the problem of stagnation and the phenomenon of switches from sharecropping to mechanisation 5 for associated reasons more rapid growth in indian agriculture is unlikely without major institutional changes to create much new employment and is likely to be more capital intensive than is usually assumed

crop insurance in a political economy an alternative perspective on agricultural policy lawmakers often subsidize farmers in times of financial distress this article models this political impulse as a constraint on government farm policy describing how ex ante government farm insurance can deter ex post disaster relief and improve production incentives by countering the moral hazard that otherwise prevails absent ex ante government policy ex post relief takes the form of revenue insurance which prompts excessive entry into farm production and under production by operating farmers ex ante government policy can raise economic and political welfare by buying out low productivity farmers and offering profitable farmers a combination of revenue insurance price supports and a program participation fee copyright 2003 oxford university press

share tenancy external risk and labour use a note on pakistani data this article outlines a labour market based explanation of the institution of sharecropping it is argued that two distinct rationales for sharecropping within the non tradable labour based explanation pertain to the supervisory labour endowments of land owners on the one hand and non supervisory family labour endowments of tenant households on the other the validity of these rationales is tested at a macro level based on data computed for each district of the punjab and sind provinces in pakistan it is found that a labour market based explanation of sharecropping is important in the pakistan context the analysis has some regional and dynamic implications as well

agricultural disaster payments in the southeastern us do weather and climate variability matter governments around the world are forced to react to disasters caused by weather the agricultural sector is particularly susceptible to weather extremes and adverse climate conditions in the us agricultural disaster payments account for a significant part of total agricultural subsidies the payments and their distribution are more important in the areas most affected by disastrous weather events usually coinciding with areas of pronounced impact of the el nino southern oscillation enso in this article the impact of weather and climate as well as some economic variables on disaster payments is analysed using county level data from four states in the southeastern united states the results suggest that weather and climate variables explain most of the crop disaster payments at the county level while socioeconomic variables do not suggesting that advancements in weather and climate forecasts could be helpful in planning for disaster compensation

chance constrained optimization for pension fund portfolios in the presence of default risk abstract in this paper we consider the portfolio optimization problem for a pension fund consisting of various government and corporate bonds the aim of the problem is to maximize the fund s cash position at the end of the time horizon while allowing for the possibility of bond defaults we model this problem as a stochastic discrete time optimal control problem with a chance constraint that ensures all future outgoing commitments can be met with sufficiently high probability we then introduce a corresponding deterministic formulation that is a conservative approximation of the original stochastic optimal control problem this approximate problem can be solved using gradient based optimization techniques we conclude the paper with a simulation study

inventory control in a fluctuating demand environment we present an inventory model where the demand rate varies with an underlying state of the world variable this variable can represent economic fluctuations or stages in the product life cycle for example we derive some basic characteristics of optimal policies and develop algorithms for computing them in addition we show that certain monotonicity patterns in the problem data are reflected in the optimal policies

on the equivalence of quadratic optimization problems commonly used in portfolio theory abstract in the paper we consider three quadratic optimization problems which are frequently applied in portfolio theory i e the markowitz mean variance problem as well as the problems based on the mean variance utility function and the quadratic utility conditions are derived under which the solutions of these three optimization procedures coincide and are lying on the efficient frontier the set of mean variance optimal portfolios it is shown that the solutions of the markowitz optimization problem and the quadratic utility problem are not always mean variance efficient the conditions for the mean variance efficiency of the solutions depend on the unknown parameters of the asset returns we deal with the problem of parameter uncertainty in detail and derive the probabilities that the estimated solutions of the markowitz problem and the quadratic utility problem are mean variance efficient because these probabilities deviate from one the above mentioned quadratic optimization problems are not stochastically equivalent the obtained results are illustrated by an empirical study

a periodic review inventory model with demand influenced by promotion decisions in this paper we use a markov decision process mdp to model the joint inventorypromotion decision problem the state variable of the mdp represents the demand state brought about by changing environmental factors as well as promotion decisions the demand state in a period determines the distribution of the random demand in that period optimal inventory and promotion decision policies in the finite horizon problem are obtained via dynamic programming under certain conditions we show that there is a threshold inventory level p for each demand state such that if the threshold is exceeded then it is desirable to promote the product for the proportional ordering cost case the optimal inventory replenishment policy is a base stock type policy with the optimal base stock level dependent on the promotion decision

