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Quantitative Forecasting (Time Series)

QuestionAnswer
Define Casual Forecasting (regression analysis). Assumes that the factor to be forecasted exhibits a cause-effect relationship with one or more independent variables.
What is the objective of Casual Forecasting (regression analysis)? To discover the form of that relationship between the variables and be able to forecast future values of the dependent variable.
What method is used in Casual Forecasting? Simple Linear Regression model (SLR)
What is the Simple Linear Regression (SLR) model? Finding the best fitted linear line for a given set of data.
What is the formula for Simple Linear Regression? y=a+b*x y: predicted(dependent variable) X: predictor (independent) b: regression slope of line a: Y intercept
How to find the slope or B in Simple Linear regression? y=n(sum of xy)- (Sum X)(Sum Y) ------------------------ n(sum x ^)- (sum x ^)
How to find Y intercept or A in simple Linear Regression? a= (sum Y)- b(sum x) ---------------- n
What is Time Series Analysis? (TS) Set of measurements ordered through time on a particular quantity of interest
Components of TS? T: Trend S: Seasonality C: Cyclical R: residual
What are smoothing methods? methods used in adjusting data to cancel out the effect of random variations and reveals components that we are looking for.
What are the popular smoothing methods? 1. Moving Average (MA) 2. Simple Exponential Smoothing (SES) 3. Naive Approach
What is the Naive Approach? Using data from previous period to forecast future values
What is the Moving Average (MA)? Based on idea that any large random component at any point in time will have smaller effect if the value is averaged with neighbors.
When does Moving Average (MA) not work? When trends or Seasonality occurs
Formula for MA? MA= Sum (most recent N data values) ------------------------- N
What does having a large N for MA mean? Slow response to real changes in demand, more stable (greater smoothing effect)
What does a small N for MA mean? Quick response to changes in demand, little smoothing effect.
What is weighted Moving average? (WMA) same as MA except putting more weight on recent data
What is Simple Exponential Smoothing? (SES) smoothing method giving weight to all data but it gives weight to recent observations more heavily
When does Simple exponential smoothing (SES) work well? when there are no seasonal or trend components
what is the formula for SES? f(t)= a* A t-1 + (1-a)Ft-1
When should one use a small (a) in a TS? If the TS contains substantial random components don't give much weight to most current observation alone.
When should one use a Large (a)in a TS? If TS is rather smooth
What can a higher value of (a) do? respond to sudden change more quickly
What is Linear Trend Approach? (time series regression forecasting) Deals with trend component. Based on Least square approach.
Which forecasting method provides most accurate forecast? Linear Trend Approach
What is diagnostic Checking? Evaluating performance of a regression equation
what are four forms of diagnostic checking? 1. Residual analysis 2. MSE 3. T test 4.R^2
What is MSE? Mean squared Errors. Smaller the better. Useful when two or more regression models are considered.
What is the t- test? Test for significance (usefulness) of regression equation. Testing weather I variable effects D variable.
What is Correlation Analysis? Measure of linear association between x and y. determines relative strenght or relationship
Created by: 511052957