calculating order up to levels for products with intermittent demand abstract the croston 1972 forecasting and stock control for intermittent demands operational research quarterly 23 289 303 method is the standard method for forecasting intermittent demand it has been shown to perform well in various studies and is available in most commercial forecasting packages however little attention has been paid to linking the method with inventory control i e using the generated forecasts to calculate the inventory control parameters in this study we consider the most commonly applied order up to policy and show how the forecasts can be used to calculate order up to levels in a numerical study we show that the calculated order up to levels lead to service levels that are close to their targets

estimating the lead time demand distribution when the daily demand is non normal and autocorrelated hon shiang lau abstract this paper develops convenient formulas for estimating the probability distribution of lead time demand when the inventory item s daily demand follows a probability distribution of any arbitrary shape and when simple univariate models can be found for the autocorrelated daily demand series numerical examples are presented to illustrate the use of these formulas the numerical results also indicate that significant error may be incurred when inventory decisions are made without proper consideration of the autocorrelations or the arbitrary distribution shapes of daily demands

intergenerational class mobility in postwar japan this article uses mobility data from japan to 1 test the feather man jones hauser hypothesis that industrial societies share similar rats of intergenerational mobility and to 2 shed light on the debate about japanese exceptionalism japanese relative mibility rates show no systematically greater deviation from the postulated common pattern than do those of nine european nations regarding absolute mobility rates however an argument can be made for the distinctiveness of mobility patterns and processes of class formation and reproduction in japan

how much demand should be fulfilled we study the inventory replenishment of a product whose demand can be manipulated by restricting the supply this research is motivated by a novel marketing tactic employed by manufacturers of fashion and luxury items such a tactic combines innovative marketing with deliberate understocking in an attempt to create shortages i e waitlists that add to the allure and sense of exclusivity of a product and stimulate its demand we model the problem as a finite horizon periodic review system where demand in each period is a decreasing function of the net ending inventory in the previous period although the optimal structure can be complex in general under certain conditions we are able to characterize the optimal policy as a state dependent monotone base stock policy we compare this policy with the optimal policy for the case in which demand is independent of the net inventory we also show that understocking is optimal in various scenarios we then propose a novel strategy called the inventory withholding strategy to further explore the wait list effect by making customers wait even when there is inventory on hand to satisfy them our numerical experiments study the impact of various model parameters in combination with the wait list effect on the optimal policy and the corresponding expected profits

interest rate volatility and the term structure a two factor general equilibrium model we develop a two factor general equilibrium model of the term structure the factors are the short term interest rate and the volatility of the short term interest rate we derive closed form expressions for discount bonds and study the properties of the term structure implied by the model the dependence of yields on volatility allows the model to capture many observed properties of the term structure we also derive closed form expressions for discount bond options we use hansen s generalized method of moments framework to test the cross sectional restrictions imposed by the model the tests support the two factor model there are essentially two approaches to the modeling of the term structure of interest rates in continuous time the equilibrium approach pioneered by

multivariate term structure models with level and heteroskedasticity effects abstract the paper introduces and estimates a multivariate level garch model for the long rate and the term structure spread where the conditional volatility is proportional to the th power of the variable itself level effects and the conditional covariance matrix evolves according to a multivariate garch process heteroskedasticity effects the long rate variance exhibits heteroskedasticity effects and level effects in accordance with the square root model the spread variance exhibits heteroskedasticity effects but no level effects the level garch model is preferred above the garch model and the level model garch effects are more important than level effects the results are robust to the maturity of the interest rates

market transition industrialization and social mobility trends in postrevolution china1 this study examines trends in intergenerational class mobility in china by analyzing six comparable nationally representative surveys between 1996 and 2012 defying a simplistic unidirectional ac

on the interaction between forecasting and stock control the case of non stationary demand the effect of using estimated forecast demand parameters on the performance of an inventory control system is an intriguing and important subject recent research has been undertaken on this phenomenon assuming stationary demand data in this paper we extend the research to non stationary demands by means of simulation the case of a periodic order up to level inventory system is considered and the experimental structure allows us to evaluate in a progressive manner the accumulated effect of using the optimal forecasting method optimal forecast parameters and correct variance expression procedures the results allow insights to be gained into operational issues and demonstrate the scope for improving stock control systems