portfolio optimization in a regime switching market with derivatives abstract we consider the optimal asset allocation problem in a continuous time regime switching market the problem is to maximize the expected utility of the terminal wealth of a portfolio that contains an option an underlying stock and a risk free bond the difficulty that arises in our setting is finding a way to represent the return of the option by the returns of the stock and the risk free bond in an incomplete regime switching market to overcome this difficulty we introduce a functional operator to generate a sequence of value functions and then show that the optimal value function is the limit of this sequence the explicit form of each function in the sequence can be obtained by solving an auxiliary portfolio optimization problem in a single regime market and then the original optimal value function can be approximated by taking the limit additionally we can also show that the optimal value function is a solution to a dynamic programming equation which leads to the explicit forms for the optimal value function and the optimal portfolio process furthermore we demonstrate that as long as the current state of the markov chain is given it is still optimal for an investor in a multiple regime market to simply allocate his her wealth in the same way as in a single regime market

asset allocation with correlation a composite trade off abstract we assess the ability of minimum variance portfolio allocation strategies accounting for time varying correlation between assets to provide performance benefits relative to an equally weighted portfolio prior to transaction costs correlation based strategies emphatically outperform the equally weighted benchmark this finding is strongest for short horizon correlation forecasts and attributed to dynamic correlation as opposed to variance forecasts thus estimation error is not found to be the primary obstacle to successful portfolio optimization rather frequent rebalancing and associated transaction costs pose a significant challenge limiting portfolio turnover through short selling restrictions and greater rebalancing error tolerance results in regular outperformance of the correlation based strategies even for large transaction costs taken together these findings provide evidence of a trade off between optimal portfolio performance forecasting horizon rebalancing frequency and transaction costs

multiperiod portfolio optimization models in stochastic markets using the mean variance approach we consider several multiperiod portfolio optimization models where the market consists of a riskless asset and several risky assets the returns in any period are random with a mean vector and a covariance matrix that depend on the prevailing economic conditions in the market during that period an important feature of our model is that the stochastic evolution of the market is described by a markov chain with perfectly observable states various models involving the safety first approach coefficient of variation and quadratic utility functions are considered where the objective functions depend only on the mean and the variance of the final wealth an auxiliary problem that generates the same efficient frontier as our formulations is solved using dynamic programming to identify optimal portfolio management policies for each problem illustrative cases are presented to demonstrate the solution procedure with an interpretation of the optimal policies

pricing weather derivatives this article presents a general method for pricing weather derivatives specification tests find that a temperature series for fresno ca follows a mean reverting brownian motion process with discrete jumps and autoregressive conditional heteroscedastic errors based on this process we define an equilibrium pricing model for cooling degree day weather options comparing option prices estimated with three methods a traditional burn rate approach a black scholes merton approximation and an equilibrium monte carlo simulation reveals significant differences equilibrium prices are preferred on theoretical grounds so are used to demonstrate the usefulness of weather derivatives as risk management tools for california specialty crop growers

design for postponement a comprehensive characterization of its benefits under unknown demand distributions recent papers have developed analytical models to explain and quantify the benefits of delayed differentiation and quick response programs these models assume that while demands in each period are random they are independent across time and their distribution is perfectly known i e sales forecasts do not need to be updated as time progresses in this paper we characterize these benefits in more general settings where parameters of the demand distributions fail to be known with accuracy or where consecutive demands are correlated here it is necessary to revise estimates of the parameters of the demand distributions on the basis of observed demand data we analyze these systems in a bayesian framework assuming that our initial information about the parameters of the demand distributions is characterized via prior distributions we also characterize the structure of close to optimal ordering rules in these systems for a variety of types of order cost functions

hara frontiers of optimal portfolios in stochastic markets abstract in this paper we consider the optimal portfolio selection problem in continuous time settings where the investor maximizes the expected utility of the terminal wealth in a stochastic market the utility function has the structure of the hara family and the market states change according to a markov process the states of the market describe the prevailing economic financial social and other conditions that affect the deterministic and probabilistic parameters of the model this includes the distributions of the random asset returns as well as the utility function we analyzed black scholes type continuous time models where the market parameters are driven by markov processes the markov process that affects the state of the market is independent of the underlying brownian motion that drives the stock prices the problem of maximizing the expected utility of the terminal wealth is investigated and solved by stochastic optimal control methods for exponential logarithmic and power utility functions we found explicit solutions for optimal policy and the associated value functions we also constructed the optimal wealth process explicitly and discussed some of its properties in particular it is shown that the optimal policy provides linear frontiers

the contribution of weather variability to economic sectors every day people make economic decisions based on the weather affecting sales of companies in a wide range of economic sectors in many cases the impact of weather on sales is not constant from

poverty and witch killing many observers have noted that poverty and violence go hand in hand there is a strong negative relationship between economic growth and crime across countries as well as across districts in india and a link between low income and the occurrence of civil war 1 yet existing studies are typically unable to resolve the key econometric identification issues of omitted variable bias and endogeneity to illustrate the unobserved quality of local government institutions may affect both income growth and crime rates and poverty could lead to violence if desperate people with nothing to lose commit more crimes but violence itself may in turn affect economic productivity this paper uses local rainfall variation to identify the impact of income shocks on murder in a rural tanzanian district 2 extreme rainfall resulting in drought or floods is exogenous and is associated with poor harvests and near famine conditions in the region and a large increase in the murder of witches there are twice as many witch murders in years of extreme rainfall as in other years the victims are nearly all elderly women typically killed by relatives these econometric results across 11 years in 67 villages provide novel evidence on the role of income shocks in causing violent crime and religious violence in particular and also provide insights into witchcraft an important social phenomenon in africa rarely studied by economists the view that economic conditions are a driving force behind witch murders is bolstered by the fact that most witch killing in tanzania takes place in poor rural areas largely dependent on rain fed agriculture and that most victims in our sample are from poor households however it is difficult to definitively disentangle this income shock theory from alternative socio cultural explanations the concentration of tanzanian witch murders in a region dominated by one particular ethnic group the sukuma and the especially high number of witch murders in villages where indigenous religious beliefs are strong both point to the important role of non economic factors economic theories and cultural theories are perhaps best viewed as complements the empirical findings demonstrate the power of economics to rationalize a phenomenon that has previously been understood almost solely through a socio cultural lens 3

numerical approximations of optimal portfolios in mispriced asymmetric levy markets abstract we present numerical approximations of optimal portfolios in mispriced levy markets under asymmetric information for informed and uninformed investors having logarithmic preference we apply our numerical scheme to kou 2002 jump diffusion markets by deriving analytic formulas for the first two derivatives of the underlying portfolio objective function which depend only on the levy measure of the jump generating process optimal portfolios are then simulated using the box muller algorithm newton s method and incomplete beta functions convergence dynamics and trajectories of sample paths of optimal portfolios for both investors are presented at different levels of information asymmetry mispricing horizon asymmetry in the kou density jump intensity volatility mean reversion speed and sharpe ratios we also apply the proposed newton s algorithm to compute optimal portfolios for investors in variance gamma markets via instantaneous centralized moments of returns

contracts resource use and productivity in sharecropping this article identifies the contractual terms in sharecropping that result in efficient use of resources evidence is then presented from pakistan to comment on the manner in which landlords ensure that sharecroppers fulfil the terms it is shown that landlords in general specify contract terms that encourage sharecroppers to adopt new techniques of production productivity comparisons are also made for farms under different tenancy contracts to conclude that share cropping tenancies do not appear to result in output loss even when technology is changing

inventory decisions for emergency supplies based on hurricane count predictions abstract this paper addresses a stochastic inventory control problem for manufacturing and retail firms who face challenging procurement and production decisions associated with hurricane seasons specifically the paper presents a control policy in which stocking decisions are based on a hurricane forecast model that predicts the number of landfall hurricanes for an ensuing hurricane season the multi period inventory control problem is formulated as a stochastic programming model with recourse where demand during each pre hurricane season period is represented as a convolution of the current period s demand and an updated estimate of demand for the ensuing hurricane season due to the computational challenges associated with solving stochastic programming problems recent scenario reduction techniques are discussed and illustrated through an example problem the proposed model specifies cost minimizing inventory strategies for simultaneously meeting stochastic demands that occur prior to the hurricane season while proactively preparing for potential demand surge during the season

political action committee contributions and u s congressional voting on sugar legislation this study examines the simultaneous relationship between political action committee pac contributions and congressional votes on u s sugar legislation we extend the conventional analysis by specifying a three equation system in which each congressman s vote depends on contributions received from pro sugar and anti sugar coalitions while the propensity of each of these coalitions to contribute depends simultaneously on the congressman s anticipated voting decision and the contributions of the opposing coalition logrolling is also accommodated by considering the effect that contributions from other coalitions have had on voting decisions we find evidence of a three way linkage between votes and competing campaign contributions and conclude that the effectiveness of pac contributions reflects the dominance of political pressure over ideological concerns

