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as 06-21-2024 4:00pm EST

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Stocks

Real Estate

Real Estate Investment Trusts

Nasdaq

National Storage Affiliates Trust Trust is a real estate investment trust. The company owns, operates, and acquires self-storage properties located within the metropolitan statistical areas throughout the United States. With the help of property management platform, the company manages and controls the day-to-day operations and affairs of consolidated properties and unconsolidated real estate ventures under the iStorage, SecurCare, Northwest and Move It brands.

More About Our NSA ML Model...

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

To train our stocks NSA 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 NSA 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 NSA 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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