optimal policies and approximations for a serial multiechelon inventory system with time correlated demand since clark and scarf s pioneering work most advances in multiechelon inventory systems have been based on demand processes that are time independent this paper revisits the serial multiechelon inventory system of clark and scarf and develops three key results first we provide a simple lower bound approximation to the optimal echelon inventory levels and an upper bound to the total system cost for the basic model of clark and scarf second we show that the structure of the optimal stocking policy of clark and scarf holds under time correlated demand processes using a martingale model of forecast evolution third we extend the approximation to the time correlated demand process and study in particular for an autoregressive demand model the impact of lead times and autocorrelation on the performance of the serial inventory system

coordinated replenishments in inventory systems with correlated demands abstract demand correlation among different inventory items is common in real life multi item inventory systems however this phenomenon has not received sufficient attention in the existing inventory literature in this paper we construct a markovian model for a two item inventory system with correlated demands and coordinated replenishments we obtain an expression for the long run total cost per unit of time under the can order replenishment policy for the scenario with independent replenishments the explicit formula for the long run total cost per time unit can be derived which leads to analytical solutions for the optimal policies we then present numerical examples of the optimal can order policies and discuss some managerial insights regarding demand correlation and replenishment coordination our numerical results also suggest a possible heuristic method for obtaining can order replenishment policies for multi item systems

comparative social mobility revisited models of convergence and divergence in 16 countries this paper reanalyzes 3 stratum intergenerational mobility classifications assembled by hazelrigg and garnier for men in 16 countries in the 1960s and 1970s log linear and log multiplicative models are used to compare mobility regimes and to estimate effects of industrialization educational enrollment social democracy and income inequality on immobility and other parameters of the mobility process several models of mobility fit the data equally well so criteria of plausibility and parsimony are applied to choose one model of stratum specific immobility and another model of vertical mobility with uniform immobility we find substantial similarity in mobility and immobility across countries but the exogenous variables do explain systematic differences among countries cross national variations are complex because most of the exogenous variables have different effects on different parameters of the mobility regime relative to other factors industrialization and education have weaker effects on mobility regimes than has usually been supposed

a robustness study of a multi echelon inventory model via simulation abstract this paper examines the robustness of a standard model of multi echelon inventory systems specifically the models discussed in axsater oper res 48 5 2000 686 a simulation model was developed to explore the model s ability to predict system performance for a two echelon one warehouse multiple retailer system using r q inventory policies under conditions that violate the model s fundamental modeling assumptions in particular the impact of non stationary demand on this stationary demand inventory model was examined the model performs well at the low demand and large retailer order batch size situations but our testing of the model indicated that care must be taken when applying this model to situations that violate its fundamental assumption these results should help practitioners to better understand the assumptions of these models and to determine when or when not to apply these models in practice

further analysis of the expectations hypothesis using very short term rates abstract longstaff longstaff f 2000 the term structure of very short term rates new evidence for the expectations hypothesis journal of financial economics 58 397 415 finds support for the expectations hypothesis at the very short end of the repurchase agreement repo term structure while other studies find calendar time based regularities cause rejection of the expectations hypothesis using longstaff s methods on a sample of repo rates that pre dates longstaff s sample we reject the expectations hypothesis for every maturity the pre longstaff sample repo data comes from a time period where the behavior of short term interest rates is similar to the long run average behavior of short term interest rates our results imply that expectations hold when rates are less volatile and or that we may be entering a period of lower volatility

short term interest rates as subordinated diffusions in this article we cbaracterize and estimate the process for short term interest rates using federal funds interest rate data we presume that we are observing a discrete time sample of a stationary scalar diffusion we concentrate on a class of models in whicb the local volatility elasticity is constant and the drift has aflexible specufication to accommodate missing observations and to break the link between economic time and calendar time we model the sampling scheme as an increasing process that is not directly observed we propose and implement two new methods for estimation we find evidence for a volatility elasticity between one and onehalf and two when interest rates are high local mean reversion is smaul and the mechanism for inducing stationarity is the increased volatility of the diffusion process

