1. Home
  2. VGAS
  3. VGAS Forecast

as 11-14-2024 2:37pm EST

$
-
.
-
-
-
$
-
.
-
-
-
-
.
-
-
%

Stocks

Industrials

Major Chemicals

Nasdaq

Verde Clean Fuels Inc is a renewable energy company specializing in the conversion of synthesis gas, or syngas, derived from diverse feedstocks, such as biomass, MSW and mixed plastics, as well as natural gas (including synthetic natural gas) and other feedstocks, into liquid hydrocarbons that can be used as gasoline through a proprietary liquid fuels technology, the STG process.

More About Our VGAS ML Model...

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

To train our stocks VGAS 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 VGAS 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 VGAS 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.

Share on Social Networks: