Ready to go beyond theory and start building real stock forecasting models?
In Book 3 of the Foundations of Time Series Forecasting for Canadian Dividend Stocks series, we dive into the core of predictive modeling using time series analysis in R. You’ll build, train, and validate powerful forecasting models on historical stock data from 11 Canadian Dividend Aristocrats.
This book is your step-by-step guide to implementing proven techniques like ARIMA, SARIMA, Exponential Smoothing (ETS), and Facebook Prophet—all explained through practical R examples and model comparisons.
What You’ll Learn:
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Build and compare time series models (ARIMA, SARIMA, ETS, Prophet)
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Fit models and assess performance on historical dividend stock data
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Use backtesting techniques like walk-forward and rolling forecasts
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Apply evaluation metrics like MAE, RMSE, and MAPE
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Validate your forecasting models for real-world investment scenarios
By the end, you’ll not only have trained forecasting models—you’ll understand which ones perform best and why.
Whether you’re an investor, data scientist, or student, this hands-on book empowers you to create and validate models that deliver trustworthy insights for long-term portfolio planning.
Author: Chuck Egboka
Year: 2025
Pages: TBD
Publisher: Cuttell Publications
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