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as 11-22-2024 4:00pm EST

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Weyerhaeuser ranks among the world's largest forest product companies. Following the 2016 sale of its pulp business to International Paper, Weyerhaeuser operates three business segments: timberlands, wood products, and real estate. Weyerhaeuser is structured as a real estate investment trust and is not required to pay federal income taxes on earnings generated by timber harvest activities. Earnings from its wood products segment are subject to federal income tax. Weyerhaeuser acquired fellow timber REIT Plum Creek in 2016.

More About Our WY ML Model...

What kind of parameters do you use to train WY stocks ML model?

To train our stocks WY ML model, we use historical data with over 25 parameters, including volume indicators, volatility indicators, momentum indicators, trend indicators, and other metrics.

How often do you update WY ML model?

We update our ML model either weekly or biweekly, depending on the market capitalization of the stocks, using TensorFlow, typically over the weekend.

Why is the accuracy of your WY model low?

Unfortunately, our current data provider offers limited historical data, which impacts the accuracy of our ML model. However, as we continue to gather more data over time and add more indicators, we expect the accuracy of our model to improve.

How can I provide and share more data with you to increase your ML model accuracy?

We would greatly appreciate your contribution. Please send an email to [email protected]

Do you offer an ML model for shorter time periods, such as 5 minutes or 15 minutes?

Yes, we offer it for strategy purposes only, with intervals: 1 minute, 2 minutes, 5 minutes, 15 minutes, and 30 minutes etc.

Can I rely on your ML model to make financial decisions regarding buying or selling stocks, or is it only intended for learning purposes?

Our ML model is primarily designed for educational purposes and is not intended to provide financial advice. We strongly recommend consulting with a financial advisor before making any buying or selling decisions.

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