Parabolic Machine Learning
The stock market is a diametrical system where when one person or company makes money there is another person or company who lost the same amount.
In a fast-moving investment space where 80% of stocks are traded by computers, the ability to use Predictive Analytics is a key driver in higher returns and lower risk.
Having relevant information gives you the ability to become more successful.
Parabolic 5.0 Weekly Swing Watch-list
Parabolic Watch-list are designed to help you pre-plan your trading strategy. With a proactive system that helps you be able to prioritize movers with higher potential, the trader is able to have a better idea of trade timeframe and how to optimize entry. This also gives the trader to assess risk to reward ratios and to ensure he is gaining a competitive edge in his investment.
Parabolic 5.0 Weekly Watch-list perfectly flows straight into our Parabolic 5.0 Swing Alerts Bot.
If these watch-list items meet our top setup criteria they will be featured in our Swing Alerts Bot.
Parabolic 5.0 Swing Alerts Bot
Gain access to the most proactive investment data
Parabolic Data System is a powerful tool for investors to have realistic expectations in their investments. Through the process of reaching the Predicted Price Target, traders were given key pivot points, resistance levels to help them assess market risk throughout the investment. This particular Biopharm investment produced 40% potential returns in a 11 day timeframe.
With an ever changing market, having relevant data-driven analytics will not only give you the opportunity for higher reward plays but produce you less risk. Key data tools the Parabolic Data System provides include the following:
Parabolic’s Wave Theory for entry, Parabolic Short Max Pain for key momentum amplifiers, and Parabolic Predicted Price target for max two week investment potential. Add the Data tools with Parabolic’s Professional traders and you get the best of both a Trade Room and top low risk investment ideas.
Parabolic 5.0 Momentum Alert Example
Still Not Sure?
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