a periodic review model with serially correlated inventory level dependent demand abstract it has been established that the demand rates of many consumer products are serially correlated and are dependent on the amount of inventory displayed to the customer a periodic review model is developed that considers both of these effects an adaptive base stock policy based on the critical fractile is presented and a solution methodology is developed the effect of this demand pattern on the safety stock requirement is investigated

forecasting and stock control a study in a wholesaling context wholesalers add value to the products they deal with by essentially bringing them closer to the end consumers in that respect the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels in this paper we address issues pertinent to forecasting and inventory management in a wholesaling environment and discuss the recommendations proposed in such a context in a case study organization our findings demonstrate the considerable scope that exists for improving current practices and offers insights into possible managerial issues

gaussian estimation of single factor continuous time models of the term structure of interest rates this article presents the first application in finance of recently developed methods for the gaussian estimation of continuous time dynamic models a range of one factor continuous time models of the short term interest rate are estimated using a discrete time model and compared to a recent discrete approximation used by chan karolyi longstaff and sanders 1992a hereafter ckls whereas the volatility of short term rates is highly sensitive to the level of rates in the united states it is not in the united kingdom the econometric estimation of continuous time models of the short term interest rate has been a relatively recent development in empirical finance see for example brown and dybvig 1986 melino and turnbull 1986 barone cuoco and zautzik 1991 babbs 1992 abken 1993 chen and scott 1993 das 1993 gibbons and ramaswamy 1993 pearson and sun 1994 lund 1994 pfann schotman and tschernig 1995 ait sahalia 1995 and broze scaillet and zakoian 1995 1 in an important study chan karolyi longstaff and sanders 1992a hereafter ckls develop a general framework to estimate and compare a range of different single factor term structure models for the short term interest rate their major conclusion is that term structure models with volatilities more highly sensitive to the level of interest rates than more generally used models have a closer empirical fit to the data in addition the functional form of the drift with or without mean reversion is of secondary importance to the correct specification of the conditional heteroskedasticity in ckls the continuous time models of the term structure are estimated using a discrete approximation we present in this article an alternative

analysis of a forecasting production inventory system with stationary demand we consider a production stage that produces a single item in a make to stock manner demand for finished goods is stationary in each time period an updated vector of demand forecasts over the forecast horizon becomes available for use in production decisions we model the sequence of forecast update vectors using the martingale model of forecast evolution developed by graves et al 1986 1998 and heath and jackson 1994 the production stage is modeled as a single server discrete time continuous state queue we focus on a modified base stock policy incorporating forecast information and use an approximate analysis rooted in heavy traffic theory and random walk theory to obtain a closed form expression for the forecast corrected base stock level that minimizes the expected steady state inventory holding and backorder costs this expression which is shown to be accurate under certain conditions in a simulation study sheds some light on the interrelationships among safety stock stochastic correlated demand inaccurate forecasts and random and capacitated production in forecasting production inventory systems

testing the empirical performance of stochastic volatility models of the short term interest rate i introduce two factor discrete time stochastic volatility models of the short term interest rate to compare the relative performance of existing and alternative empiricial specificattions i develop a nonlinear asymmmetric framework that allows for comparisons of non nested models featuring conditional heteoskedasticity and sensitivity of the volatility process to interest rate levels a new class of stochastic volatility models with asymmetric garch models the existing models are rejected in favor of the newly proposed models because of the asymmetric drift of the short rate and the presence of nonlinearity asymmetry garch and level effects in its volatility i test the predictive power of nested and non nested models in capturing the stochastic behavior of the risk free rate empirical evidence on three six and 12 month u s treasury bills indicates but that two factor stochastic volatility models are better than diffusion and garch models in forecasting the future level and volatility of interest rate changes

