Category Archives: Python

Walk-Forward Strategy Performance

The previous post introduced forecasting using multiple series and also suggested another form of improvement – namely filtering out low probability forecasts. Can we improve the forecasts by any of these approaches, and if yes, by how much?
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Better Model Selection for Evolving Models

For quite some time now I have been using R’s caret package to choose the model for forecasting time series data. The approach is satisfactory as long as the model is not an evolving model (i.e. is not re-trained), or if it evolves rarely. If the model is re-trained often – the approach has significant computational overhead. Interestingly enough, an alternative, more efficient approach allows also for more flexibility in the area of model selection.

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Loading Data with Pandas

On at least a couple of occasions lately, I realized that I may need Python in the near future. While I have amassed some limited experience with the language over the years, I never spent the time to understand Pandas, its de-facto standard data-frame library.

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