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Corporate Cash Flow Shortfall Risk Analysis Based on Monte Carlo Simulation: Evidence from a Chinese Manufacturing Enterprise

Sep 2026 · Journal of Mathematical Finance and Risk Management · 0 citations · 13 references

Abstract

For Chinese companies, especially manufacturers, cash flow has become a critical issue in their survival, given that they rely heavily on short-term bank borrowing and extend generous trade credit to downstream customers. The traditional diagnostics that are based on ratios provide information about past liquidity, but not about the likelihood that future liquidity will be insufficient for a firm's operations. In this paper, a Monte Carlo simulation model for estimating corporate cash flow shortfall risk is developed. The variables that are subject to random variation are formulated as random variables: revenue growth, the ratio of receivables collected, the ratio of variable costs, the ratio of payments to suppliers, and fixed cash expenses. The path of the cash balance generated by these variables is then simulated for a one-year period, quarterly. The framework is applied to an anonymized medium-sized Chinese machinery manufacturer whose input distributions have been calibrated to published financial statements, and industry norms. Across 10,000 iterations, the chance of falling below the minimum operating cash floor within one year is 11.83 percent, most of it in the fourth quarter when a large loan repayment is due. At a 95 percent confidence level, cash flow at risk reaches 107.0 million RMB relative to the expected outcome. Sensitivity analysis identifies the collection ratio as the largest risk factor, while scenario tests show that deferring part of the year-end debt maturity, together with a two-point increase in the collection ratio, reduces the shortfall probability to less than 1 percent. Robustness tests on sampling error, alternative random seeds, heavier-tailed shocks and correlated inputs confirm the reliability of the estimates, and suggest that the assumed independence between demand and collections is the assumption to which the results are most sensitive. The study shows that the application of a set of shortfall metrics based on simulation is a viable complement to existing financial risk early warning indicators for Chinese enterprises with a clear forward-looking perspective.

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