Financial Forecast Report
I conducted a forecasting analysis of Meta Platforms Inc. with the goal of identifying the most accurate method to project its quarterly revenue for the coming year, based on historical data from the past 16 quarters. I applied several forecasting techniques like moving average, exponential smoothing, and trend-adjusted models. Using Excel and real financial data sourced from Meta’s SEC filings to build and test these models. By evaluating forecast accuracy using error metrics such as MAD and MSE, I found that the trend-adjusted exponential smoothing model is the most effective. This project improved my data analysis abilities and deepened my expertise in financial modeling using Excel.