List and describe the four key steps in financial forecasting

Financial forecasting

Some of the purposes of the financial forecast are its ability to highlight and evaluate the existing and upcoming financial status that guides procedure and systematic decisions. An economic outlook is regarded to be a financial management technique that is applied as a representation of the projected data centered on the precedent, present and estimated economic status. It will assist in identifying the prospected returns and spending processes that are likely to have an instant or a prolonged effect on the State’s policies, planned goals, and societal services.

Step One: Define Assumptions

This is the foremost stage in financial forecasting where there is need to identify the critical problems affecting the forecast (Bagheri, Peyhani, & Akbari, 2014). The response of this primary process will present a highlight into which forecasting techniques are the most suitable and will be of assistance in creating a mutual consideration among the individuals forecasting as to the objectives of the entire financial procedure.

Step Two: Collect Data

About supporting the forecasting procedure, there is the need to apply the mathematical information as well as the gathered verdict and techniques of people within and maybe outside the institution. The process is intended to boost the forecasters professional know how on the factors affecting the taxes and expenditures (Daníelsson, 2011). It would also involve events that are likely to disrupt the operating surroundings and existing processes.

Step Three: Exploratory Analysis

This study should comprise of an evaluation of past information and relevant economic status (Soofi & Cao, 2012). Also, the analysis process enhances the nature of the forecast process through initiating the forecast a better insight into when and what quantitative procedures might be suitable and even is essential in supplementing forecasting process.

Step Four: Select Methods

In this stage, it is vital for the forecaster to determine the qualitative and quantitative forecasting techniques that would be used, and always have to know that the picked methods for a particular program may vary from another. While complex ways may get more accurate feedbacks in a given case, more straightforward methods also execute just as well or improve on average.




Bagheri, A., Peyhani, H. M., & Akbari, M. (2014). Financial forecasting using ANFIS networks with quantum-behaved particle swarm optimization. Expert Systems with Applications, 41(14), 6235-6250.

Daníelsson, J. (2011). Financial risk forecasting: the theory and practice of forecasting market risk with implementation in R and Matlab (Vol. 588). John Wiley & Sons.

Soofi, A. S., & Cao, L. (Eds.). (2012). Modelling and forecasting financial data: techniques of nonlinear dynamics (Vol. 2). Springer Science & Business Media.

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