Estimate of Bankruptcy Probability through Crude Monte Carlo Simulation

This study presents a sophisticated approach to quantifying the likelihood of corporate bankruptcy through Crude Monte Carlo Simulation. By employing a probabilistic model, we generate a vast ensemble of a firm's financial trajectories based on stochastic processes that reflect the volatility of key financial indicators. The simulation incorporates random perturbations to cash flow, debt obligations, and asset valuations, mirroring real-world market fluctuations. Through iterative computation, we extrapolate the frequency of insolvency occurrences, yielding an empirical bankruptcy probability. The model's robustness is reinforced by incorporating systemic risk factors and recovery rates, ensuring a comprehensive risk assessment. The findings underscore the significance of scenario-based analysis in financial risk management, providing valuable insights for investors and creditors alike. This methodological framework not only enhances predictive accuracy but also offers a scalable tool for risk evaluation amidst the complexity of economic uncertainties.