computing the optimal replenishment policy for inventory systems with random discount opportunities the paper considers the optimal control of a single item continuous review inventory system with random demand and discount opportunities items can always be purchased with the regular order setup and variable costs however when a discount opportunity occurs they can also be purchased with a different setup cost and a lower variable cost demands for individual items and discount opportunities occur according to independent poisson processes the paper proposes an algorithm to compute the parameters of the optimal replenishment policy which has been shown to be an r r d d policy wherer

using weather variability to estimate the response of savings to transitory income in thailand this paper measures the extent to which farmers are able to use savings and dissavings to smooth consumption in response to unexpected shocks to income time series information on regional rainfall is used to construct estimates of transitory income due to rainfall shocks the relationship between these measures of transitory income and savings indicates that farm households save a significantly higher fraction of transitory income than nontransitory income jel d91 016 the incomes of farm households in developing countries are notorious for being both low and uncertain policies that increase the incomes of farmers may well be different

a possibilistic mean semivariance entropy model for multi period portfolio selection with transaction costs abstract this paper deals with a multi period portfolio selection problem with fuzzy returns a possibilistic mean semivariance entropy model for multi period portfolio selection is presented by taking into account four criteria viz return risk transaction cost and diversification degree of portfolio in the proposed model the return level is quantified by the possibilistic mean value of return the risk level is characterized by the lower possibilistic semivariance of return and the diversification degree of portfolio is measured by the originally presented possibilistic entropy furthermore a hybrid intelligent algorithm is designed to obtain the optimal portfolio strategy finally the comparison analysis between the possibilistic entropy model and the proportion entropy model is provided by two numerical examples to illustrate the efficiency of the proposed approaches and the designed algorithm

time consistent investment policies in markovian markets a case of mean variance analysis abstract the optimal investment policy for a standard multi period mean variance model is not time consistent because the variance operator is not separable in the sense of the dynamic programming principle with a nested conditional expectation mapping we develop an investment model with time consistency in markovian markets furthermore we examine the differences of the investment policies with a riskless asset from those without a riskless asset analytical solutions for time consistent optimal investment policies and the resulting mean variance efficient frontier are obtained finally using numerical examples we show that the optimal investment policy derived from our model is more efficient than that of the standard mean variance model in which the trade off is determined between the mean and variance of the terminal wealth

cash management in a randomly varying environment we study a cash management system in which the distribution of the cash flow xn in period n 1 2 depends on the state in of a randomly varying environment sufficient conditions are found for the optimality of a simple transfer rule generalizing and partially improving the well known results for the classical case with i i d cash flows these and further structural results obtained for the cash balance are shown to reduce the computational effort drastically in determining an optimal transfer rule in addition structural and computational results w r t the environment are derived finally some examples are given for economic and statistical environments and their interactions with the cash flow process

transaction costs risk aversion and the choice of contractual arrangements publisher summary this chapter discusses transaction costs risk aversion and the choice of contractual arrangements every transaction involves a contract and the transactions conducted in the marketplace entail outright or partial transfers of property rights among individual contracting parties the contractual arrangements through which these transfers are negotiated are several and varied the chapter presents a theory that states that economic efficiency is the same under various land tenure arrangements subject to the constraint of private property rights although transaction costs exist in the real world the theory enables the understanding of much of the farming behavior however the presence of a variety of contractual arrangements under the same constraint of competition poses the question of the choice of these arrangements if a firm can increase efficiency in production by employing productive resources of more than one resource owner a contract to combine the resources will be obtained the formation of the contract involves partial transfers of property rights in one form or another such as leasing hiring or mortgaging

stopped myopic policies in some inventory models with generalized demand processes this paper considers single item inventory systems with immediate delivery and no economies of scale bounds are provided on the value loss relative to optimal cost for restricting attention to the class of inventory stocking policies that behave myopically up to a specified stopping time the stopping time may be random and may depend on demand histories as well as information exogenous to the firm the bounds are robust to the nature of the demand process faced after the stopping time so are applicable when the statistics of demand after the stopping time are unknown stopping times that are large with high probability imply that near term decisions are completely specified with high probability the general bounding results allow one to consider demand processes that may otherwise be analytically intractable it is shown that the class of demand models for which the assumption of additive i i d shocks is appropriate is the same class admitting effective myopic stocking policies the bounds also make rigorous the intuitive notion that myopic policies are least effective in systems with precipitous drops in demand coupled with an inability to recover cash invested in inventory the option of selling inventory at discount is a reality in many real systems and enhances the attractiveness of the myopic stocking policy in numerical examples the myopic policy is shown to be an effective competitor in a range of systems for which optimal policies are not known the results suggest that for systems with immediate delivery no economies of scale and no currently known optimal policy the myopic stocking rule is a reasonable default policy to adopt

