Consensus Methods of Financial Forecasting - Research Paper Example

Consensus Methods of Financial Forecasting Abstract This paper discusses the various methods used for financial forecasting, including regression analysis. Financial forecasting is extensively used to support business decisions and financial operations. There are 2 main types of financial forecasting; qualitative and quantitative forecasting. There exist multiple models and methods within both of these types of forecasting. Qualitative forecasts are more often based on data which is subjective, while quantitative forecasting is derived from objective data. Each of these methods is suitable for unique situations or circumstances, and they both have inherent weaknesses and strengths. It is thus imperative for a forecaster to understand the strengths and shortcomings of different forecasting types in order to choose appropriately. Introduction Financial forecasting has been defined as “a forecast of the expected financial position and the results of operations and cash flows based on expected conditions” (Brealey, R.A., Marcus, S.C. and Myers, A.J. 1991). Most people believe that the financial world consists of a vast range of alternatives. Financial forecasting has evolved as a way through which financial alternatives can be examined in order to identify the most viable alternative. Financial forecasting can be viewed as making estimates of the most probable financial positions, or the most probable operational results, or estimating the changes in financial position for relevant future periods. Financial forecasting is designed to aid the forecaster in making decisions and planning for future occurrences in the present. According to Heizer and Render, “Financial forecasting is based on management’s judgment of the most likely set of conditions and most likely course of action. A forecast is usually classified by the future time horizon that it covers. Time horizons fall into three different categories: short-range forecast, medium-range forecast, and long-range forecast. Short-range forecast is from three months to one year. It is used for planning purchasing, job assignments, job scheduling, workforce levels, and production levels. Medium-range forecast ranges from three months to three years. It is used for planning, budgeting and production planning, cash budgeting, and analysis of various operating plans. Long-range forecast is generally three or more years in time. It is used in planning new products, capital expenditures, facility location or expansion, and research and development.” (Heizer, J and Barry Render 2004) It is thus usual for operations managers to allocate personnel, time, and resources in order to meet the forecasting demands. Successful organizations achieve the desired results by proper allocation of resources, but although such allocation and forecasting is widely used, there exist multiple proven forecasting models. This paper will also examine, compare, and contrast the two most commonly used methods of qualitative and quantitative forecasting, and as a case study, examine the forecasting techniques used by the United States Marine Corps to forecast the ammunition requirements for each fiscal year. Literature review There are numerous instances in which people have been remarkable successful at forecasting future trends. There are also a lot of instances in which financial forecasts have proved to be wrong. One weakness inherent in genius forecasting is the impossibility of recognizing good predictions and forecasts until the relevant events have already come to pass. According to Makridakis and Wheelwright (1989), “the forecasting of future events is usually characterized as the search for solutions to one or more of the following questions: 1. What new economic, technical, or sociological forces is the organization likely to face in both the near and long term? 2. How much change should the firm anticipate both in the short run and the long run? 3. Who is likely to be first to adapt to each competitive challenge? 4. When might these forces impact the firm’s objective environment?” (Makridakis, S. and Wheelwright, S.C.1989) During corporate financial forecasting, “Expenses often excluded from pro forma results include company restructuring costs and a decline in the value of the company's investments.” (Brealey, R.A., Marcus, S.C. and Myers, A.J.1991) A major reason why organizations need to be involved in financial forecast is that such an organization might have the expansion of their business in mind, or the company may need a business loan. Thus, financial forecasting is required for various developmental plans, payments or purchases. The information gathered from the forecast can also be used to help the organization to understand their spending capabilities. For instance, when an organization intends to hire new employees, or buy some new equipments or items necessary for successful operation, there should be proper financial forecasting carried out. Most times, banks will require a company to do come form of financial forecast in order to ensure that such a company does possess the ability to pay back any loans that the bank grants them. “If a financial forecast is prepared properly, it can assist the company with information on the company’s liabilities, assets and profits. This will allow investors and buyers to see what potential the company will have in later dates. Normalization is a process for evaluating and correcting table structures to minimize data redundancies, thereby helping to eliminate data anomalies” (Coronel, Rob, 2004, p.184). There are several assumptions about financial forecasting: “1. There is no way to state what the future will be with complete certainty. Regardless of the methods that we use there will always be an element of uncertainty until the forecast horizon has come to pass. 2. There will always be blind spots in forecasts. We cannot, for example, forecast completely new technologies for which there are no existing paradigms. 3. Providing forecasts to policy-makers will help them formulate social policy. The new social policy, in turn, will affect the future, thus changing the accuracy of the forecast.” (Makridakis, S. and Wheelwright, S.C. 1989) There also exists a method of forecasting known as Genius forecasting, which is based on a combination of insight, intuition and sheer luck. Qualitative and Quantitative forecasting Techniques The main aim of Forecasting is to help people to make better decisions. Forecasting is extremely difficult, as one must pull information from all relevant sources. Qualitative forecasts tend to be less scientific and are “based exclusively upon subjective data, such as opinions and estimates” (Aquilano, Chase & Jacobs, 2005). Within the realm of qualitative forecasting are multiple techniques and measures, including market research, historical analogy, panel consensus, grass roots, and also the Delphi method. “Financial modeling can use economic or corporate financial models to estimate sales or other financial forecasts. Decision trees, game theory or internal rate of return are forecasting tools that take internal and external information into account when computing financial forecasts. Financial modeling can provide more benefits only if business owners have access to accurate and timely economic information. These models also take into consideration the number of competitors or future economic changes in the marketplace. Business owners and managers may not need additional computer software applications to use forecast models, as these tools rely more on personal judgment and inference.” (Gallagher and Andrew, 2003) Financial