Second-Order Exponential Smoothing forecasting model

[former_member804079]

Hi SAP users,

I am new here, so I do appologize if this post is posted in the wrong place.

I have a short question regarding to one of your forecast models: Second-Order Exponential Smoothing.

I am currently doing my Master Thesis. In short, we are writing about food waste and its impact on sustainability through CO2e emissisons - we are trying to improve a current forecasting model for a firm which is a constant simple expoential smoothing model.

I have analyzed the second-order exponential smoothing model to see if it is a better fit, however, I am not quite sure how to interpret the formula of the model (https://help.sap.com/docs/SAP_S4HANA_ON-PREMISE/4a9f13fe60454250988a4a0f4f014712/df6db6531de6b64ce10000000a174cb4.html?version=1610.latest)

I can see that it contains two parts, G(t)(1) and G(t)(2). The first part is quite similar to the initial first-order smoothing model, but the second part confuses me a bit. Does it use t and t-1 vaues from the first smoothing and does it not include any beta or gamma values? I have read other theories on the second smoothing approach which often relates to a Holt Winter approach/model which includes beta and gamma values.

Does anyone have any mathematical derivations of the model, examples or simply want to explain my how to use the second-order exponential smoothing model? I have all data available including alpha values (no beta- and gamma values).

Thank you a lot!
Best regards, Oscar

[AlexGourdet]

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[former_member804079]

Hi Alex Gourdet,

When searching for answers, I only find similar questions without any clear answers. Only usable answer is to follow a link with explanations, however, the links are not accesable anymore.

I wonder if anyone can explain me the mathematics in the two models?

Best,

Oscar