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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...