The term 'Financial Forecasting' is included in the Corporate Finance edition of the Herold Financial Dictionary, which you can get from Amazon in Ebook or Paperback edition.
Financial Forecasting refers to the corporate or government fiscal management tool for delivering information based on estimates from past, present, and anticipated future financial conditions of a firm or national government finances. It is extremely useful in projecting future revenue streams or expenditures. These can create a longer term or short term impact on corporate or government goals, policies, spending, and other activities. Such forecasting proves to be an indispensable component in the yearly budgeting activities.
Financial Forecasting is also the implementation of historical data in order to prognosticate future financial directions and trends. Companies employ such means of forecasting so they can decide how best to allocate out their budgets in order to plan for expected expenses over a future time period. This prediction model will commonly be derived from the forecast for demand of the corporate services and goods they purvey.
Investors can also employ such forecasting techniques to their advantages. They may run scenarios to decide if corporate events, including sales or revenue expectations, will boost or lower the stock price in a given firm. It gives the companies themselves a crucial means of benchmarking, which requires a longer term perspective on company operations.
Stock market and economic analysts also utilize Financial Forecasting in order to extrapolate the way that economic trends like unemployment and GDP will alter in the future quarters or even years. The problem with this is that it is not a precise science ultimately. As a forecast is farther removed from the present, the chances for it to be inaccurate only grow with time.
Statisticians also use Financial Forecasting for those scenarios that need future predictions. Data on customer satisfaction and how it will shift when a business’ hours change can be gathered and measured using it. Similarly they can quantify and predict the impact of shifting working conditions on the company staff morale.
Stock analysts deploy a range of forecasting techniques in order to decide the ways that a given stock price will fluctuate over the future. They could begin by investigating a corporate revenue stream and contrasting this with national economic indicators for the country as a whole. They would have to measure any changes to statistical or financial data in order to ascertain the interconnecting relationship of numerous variables. Such relationships can be derived from particular events or the normal passing of time. Sales model forecasts could rely on a given event which is anticipated, such as buying the business of a competitor.
Financial Forecasting also takes on data sets or problems. Economists are able to engage in assumptions that pertain to a certain situation or simulation. They will select the most relevant data set to manipulate. After analyzing the information, they come up with their prognosis. Finally, there will be a reasonable verification time frame during which the analysts will compare their forecast to the real world results. They do this so that they can create still more accurate forecasting models for the future.
There are two types of specific Financial Forecasting techniques. The first particular kind is Qualitative forecasting models. Analysts utilize these to create prognoses that have a more limited scope. Such models will be greatly dependent on the opinions of experts. They benefit most heavily any short term forecasts. There are a number of examples of qualitative forecasting models available. Some of them are polls, market research, and survey which employ the Delphi method.
On the other hand, the alternative type of Financial Forecasting is quantitative forecasting. This means of forecasting will rule out expert opinions. It employs statistical data reliant on quantitative information. These quantitative forecasting models cover such series as discounting, methods, econometric modeling, and analysis of lagging and/or leading economic indicators.