Quantitative Forecasting
Part 3 of Forecasting by Hand by Dr. Alvin Ang
This is part of a series on :
- Quantitative Forecasting = Time Series Method or Causal Method.
- In this article, we only focus on Time Series Method.
- Causal Methods = Regression / Econometrics / Tracking Signals
Time Series method comprises of 2 types:
1. Smoothing Method (stable)
Purpose to “smooth out” or “average out” the irregular components of time series.
- Moving Average
- Weighted Moving Average
- Exponential Moving Average
2. Trend Projection (unstable)
- Linear trend = Gradual shifting of the time series over a long period of time.
- Cyclical trend = Regular pattern of sequences above and below the trend line.
- Seasonal trend (CMA) = Regular patterns of variability within certain time periods, such as over a year.
- Irregular trend = Short‐term, unanticipated and non‐recurring factors that affect the values of the time series. One cannot attempt to predict its impact on the time series in advance.
About Dr. Alvin Ang
Dr. Alvin Ang earned his Ph.D., Masters and Bachelor degrees from NTU, Singapore. Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background He is a scientist, entrepreneur, as well as a personal/business advisor.
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More about him at www.AlvinAng.sg.
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