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Int. J. Production Economics 158 (2014) 65–76
Contents lists available at ScienceDirect
Int. J. Production Economics
journal homepage: www.elsevier.com/locate/ijpe
Stochastic financial analytics for cash flow forecasting
Rattachut Tangsucheeva, Vittaldas Prabhu n
The Pennsylvania State University, University Park, PA, USA
art ic l e i nf o
a b s t r a c t
Article history:
Received 16 February 2014
Accepted 18 July 2014
Available online 27 July 2014
Accurate cash flow forecasting is essential for successful management of firms and it becomes especially
critical during uncertain market and credit conditions. Without accurate cash flow forecasting, a firm
may fail to meet its short-term obligations and risk bankruptcy. Accurate cash flow forecasting can be
limited by a number of factors including changes in macro-economic conditions that influence liquidity
in the economy, customer payment behavior that can vary from time to time as well by industry, and
dynamics of the particular supply chain itself. We develop stochastic financial analytics for cash flow
forecasting for firms by integrating two models: (1) Markov chain model of the aggregate payment
behavior across all customers of the firm using accounts receivable aging and; (2) Bayesian model of
individual customer payment behavior at the individual invoice level. As the stochastic dynamics of cash
flow evolves every day, the forecast can be updated every time an invoice is paid. The proposed model is
back-tested using empirical data from a small manufacturing firm and found to differ 3–6% from actual
monthly cash flow, and differs approximately 2–4% compared to actual annual cash flow. The forecast
accuracy of the proposed stochastic financial analytics model is found to be considerably superior to
other techniques commonly used. Furthermore, in computer simulation experiments, the proposed
model is found to be largely robust to supply chain dynamics, including when subjected to severe...