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as 12-20-2024 4:00pm EST

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Stocks

Consumer Discretionary

Business Services

Nasdaq

Paysafe Ltd is an integrated payments platform. Its core purpose is to enable businesses and consumers to connect and transact seamlessly through capabilities in payment processing, digital wallet, and online cash solutions. The company provides payment solutions through three primary lines of business: Integrated Processing, Digital Wallet, and eCash Solutions. It derives a majority of revenue from the USA followed by Germany, the UK, and all other countries.

More About Our PSFE ML Model...

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

To train our stocks PSFE 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 PSFE 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 PSFE 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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