DocumentCode :
850150
Title :
Dynamic optimization of cash flow management decisions: a stochastic model
Author :
Paté-cornell, M. Elisabeth ; Tagaras, George ; Eisenhardt, Kathleen M.
Author_Institution :
Dept. of Ind. Eng. & Eng. Manage., Stanford Univ., CA, USA
Volume :
37
Issue :
3
fYear :
1990
fDate :
8/1/1990 12:00:00 AM
Firstpage :
203
Lastpage :
212
Abstract :
A stochastic method is proposed that is based on decision analysis and Bayesian updating to monitor cash flow and make short-term decisions when a liquidity squeeze appears possible. The uncertainties about the payment time of outstanding bills sent out to customers, and the updating of this information as the manager gets to know his customers through successive payments, is modeled. This updating is done through the use of conjugate probability distributions that allow closed-form analytical computation of the probability density functions for the payment of each client given past experience. The use of exponential utility functions allows simple computation of the benefits of this cash-flow monitoring system. This formulation is adapted to the case of small and new business with a small number of customers whose buying and paying schedules are critical for the firm. It can be particularly useful for new high-technology ventures as part of their strategy to manage short-term financial risk. An illustrative example is used to assess the benefits of such a monitoring system
Keywords :
economics; management; Bayesian updating; cash flow management; conjugate probability distributions; decision analysis; exponential utility functions; outstanding bills; payment time; short-term financial risk; stochastic model; Bayesian methods; Distributed computing; Financial management; Information management; Monitoring; Probability density function; Probability distribution; Processor scheduling; Stochastic processes; Uncertainty;
fLanguage :
English
Journal_Title :
Engineering Management, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9391
Type :
jour
DOI :
10.1109/17.104290
Filename :
104290
Link To Document :
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