Which of the following are common methods for financial forecasting?

Trend analysis and regression analysis are indeed common methods for financial forecasting because they rely on historical data to predict future financial outcomes.

Trend analysis involves examining historical financial data to identify patterns and trends that can provide insights into future performance. By analyzing past revenues, expenses, and other financial metrics, organizations can project future trends and make informed decisions based on that information.

Regression analysis complements this by quantifying relationships between variables. It allows financial professionals to model how different factors, such as sales volume or marketing spending, impact financial outcomes. By using statistical techniques, regression analysis can help forecast future revenues and other key financial metrics based on the values of independent variables.

Together, these methods provide a strong basis for developing realistic and data-driven financial forecasts, helping organizations plan strategically and allocate resources effectively.

The other options may include elements that are important in finance, but they do not specifically focus on common forecasting methods. For example, time management is essential for project execution, while capital budgeting is more about investment decision-making than forecasting. Similarly, market research and sales projections are valuable in understanding market dynamics but do not describe commonly recognized statistical methods for financial forecasting like trend and regression analyses do.