Applying forecasting methods to accrual-based and cash-based ratio analysis

Research Questions: Which of the forecasting methods (SMA, ARIMA, ES) is the most informative?Can forecasting methods be used to verify each other's results?How do the manipulations in historical data affect the forecasting of accrual and cash ratios?Motivation: addressing the challenge of analytical precision in financial forecasting, the research proposes and empirically investigates the financial forecasting approach based on integrated cash-based and accrual-based ratio analysis in the dimensions of solvency, liquidity, efficiency and profitability. Idea:The effectiveness of the forecasting methods based on ratio analysis is evaluated by determining the most informative approach while examining how data manipulations influence forecasting outcomes.Data: Historical panel data for seven years (2015-2022) from financial statements of two production companies listed on the Baltic Stock Exchange was taken as a base for equallyweighted ratio calculations: solvency, liquidity, efficiency and profitability.Based on the ratio results, the forecasting for three years was done.Tools: Quantitative forecasting methods included Simple Moving Average method implemented in Excel, and ARIMA and Exponential Smoothing done via R-Script.Findings: Exponential Smoothing is the most informative method of forecasting for three years due to its sensitivity to data fluctuations, particularly in cash-based ratios.The forecasts