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as 12-23-2024 4:00pm EST

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Stocks

Health Care

Medicinal Chemicals and Botanical Products

Nasdaq

Bon Natural Life Ltd is engaged in the manufacturing of personal care ingredients, such as plants extracted fragrance compounds to perfume and fragrance manufacturers, natural health supplements such as powder drinks and bioactive food ingredient products mostly used as food additives and nutritional supplements. The company has its geographic presence in PRC and in Overseas. The company derives maximum revenue from perfumes and fragrance products.

More About Our BON ML Model...

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

To train our stocks BON 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 BON 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 BON 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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