scarf s state reduction method flexibility and a dependent demand inventory model we consider a finite horizon inventory model with linear holding shortage and ordering costs the demand random variables are dependent and average demand is described by an exponential smoothing formula this model can be formulated as a two state variable inventory level weighted past demands dynamic program using a procedure first developed by scarf for a bayesian inventory model we are able to reformulate the model as a one state variable dynamic program resulting in a considerable computational saving over the two state variable formulation we also show that this dependent demand model orders less than or equal the amount ordered by a comparable independent demand model we establish this result under the assumption that demand represents failures that are repaired by the beginning of the next period

quadratic arch models we introduce a new model for time varying conditional variances as the most general quadratic version possible within the arch class hence it encompasses all the existing restricted quadratic variance functions its properties are very similar to those of garch models but avoids some of their criticisms in univariate applications to daily u s and monthly u k stock market returns qarch adequately represents volatility and risk premia qarch is easy to incorporate in multivariate models to capture dynamic asymmetries that garch rules out such asymmetries are found in an empirical application of a conditional factor model to 26 u k sectorial stock returns

the pricing of options on default free bonds recent developments in the finance literature dealing with the valuation of contingent claims have been triggered by black and scholes 2 with their valuation of european options on corporate stocks the type of valuation model derived by black and scholes is attractive because it is independent of preferences this independence is possible due to the fact that the contingent claims are usually assumed to be contingent on traded assets or traded state variables for example a european call option is a claim contingent on the value of the corresponding stock to maintain the independence of the claim from preferences however some variables have to be discarded and considered as constants for example the rate of interest which is not a traded state variable is considered a constant in most of the literature see black and scholes 2 merton 11 and ingersoll 9 though this approximation might not cause important discrepancies in the case of corporate liabilities and options on corporate liabilities the effect of such an approximation on the value of default free bonds and options on default free bonds is more important since these liabilities depend only on the rate of interest

exploiting the conditional density in estimating the term structure an application to the cox ingersoll and ross model we propose an empirical method that utilizes the conditional density of the state variables to estimate and test a term structure model with known price formulae using data on both discount and coupon bonds the method is applied to an extension of a two factor model due to cox ingersoll and ross 1985 cir our results show that estimates based on only bills imply unreasonably large price errors for longer maturities we reject the original cir model using a likelihood ratio test and conclude that the extended cir model also fails to provide a good description of the treasury market

hedging effectiveness of the hedged portfolio the expected utility maximization subject to the value at risk approach multivariate volatilities and distribution play an important role in portfolio selection and can be used to calculate the value at risk var of a multiple asset financial position this study proposes a new expected utility maximization eum model that accounts for var eum model with a var constraint eum var additionally using the eum var model this study investigates the hedging effectiveness of short and long hedged portfolios constructed with multivariate generalized autoregressive conditional heteroscedasticity garch type models that feature level effects and multivariate normal and skewed distributions for stock indexes and their corresponding futures in the greater china region it is found that all else equal portfolios constructed using the multivariate skewed distribution are far more effective in hedging than those that rely on the other distributions and the effectiveness of hedged portfolios from the multivariate garch type models with level effects outperform those without level

adapting wright s modification of holt s method to forecasting intermittent demand abstract the challenge of accurately forecasting demand for spare parts is due to the intermittent nature of their demand this study compares a recent modification of croston s method and a method based on holt s double exponential smoothing taking the firm s competitive priorities into consideration wright s modification of holt s method is presented as a viable alternative when forecasting demand for spares especially when trend is present results indicate that firms focusing on minimizing inventory levels as a priority should consider forecasting using the modified croston s method if their priority is high customer service then the modified holt s method is superior

on the bias of intermittent demand estimates forecasting and inventory control for intermittent demand items has been a major problem in the manufacturing and supply environment croston operational research quarterly 23 1972 289 proposed a method according to which intermittent demand estimates can be built from constituent events croston s method has been reported to be a robust method but has shown more modest benefits in forecasting accuracy than expected in this research one of the causes of this unexpected performance has been identified as a first step towards improving croston s method certain limitations are identified in croston s approach and a correction in his derivation of the expected estimate of demand per time period is presented in addition a modification to his method that gives approximately unbiased demand per period estimates is introduced all the conclusions are confirmed by means of an extended simulation experiment where croston s and revised croston s methods are compared the forecasting accuracy comparison corresponds to a situation of an inventory control system employing a re order interval or product group review

