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• MONTE CARLO SIMULATION FOR STRESS TESTING ENDOGENOUS PROFITABILITY FACTORS DURING POLYCRISIS: A CASE STUDY FROM THE POULTRY SUBSECTOR

  Máté Varga

  Patrícia Becsky-Nagy

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  Can historical company data help estimate future performance during economic uncertainty? This study investigates whether past business cycles can be used to estimate profitability in the context of a polycrisis – a period marked by overlapping disruptions such as avian influenza, COVID-19 trade restrictions, extreme weather events, and rising feed and energy prices. These shocks have severely impacted agro-related industries, such as poultry processing. Focusing on three Central European poultry processing companies, we use Monte Carlo simulations for stress testing their profitability for the 2023 period, aiming to support financial planning by analysing firm-specific, endogenous, management-controllable factors. Return on Sales (ROS) and Return on Equity (ROE) are used to evaluate profitability, incorporating variables such as euro exchange rates in the case of export-driven firms. Our results indicate that Company “A,” characterized by stable operations, had the lowest probability of negative ROE, while Companies “B” and “C” demonstrated greater volatility. We found that the model provides a good estimate of the factors affecting the companies’ profitability that are directly or indirectly reflected in their accounting data. Indicating that the test could be a valuable tool for supporting managerial decision-making in financial planning, though further refinements are needed to enhance accuracy.