| MAY 1983
Applying ARIMA Forecasts by ERIC WEISS, Ph.D.
Applying ARIMA Forecasts by ERIC WEISS, Ph.D. ""Applying ARIMA Forecasts"" is an article continuing a series started in the October (82) and the January (83) issues of Technical Analysis. AutoRegressive-lntegrated Moving Average(ARIMA) is a forecasting methodology based upon the techniques described by Box and Jenkins in their book: Time Series Analysis, Forecasting and Control, published by Holden-Day, 1976, 2nd ed. With understanding and time one may construct a model of a discrete statistical time series, such as the markets, that will forecast the future with known probable error. To begin, let's use this example: Variable: high Sum of Squared Residuals: 44.76 Residual Variance: .75 Average Absolute Error: .65 Observations: 64 Degrees of Freedom: 60
by ERIC WEISS, Ph.D.
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