The capital cost of holding inventory  A real options approach
(2002) Abstract
 This thesis is based on three scientific papers dealing with costs and financial risks associated with keeping stock. Reasonable cost parameters are important to implement an effective inventory control system, which in turn is one of the key activities in logistics management.
All three papers consider a singlelevel inventory system. Singleperiod, multiperiod as well as continuous review systems are investigated. The models are analyzed in a real options framework. Stochastic demand is treated in Paper A and C, stochastic purchase price per unit in Papers A and B and stochastic setup cost in Appendix 4. The parameters are varied one at a time and they are assumed to follow stochastic processes normally used in financial... (More)  This thesis is based on three scientific papers dealing with costs and financial risks associated with keeping stock. Reasonable cost parameters are important to implement an effective inventory control system, which in turn is one of the key activities in logistics management.
All three papers consider a singlelevel inventory system. Singleperiod, multiperiod as well as continuous review systems are investigated. The models are analyzed in a real options framework. Stochastic demand is treated in Paper A and C, stochastic purchase price per unit in Papers A and B and stochastic setup cost in Appendix 4. The parameters are varied one at a time and they are assumed to follow stochastic processes normally used in financial literature. Both the lognormal Wiener process and the OrnsteinUhlenbeck process are used.
The optimal policy is derived through a backwardpass dynamic programming approach. The expected net present value of the inventory costs associated with the optimal policy is then used to evaluate the cost efficiency of policies based on simple adjustments of wellknown heuristics, such as the EOQformula.
The thesis shows that the financial risk associated with a stochastic setup cost typically can be neglected when the inventory control parameters are determined. This holds for stochastic demand, too, although a minor improvement could be achieved by a simple adjustment of the order point. It is also shown that autocorrelated demand has very little effect on the optimal inventory policy.
The systematic risk of the unit purchase price has a significant effect on the optimal inventory control parameters. It is shown that an excellent approximation is attained if the expected rate of relative decrease in risk adjusted purchase price, i.e., the risk premium, is added to the capital cost rate. The results show that if this rate varies over time, a good policy is to use the average price change over a period of about 1/3 to 2/3 of the order cycle when estimating the risk premium.
It can be concluded that one can obtain a close to optimal inventory control system by using wellknown heuristics with just minor adjustments of the capital holding cost. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1038420
 author
 Berling, Peter ^{LU}
 supervisor

 Kaj Rosling ^{LU}
 organization
 publishing date
 2002
 type
 Thesis
 publication status
 published
 subject
 publisher
 Lund University
 ISBN
 9163119544
 language
 English
 LU publication?
 yes
 id
 8363b73d508f43de8960af0ee5d4f052 (old id 1038420)
 date added to LUP
 20160404 11:59:09
 date last changed
 20181121 21:08:22
@misc{8363b73d508f43de8960af0ee5d4f052, abstract = {{This thesis is based on three scientific papers dealing with costs and financial risks associated with keeping stock. Reasonable cost parameters are important to implement an effective inventory control system, which in turn is one of the key activities in logistics management.<br/><br> All three papers consider a singlelevel inventory system. Singleperiod, multiperiod as well as continuous review systems are investigated. The models are analyzed in a real options framework. Stochastic demand is treated in Paper A and C, stochastic purchase price per unit in Papers A and B and stochastic setup cost in Appendix 4. The parameters are varied one at a time and they are assumed to follow stochastic processes normally used in financial literature. Both the lognormal Wiener process and the OrnsteinUhlenbeck process are used.<br/><br> The optimal policy is derived through a backwardpass dynamic programming approach. The expected net present value of the inventory costs associated with the optimal policy is then used to evaluate the cost efficiency of policies based on simple adjustments of wellknown heuristics, such as the EOQformula.<br/><br> The thesis shows that the financial risk associated with a stochastic setup cost typically can be neglected when the inventory control parameters are determined. This holds for stochastic demand, too, although a minor improvement could be achieved by a simple adjustment of the order point. It is also shown that autocorrelated demand has very little effect on the optimal inventory policy.<br/><br> The systematic risk of the unit purchase price has a significant effect on the optimal inventory control parameters. It is shown that an excellent approximation is attained if the expected rate of relative decrease in risk adjusted purchase price, i.e., the risk premium, is added to the capital cost rate. The results show that if this rate varies over time, a good policy is to use the average price change over a period of about 1/3 to 2/3 of the order cycle when estimating the risk premium.<br/><br> It can be concluded that one can obtain a close to optimal inventory control system by using wellknown heuristics with just minor adjustments of the capital holding cost.}}, author = {{Berling, Peter}}, isbn = {{9163119544}}, language = {{eng}}, note = {{Licentiate Thesis}}, publisher = {{Lund University}}, title = {{The capital cost of holding inventory  A real options approach}}, year = {{2002}}, }