analysis of an inventory system under backorder correlated deterministic demand and geometric supply process abstract in this article we propose a single item periodic review model that investigates the effects of changes in the demand process that occur after stockout realizations we investigate a system where the demands in successive periods are deterministic but affected by the backorder realizations in order to capture the effects of changes in the demand process we use a geometric type supply availability we analytically derive the necessary components for obtaining profit related performance measures and provide computational analysis

joint pricing and inventory control with a markovian demand model abstract we consider the joint pricing and inventory control problem for a single product over a finite horizon and with periodic review the demand distribution in each period is determined by an exogenous markov chain pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged the surplus costs as well as fixed and variable costs are state dependent we show the existence of an optimal s s p type feedback policy for the additive demand model we extend the model to the case of emergency orders we compute the optimal policy for a class of markovian demand and illustrate the benefits of dynamic pricing over fixed pricing through numerical examples the results indicate that it is more beneficial to implement dynamic pricing in a markovian demand environment with a high fixed ordering cost or with high demand variability

inventory control with information about supply conditions this paper presents an inventory control model which includes a markovian model of the supply system as that system evolves over time so do the replenishment leadtimes the optimal policy has the same structure as in standard models but its parameters change dynamically to reflect current supply conditions in this setting contrary to conventional wisdom a longer leadtime does not necessarily imply more inventory the leadtime is important but so is a concept we call order coverage

batch quantities when forecasts are improving this paper considers the choice of initial batch quantities when demand forecasts are improving we assume that the standard deviation of the demand per period is decreasing exponentially and approaching a long run value a discrete time stochastic single level inventory model is considered there are traditional holding and backorder costs as well as an ordering cost the ordering periods must be determined in advance and we wish to determine a suitable schedule

technical note on optimal policies for inventory systems with batch ordering we study a periodically reviewed multiechelon inventory system in series such that order quantities at every stage have to be multiples of a given stage specific batch size the batch sizes are nested in the sense that the batch size for every stage is an integer multiple of the batch size for its downstream stage the problem is that of determining the policy that minimizes the expected discounted sum of costs over a finite horizon the result is that an echelon r nq policy is optimal when demands are independent across periods or more generally markov modulated we also comment on algorithmic implications of our result and on extensions

portfolio optimization with disutility based risk measure abstract in this paper we propose a quantile based risk measure which is defined using the modified loss distribution according to the decision maker s risk and loss aversion the properties related to different classes of disutility functions are established a portfolio selection model in the mean risk framework is proposed and equivalent formulations of the model generating the same efficient frontier are given the advantages of this approach are investigated using real world data from nyse the differences between the efficient frontier of the proposed model and the classical mean variance and mean cvar are quantified and interpreted extensive experiments show that the efficient portfolios obtained by using the proposed model exhibit lower risk levels and an increased satisfaction compared to the other two mean risk models

myopic policies for some inventory models with uncertain demand distributions the majority of papers on stochastic inventory theory make the assumption that the distribution of consumer demand in each time period is known with certainty while this assumption is unsupported in many applied contexts it is conventionally held that more realistic models are more difficult to solve and will not yield simple operational policies this paper shows that a simple inventory policy based upon a critical fractile can be optimal or near optimal in some inventory models with parameter adaptive demand processes in these some parameter of the demand distribution is not known with certainty and estimates of the parameter are updated in a statistical fashion as demand is observed through time examples include exponentially smoothed forecasts and bayesian updating of parameter estimates bounds on the value loss relative to optimal cost when using the critical fractile policy can be calculated directly from the problem data some numerical examples illustrate the technique

bullwhip effect measurement and its implications the bullwhip effect or demand information distortion has been a subject of both theoretical and empirical studies in the operations management literature in this paper we develop a simple set of formulas that describe the traditional bullwhip measure as a combined outcome of several important drivers such as finite capacity batch ordering and seasonality our modeling framework is descriptive in nature as it features certain plausible approximations that are commonly employed in practical inventory systems the results are nonetheless compelling and can be used to explain various conflicting observations in previous empirical studies building on the theoretical framework we discuss the managerial implications of the bullwhip measurement we show that the measurement can be completely noninformative about the underlying supply chain cost performance if it is not linked to the operational details such as decision intervals and leadtimes specifically we show that an aggregated measurement over relatively long time periods can mask the operational level bullwhip in addition we show that masking also exists under product or location aggregation in some illustrative cases