forecasting “empowers people because their use implies that we can modify variables now to alter (or be prepared for) the future. A prediction is an invitation to introduce change into a system. Financial planning is a continuous process of directing and allocating financial resources to meet strategic goals and objectives. The output from financial planning takes the form of budgets.” (Brayshaw, R.E., Samuels, J.M. and Wilkes, F.M. 1990) Quantitative forecasting techniques are best used when changes are infrequent. In the rapidly changing world of finance quantitative techniques tend to be of little use. There should be an addition of more qualitative techniques into business and the budgeting process. Some of such qualitative techniques include interviews, surveys, market reports, articles and other reliable sources of information. Financial forecasting can help to improve the budgeting process, especially if operating in a rapidly changing environment. The Delphi method is an example of a qualitative financial forecasting technique. Here, a group of experts come together and reach a consensus on what they believe would happen in the future. Some times, questionnaires are used to aid this technique. This method has some disadvantages like low reliability with the consensus and inability to reach a clear consensus. Consensus methods of financial forecasting In complex systems, financial forecasting usually involves seeking for expert opinion from two or more financial experts. The financial forecast is hence obtained by synthesizing or synchronizing these expert opinions. One known method of arriving at a consensus forecast is by gathering various experts in one room and allowing them to argue matters out. The disadvantage of this method is that such situations are often controlled by those experts with better persuasion or group interaction skills. The Delphi technique is a better method of financial forecasting, as there is an attempt to rectify the inherent problems of face-to-face confrontation in the group of experts, and ensure that there is anonymity in the responses from the participants. In the classical Delphi technique, there is a well defined sequence of the proceedings. To begin with, each of the gathered experts is asked to write down his or her predictions. These predictions are then collated and copies of these are distributed among the participants. They are then asked to make comments about any extreme views or predictions and are also given a chance to defend or modify their initial opinions based on the views of the other experts. Finally, the modified opinions are gathered and fed back to the participants and they are asked to carry out a reassessment of their opinions in view of the opinions of the other participants. Smoothing out the numbers One simple approach to financial forecasting is the setting up of a model that relies on averages obtained from previous historical data. For instance if we take an average of the financial data for a period of 5 years, and as we continue into the next planning period, a new set of results for the moving average can be reached and thus utilized by putting more emphasis on the most recent data. Forecasting with Regression Analysis Regression analysis involves the study of the manner in which variables relate, with the aim of estimating or predicting the value of a particular variable from already established or assumed values of the other related variables. It should be noted that a regression model may fail to exploit the time dimension unless the variables are chosen very carefully. “One may particularly wish to consider using lagged and/or differenced variables in the forecasting equation, so that some of the history of the dependent and/or independent variables, as well as their current values, are used in the forecast. A regression using only one predictor is called a simple regression, but where there are two or more predictors, multiple regression analysis is employed.” (Heizer, J and Barry Render 2004). Regression analysis also involves scatter diagrams: A scatter diagram is a graphical representation of the pairs of data that can be drawn to gain an overall view of financial problems. Sensitivity Analysis It is possible to gauge the degree of sensitivity of a forecast in regard to any changes in the related variables. A range of possibilities can be also developed under various assumptions in order to prepare alternative plans. Thus, if plan A, we can quickly redirect to plan B. this method of sensitivity analysis enables us to know which assumptions make the largest impact on the financial forecast. This enables managers to concentrate most of their resources on the highest impact areas, so as to improve forecasting. The main benefit of this type of sensitivity analysis is that it provides an avenue to measure the probability or possibility of errors in financial forecasting. Conclusion Financial forecasting is a vital activity for every organization, as it can determine whether the organization fails or succeeds. In carrying out a financial forecast, an organization must adequately analyze and interpret the market and its projected sales in order to arrive at a reliable forecast. Depending on the organization in question, the level of desired detail and the market, financial forecasting may either involve a very simple process or it can be a very complex procedure These days, it is not unusual to diminish the value of mathematical extrapolation in forecasting. According to Makridakis and Wheelwright “judgmental forecasting is superior to mathematical models; however, there are many forecasting applications where computer generated forecasts are more feasible. For example, large manufacturing companies often forecast inventory levels for thousands of items each month. It would simply not be feasible to use judgmental forecasting in this kind of application.” (Makridakis, S. and Wheelwright, S.C. 1989) Financial modeling can make use of economic or corporate financial models to estimate sales or other financial forecasts. Financial planning and forecasting starts at the top of an organization, as there is need to start the budgeting process within the strategic planning process because strategic decisions usually have financial implications. Without proper financial forecasting, a project, or the budget for the project is bound to fail. This kind of strategic planning involves a formal process of establishing goals and objectives over the long run and involves the development of a mission statement that captures the purpose of the existence of an organization and its future plans. Thus, financial planning and forecasting are extremely important in order to avoid mistakes in the future. Forecasting helps in the establishment of financial goals for the short term, as well as for long-term planning. References Aquilano, Chase and Jacobs (2005). Operations management for competitive advantage, New Jersey: John Wiley & sons, Inc. Atrill, P. and McLaney E. (1998), Accounting: An Introduction. Prentice Hall, Europe. Brayshaw, R.E., Samuels, J.M. and Wilkes, F.M. (1990), Management of Company Finance. Chapman and Hall, London Brealey, R.A., Marcus, S.C. and Myers, A.J. (1991) Fundamentals of Corporate Finance. McGraw-Hill, New York. Gallagher, Timothy J, and Joseph D. (2003) Financial Management: Principles and Practice. Prentice Hall. Heizer, J and Barry Render (2004) Principles of Operations Management. Prentice Hall. Upper Saddle River, N.J. Makridakis, S. and Wheelwright, S.C. (1989), Forecasting Methods for Management. Chichester: Wiley. Peter Rob, Carlos Coronel (2004) Database Systems: Design Implementation and Management Read More