Quantitative Analysis of Strategic Financial Planning in Corporate Management: A Study of Optimization Models, Risk Assessment Frameworks, and Decision-Support Tools

Strategic financial planning is more and more dependent upon data-driven decision support models in which profitability, risk analysis and capital allocation are integrated. This paper develops and uses a quantitative model based on fundamental analysis to discuss how firms can be systematically analyzed and selected for the deployment of capital for maximum returns. With a globally representative sample of 1,254 firms in 18 countries over the period 2013-2023, the analysis begins with the construction of simple financial ratios of return on assets (ROA), debt to equity and current ratio, which then are used in the measurement of profitability, leverage and liquidity. Risk is defined as a measure of volatility of earnings, which is defined as the standard deviation of the net income growth over time and it allows consistent and market-independent proxy for risk. Descriptive results indicate a right-skewed distribution of profitability, high dispersion of capital structures and the low correlation between liquidity and returns. It then utilizes a composite score heuristic optimization process to invest in companies with better risk-adjusted performance subject to leverage and liquidity constraints. The optimal portfolio is rewarded with a higher weighted-average ROA than the sample median while violating no risk constraint and essentially reallocates the portfolio to the empirical efficient frontier. The results stress the usefulness of transparent and reproducible heuristics to inform strategic financial planning and offer managerial insights that are relevant for balancing growth, profitability and stability in an uncertain environment.