What is referred to by the term "Mixed forecasting"?

Mixed forecasting refers to using multiple forecasting methods to improve the accuracy and reliability of predictions. This approach takes advantage of the strengths of different forecasting techniques, enabling analysts to capture a broader range of potential outcomes and minimize the weaknesses of any single method. By combining various methods, such as qualitative assessments, quantitative analyses, or time-series models, forecasters can arrive at a more nuanced and robust prediction.

The rationale behind mixed forecasting is that different methods might yield different insights based on the nature of the data or market conditions. By synthesizing these insights, organizations can make better-informed decisions regarding future trends, which is critical in areas such as financial forecasting and economic analysis. This flexibility allows for adjustments based on changing scenarios and emerging information, thereby increasing the predictive power of the forecasts.