FORECASTING METHODS

FORECASTING METHODS

1. FORECAST

   • The act of predicting business activity for a future period of time

2. QUANTITATIVE

   • SIMPLE AND MOVING AVERAGE
     • (SMA )
     • calculated by adding recent closing prices and then dividing that by the number of time periods in the calculation average
       • ifferent number of time periods
         • average price of the security over the time period
       • closing price of the security for a number of time periods
       • dividing this total by the number of time periods
   • EXPONENTIAL SMOOTHING
     • rule of thumb technique
     • smoothing time series data
     • using the exponential window function.
       • xponential functions are used to assign exponentially decreasing weights over time.
   • SIMPLE AND ULTIPLE LINEAL REGRESSION
     • xtension of the simple linear regression model
     • are simply more than one independent (predictor) variable
     • The intercept, β0 of the line, gives the expected value of Y when all x 0 s = 0
       • The slopes, βj , j = 1...p where p is the number of explanatory variables, give the increase (or decrease) in Y for a unit increase in each xj i, given the other explanatory variables in the model.
   • MINIMUN SQUARES
     • standard approach
     • to approximate the solution of overdetermined systems
       • The most important application is in data fitting
     • Least-squares problems fall into two categories
       • ordinary least squares
       • nonlinear least squares

3. QUALITATIVE

   • DELPHI METHOD
     • structured communication technique or method
     • originally developed as a systematic, interactive forecasting method which relies on a panel of experts
   • CONSUMER MARKET SURVEY
   • MOVING AVERAGES
     • s a technical analysis indicator that helps smooth out price action by filtering out the “noise” from random price fluctuations.
   • Stationary time series
     • The random variable D(t) has thus a mean equal to a and a standard deviation equal to σ. This is an assumption. In reality we do not know whether the demand is distributed like this. We just think here, it is constant. The problem then is to determine the constant a.

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• Forecasting Methods Overview (Incorporar)