Assessing Budget Risk with Monte Carlo and Time Series Bootstrap

Budgets are important management tools recognized for their help in planning, communication, monitoring the expense performance, and even motivating collaborators. However, recently there has been criticism of traditional Budgeting Process due to its cumbersomeness, long duration, eventual diversion focus from day-to-day activities. Thus, improving by incorporating Expense component uncertainties is uttermost importance accelerate approval. This paper presents a methodology companies assess budget risk based on historical data applying Monte Carlo Simulation Time Series Bootstrapping Techniques. Besides, some state-of-the-art sensitivity Importance Measures also implemented evaluate relative components. The proposed, real case study with major Portuguese retailer, advantage being objective supported data, thus not subject bias management.