an improved method for forecasting spare parts demand using extreme value theory inventory control for spare parts is essential for many organizations due to the trade off between preventing high holding cost and stockouts the lead time demand distribution plays a central role in inventory control the estimation of this distribution is problematic as the spare part demand is often intermittent and as a consequence often only a limited number of non zero data points are available in practice the well known empirical method uses historical demand data to construct the lead time demand distribution although it performs reasonably well when service requirements are relatively low it has difficulties in achieving high target service levels in this paper we improve the empirical method by applying extreme value theory to model the tail of the lead time demand distribution to make the most out of a limited number of demand observations we establish that extreme value theory can be applied to lead time demand periods computed over overlapping intervals we consider two service levels the expected waiting time and cycle service level our experiments show that our method improves the inventory performance compared to the empirical method and is competitive with the wss method croston s method and sba for a range of demand distributions

interest rate risk and the forward premium anomaly in foreign exchange markets this paper shows that even adjusted for the time varying risk premiums implied by the yield curves across countries uncovered interest parity is still strongly rejected by the data moreover factors that predict the excess bond returns are found not significant at all in predicting the foreign exchange returns these results reject the joint restrictions on the exchange rate and interest rates imposed by dynamic term structure models suggesting that foreign exchange markets and bond markets may not be fully integrated and we have to look beyond interest rate risk in order to understand the exchange rate anomaly

an empirical comparison of forward rate and spot rate models for valuing interest rate options our main goal is to investigate the question of which interest rate options valuation models are better suited to support the management of interest rate risk we use the german market to test seven spot and forward rate models with one and two factors for interest rate warrants for the period from 1990 to 1993 we identify a one factor forward rate model and two spot rate models with two factors that are not significantly outperformed by any of the other four models further rankings are possible if additional criteria are applied

operations research in inventory management a review and critique the objectives of inventory management including the relevant related costs are examined in this paper a brief review of standard problems that have been effectively solved is presented however we point out that a serious gap exists between theory and practice in many organizations suggestions are made for bridging this gap finally a list is provided of a number of research problems whose implementable solution would have a major beneficial impact on the practice of inventory management

safety stock determination with correlated demands and arbitrary lead times abstract in this new paper a new method is proposed for determining the safety stock when daily demands are autocorrelated and lead times follow an arbitrary distribution the method is then used as a basis for examining effects on the safety stock when the usual assumptions namely independence and normality of daily demand and normality of lead times are violated the new method is derived by using inequalities on the basis of probability arguments it is simple to use and provides an upper bound of the safety stock further numerical investigation based on the new method shows that the effect of autocorrelation is more pronounced than departure from normality in determining the safety stock substantial error may be incurred if such autocorrelation is ignored in the test cases

coordinating lead times and safety stocks under autocorrelated demand we consider a supply chain in which orders and lead times are linked endogenously as opposed to assuming lead times are exogenous this assumption is relevant when a retailer s orders are produced by a supplier with finite capacity and replenished when the order is completed the retailer faces demands that are correlated over time either positively or negatively which may for example be induced by a pricing or promotion policy the auto correlation in demand affects the order stream placed by the retailer onto the supplier and this in turn influences the resulting lead times seen by the retailer since these lead times also determine the retailer s orders and its safety stocks which the retailer must set to cover lead time demand there is a mutual dependency between orders and lead times the inclusion of endogenous lead times and autocorrelated demand represents a better fit with real life situations however it poses some additional methodological issues compared to assuming exogenous lead times or stationary demand processes that are independent over time by means of a markov chain analysis and matrix analytic methods we develop a procedure to determine the distribution of lead times and inventories that takes into account the correlation between orders and lead times our analysis shows that negative autocorrelation in demand although more erratic improves both lead time and inventory performance relative to iid demand positive correlation makes matters worse than iid demand due to the endogeneity of lead times these effects are much more pronounced and substantial error may be incurred if this endogeneity is ignored

