What is forecasting Explain the different techniques of forecasting.pdf

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What is forecasting? Explain the different techniques of forecasting? Solution Forecasting is the process of estimating the relevant events of future, based on the analysis of their past and present behaviour. Techniques of Forecasting: There are various methods of forecasting. Some of them are: 1. Historical Analogy Method: Under this method, forecast in regard to a particular situation is based on some analogous conditions elsewhere in the past. The economic situation of a country can be predicted by making comparison with the advanced countries at a particular stage through which the country is presently passing. 2. Survey Method: Surveys can be conducted to gather information on the intentions of the concerned people. 3. Opinion Poll: Opinion poll is conducted to assess the opinion of the experienced persons and experts in the particular field whose views carry a lot of weight. 4. Business Barometers: A barometer is used to measure the atmospheric pressure. In the same way, index numbers are used to measure the state of an economy between two or more periods. These index numbers are the device to study the trends, seasonal fluctuations, cyclical movements, and irregular fluctuations. 5. Time Series Analysis: Time series analysis involves decomposition of historical series into its various components, viz. trend, seasonal variances, cyclical variations, and random variances. When the various components of a time series are separated, the variation of a particular situation, the subject under study, can be known over the period of time and projection can be made about the future. 6. Regression Analysis: Regression analysis is meant to disclose the relative movements of two or more inter-related series. It is used to estimate the changes in one variable as a result of specified changes in other variable or variables. In economic and business situations, a number of factors affect a business activity simultaneously. 7. Input-Output Analysis: According to this method, a forecast of output is based on given input if relationship between input and output is known. Similarly, input requirement can be forecast on the basis of final output with a given input-output relationship. The basis of this technique is that the various sectors of economy are inter related and such inter-relationships are well-established..

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output with a given input-output relationship. The basis of this technique is that the various
sectors of economy are inter-related and such inter-relationships are well-established.

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Forecasting Discuss the different types of forecasts to include time-series, causal, and qualitative models. When might a researcher or project manager utilize exponential smoothing? What benefit does a Delphi technique provide when working with qualitative-based decision making? Solution Forecasting is basically the process of estimating or predicting the future trend, based on the trend and information of the past and the present.Forecasting is a calculated assumption of how the trend is going to be in a future date based on what we saw in the past and what we are observing in the present scenario. Time series methods: These methods use historical data to assume future trends. There are various time series methods such as, 1)Simple Moving Average Method: it is commonly used in technical analysis of financial data such as stock prices,trading volumes or returns.Among the most popular technical indicators, moving averages are used to gauge the direction of the current trend.It is calculated by averaging a number of past data points. Once determined, the resulting average is then plotted onto a chart in order to allow traders to look at smoothed data rather than focusing on the day-to-day price fluctuations that are inherent in all financial markets. As new values become available, the oldest data points must be dropped from the set and new data points must come in to replace them. Thus, the data set is constantly \"moving\" to account for new data as it becomes available. This method of calculation ensures that only the current information is being accounted for. for example, to calculate a basic 10-day moving average you would add up the closing prices from the past 10 days and then divide the result by 10. The average thus obtained is plotted on a chart. As the time progresses, we replace the first variable with the latest variable available ie. latest closing price of 11th day, therefore getting a new avaerage. We plot this one too in the chart. The chart thus formed gives a trend which is used for forecasting future movements. 2)Exponentially smoothed moving average: Over the years, technicians have found two problems with the simple moving average. The first problem lies in the time frame of the moving average (MA). Most technical analysts believe that price action, the opening or closing stock price, is not enough on which to depend for properly predicting buy or sell signals of the MA\'s crossover action. To solve this problem, analysts now assign more weight to the most recent price data by using the exponentially smoothed moving average (EMA).It is a type of infinite impulse response filter that applies weighting factors which decrease exponentially. The weighting for each older datum decreases exponentially, never reaching zero. The exponentially smoothed moving average addresses both of the problems associated with the simple moving average. First, the exponentially smoothed average assigns a greater weight to the more recent data..

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