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Time Series and Forecasting BASE Master 2013 Problem set 2 News Shocks Instructions: You can work in groups of two. I need the m ?less you use and a .pdf ?LE with an explanation of what you do. The
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Build the time series model: Use the chosen model to fit the training data. This involves estimating the model parameters and fine-tuning the model to minimize errors or improve accuracy. Consider adjusting for seasonality, trends, or any other relevant factors in the data.
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Validate the model: Once the model is built, validate it using the testing set. Evaluate how well the model predicts future data points by comparing the forecasted values with the actual values. Use metrics like Mean Absolute Error (MAE) or Root Mean Squared Error (RMSE) to assess the accuracy of the forecasts.
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Fine-tune and improve the model: If the initial model performance is not satisfactory, iterate and refine the model by adjusting model parameters, trying different algorithms, or including additional features. Continuously evaluate the model's performance and iterate until a satisfactory forecasting accuracy is achieved.
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