a discontinuous mispricing model under asymmetric information we study a discontinuous mispricing model of a risky asset under asymmetric information where jumps in the asset price and mispricing are modelled by levy processes by contracting the filtration of the informed investor we obtain optimal portfolios and maximum expected utilities for the informed and uninformed investors we also discuss their asymptotic properties which can be estimated using the instantaneous centralized moments of return we find that optimal and asymptotic utilities are increased due to jumps in mispricing for the uninformed investor but the informed investor still has excess utility provided there is not too little or too much mispricing

joint pricing procurement control under fluctuating raw material costs abstract we consider a firm that periodically procures raw material units stores them and processes them into finished products upon order arrivals the raw material cost evolves in a markovian fashion whereas the demand process is influenced by both the raw material cost and sales prices charged by the firm the firm controls both the raw material procurement activity and sales price in each period we show the optimality of base stock list price type of policies with the additional raw cost dependence under conditions that are verifiable when the firm engages in price competition with other firms tapping into the same raw material market and when the raw material cost process has time continuity and mean reversion tendencies we identify two monotone patterns in which policy parameters should follow as the raw material cost fluctuates cost increases are also shown to translate into price increases at low inventory levels in other circumstances however there does not appear to be a clear pattern as to how the firm should pass cost increases on to end customers our numerical evidence unequivocally supports the adaptation of procurement and pricing controls to changing raw material costs

portfolio selection in stochastic markets with hara utility functions in this paper we consider the optimal portfolio selection problem where the investor maximizes the expected utility of the terminal wealth the utility function belongs to the hara family which includes exponential logarithmic and power utility functions the main feature of the model is that returns of the risky assets and the utility function all depend on an external process that represents the stochastic market the states of the market describe the prevailing economic financial social political and other conditions that affect the deterministic and probabilistic parameters of the model we suppose that the random changes in the market states are depicted by a markov chain dynamic programming is used to obtain an explicit characterization of the optimal policy in particular it is shown that optimal portfolios satisfy the separation property and the composition of the risky portfolio does not depend on the wealth of the investor we also provide an explicit construction of the optimal wealth process and use it to determine various quantities of interest the return risk frontiers of the terminal wealth are shown to have linear forms special cases are discussed together with numerical illustrations

a partially observed markov decision process for dynamic pricing in this paper we develop a stylized partially observed markov decision process pomdp framework to study a dynamic pricing problem faced by sellers of fashion like goods we consider a retailer that plans to sell a given stock of items during a finite sales season the objective of the retailer is to dynamically price the product in a way that maximizes expected revenues our model brings together various types of uncertainties about the demand some of which are resolvable through sales observations we develop a rigorous upper bound for the seller s optimal dynamic decision problem and use it to propose an active learning heuristic pricing policy we conduct a numerical study to test the performance of four different heuristic dynamic pricing policies in order to gain insight into several important managerial questions that arise in the context of revenue management

adaptive inventory control for nonstationary demand and partial information this paper examines several different policies for an inventory control problem in which the demand process is nonstationary and partially observed the probability distribution for the demand in each period is determined by the state of a markov chain the core process however the state of this core process is not directly observed only the actual demand is observed by the decision maker given this demand process the inventory control problem is a composite state partially observed markov decision process pomdp which is an appropriate model for a number of dynamic demand problems in practice managers often use certainty equivalent control cec policies to solve such a problem however this paper presents results that demonstrate that there are other practical control policies that almost always provide much better solutions for this problem than the cec policies commonly used in practice the computational results also indicate how specific problem characteristics influence the performance of each of the alternative policies

inventory management with random supply and imperfect information a hidden markov model in most of the papers on inventory models operating in a random environment the state of the environment in each period is assumed to be fully observed with perfect information however this assumption is not realistic in most real life situations and we provide a remedy in this paper by assuming that the environment is only partially observed with imperfect information we accomplish this by analyzing two formulations of single item models with periodic review and random supply in a random environment in the first one supply is random due to random capacity of production and random availability of transportation we show that state dependent base stock policy is optimal if the capacity and all costs are observed while demand and availability are unobserved in the second model we consider a model with random availability only with fixed ordering cost we show that state dependent s s policy is optimal if the availability process is observable