likelihood based specification analysis of continuous time models of the short term interest rate an extensive collection of continuous time models of the short term interest rate is evaluated over data sets that have appeared previously in the literature the analysis which uses the simulated maximum likelihood procedure proposed by durham and gallant 2002 provides new insights regarding several previously unresolved questions for single factor models i find that the volatility not the drift is the critical component in model specification allowing for additional flexibility beyond a constant term in the drift provides negligible benefit while constant drift would appear to imply that the short rate is nonstationary in fact stationarity is volatility induced the simple constant elasticity of volatility model fits weekly observations of the three month treasury bill rate remarkably well but is easily rejected when compared with more flexible volatility specifications over daily data the methodology of durham and gallant can also be used to estimate stochastic volatility models while adding the latent volatility component provides a large improvement in the likelihood for the physical process it does little to improve bond pricing performance

the accuracy of a modified croston procedure a modified croston procedure to forecast intermittent demand is reviewed the modified procedure published in this journal in 2004 consists of a new method for estimating the mean demand and a smoothing method for estimating the variance of the forecasted demand rate it is found that the smoothed variance estimate is based on an invalid measure of forecast accuracy moreover it is shown that the method of forecasting mean demand produces biased forecasts the accuracy of this method is assessed using simulated data and the mean square error measure and compared with croston s method and single exponential smoothing it is found that croston s method is generally more accurate than its modification particularly for strongly intermittent series

are levels effects important in out of sample performance of short rate models abstract this paper derives short term interest rate volatility forecasts from various interest rate models while models that specify both garch and levels effects are superior in their forecasts accuracy they systematically under predict interest rate volatility more frequently than simple short rate models

exploiting elapsed time for managing intermittent demand for spare parts we present an intermittent demand forecasting method that conditions on the elapsed time since the last demand occurrence to anticipate incoming demand and show using empirical data that this can substantially reduce both stock investment and lost revenue for spare parts management we extensively benchmark our method against existing forecasting and bootstrapping methods on forecast accuracy and inventory performance and demonstrate that its performance is robust under general conditions our method is the first to incorporate that activities at the demand side such as aggregation of demand preventive and corrective maintenance can lead to a positive relation between demand size and inter arrival time of demand occurrences by anticipating incoming demand our method offers substantial financial gains

unequal but fluid social mobility in chile in comparative perspective a major finding in comparative mobility research is the high similarity across countries and the lack of association between mobility and other national attributes with one exception higher inequality seems to be associated with lower mobility evidence for the mobility inequality link is however inconclusive largely because most mobility studies have been conducted in advanced countries with relatively similar levels of inequality this article introduces chile to the comparative project as the 10th most unequal country in the world chile is an adjudicative case if high inequality results in lower mobility chile should be significantly more rigid than its industrialized peers this hypothesis is disproved by the analysis despite vast economic inequality chile is as fluid if not more so than the much more equal industrialized nations furthermore there is no evidence of a decline in mobility as the result of the increase in inequality during the market oriented transformation of the country

the effects of integrating management judgement into intermittent demand forecasts empirical research suggests that quantitatively derived forecasts are very frequently judgementally adjusted nevertheless little work has been conducted to evaluate the performance of these judgemental adjustments in a practical demand sales context in addition the relevant analysis does not distinguish between slow and fast moving items currently there are neither conceptual developments nor empirical evidence on the issue of integrating judgements and statistical forecasts for slow intermittent demand items moreover no results have ever been reported on the stock control implications of these human judgements our work analyses monthly intermittent demand forecasts for the uk branch of a major international pharmaceutical company the company relies upon a commercially available statistical forecasting system to produce forecasts that are subsequently judgementally adjusted based on marketing intelligence gathered by the company forecasters the benefits of the intervention are evaluated by comparing the actual sales to system and final forecasts using both forecast accuracy and inventory control accuracy implication metrics our study allows insights to be gained on potential improvements to intermittent demand forecasting processes and subsequently the design effectiveness of forecasting support systems

optimal centralized ordering policies in multi echelon inventory systems with correlated demands this paper treats a depot warehouse system in which demand occurs at the warehouse or retail level this work differs from a number of other studies in that we allow item demands to be correlated both across warehouses and also correlated in time our motivation for this generalization arises from our experience with an actual system of this type used by a major national producer and distributor of consumer products we observed both high correlations between successive monthly demands around 0 7 and correlations between demands for an item at different locations also about 0 7 in a given time period we derive an explicit expression for the optimal safety stock as a function of the level of correlation through time the analysis requires two assumptions 1 the allocation assumption and 2 the equal coefficient of variation assumption similar assumptions have been used by other researchers finally numerical evaluations are included to illustrate the impact of the various magnitudes of correlation

yield factor volatility models the term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve in this paper we develop a comprehensive model for volatility dynamics in the level slope and curvature of the yield curve that simultaneously includes level and garch effects along with regime shifts we show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant garch effects present even after including a level effect further we find that allowing for regime shifts in the factor volatilities dramatically improves the model s fit and strengthens the level effect we also show that a regime switching model with level and garch effects provides the best out of sample forecasting performance of yield volatility we argue that the auxiliary models often used to estimate term structure models with simulation based estimation techniques should be consistent with the main features of the yield curve that are identified by our model

effects of correlation on intermittent demand forecasting and stock control abstract this study investigates the effects of three different types of correlation on forecasting and stock control of intermittent demand items applying appropriate forecasting and stock control methods to theoretically generated compound poisson demand data we show that correlation in intermittent demand does play a role in forecast quality and stock control performance negative autocorrelation levels lead to higher service levels than positive values while cost does not significantly change our results also show that high intermittency levels intensify these changes in service level we also show that cross correlation produces results in the opposite direction of autocorrelation in size or intervals that is positive negative cross correlation leads to higher lower service levels

another look at models of the short term interest rate the short term rate of interest is fundamental to much of theoretical and empirical finance yet no consensus has emerged on the dynamics of its volatility we show that models which parameterize volatility only as a function of interest rate levels tend to over emphasize the sensitivity of volatility to levels and fail to model adequately the serial correlation in condi tional variances on the other hand serial correlation based models like garch models fail to capture adequately the relationship between interest rate levels and volatility we introduce and test a new class of models for the dynamics of short term interest rate volatility which allows volatility to depend on both interest rate levels and information shocks two important conclusions emerge first the sensitivity of interest rate volatility to interest rate levels has been overstated in the literature while this relationship is important adequately modeling volatility as a function of unexpected information shocks is also important sec ond we conclude that the volatility processes in many existing theoretical models of interest rates are misspecified and suggest new paths toward improving the theory

on the empirical performance of t s s heuristics the periodic t s s policies have received considerable attention from the academic literature determination of the optimal parameters is computationally prohibitive and a number of heuristic procedures have been put forward however these heuristics have never been compared in an extensive empirical study such an investigation on 3055 skus is carried out in this paper our study provides insights into the performance of t s s heuristics also in relation to demand forecasting the results show that naddor s heuristic is best able to minimize the total cost however the normal and power approximations achieve more efficient solutions in that backorder volumes are smaller at the same inventory levels indicating the potentially superior performance of these methods if the balancing of holding and backorder costs can be improved the results also show that for all heuristics the sba variant of the croston forecasting method significantly outperforms croston as well as single exponential smoothing ses

modeling asymmetric comovements of asset returns existing time varying covariance models usually impose strong restrictions on how past shocks affect the forecasted covariance matrix in this article we compare the restrictions imposed by the four most popular multivariate garch models and introduce a set of robust conditional moment tests to detect misspecification we demonstrate that the choice of a multivariate volatility model can lead to substantially different conclusions in any application that involves forecasting dynamic covariance matrices like estimating the optimal hedge ratio or deriving the risk minimizing portfolio we therefore introduce a general model which nests these four models and their natural asymmetric extensions the new model is applied to study the dynamic relation between large and small firm returns article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies