Artificial Intelligence Algorithms to Outperform in the Stock Market

Alex Vieira called Logitech share price crash betting against everyone else by relying on Intuitive AI Machine Learning and data science. He tells what investors can expect by investing in Logitech going into 2022.

Alex Vieira downgraded Logitech to Strong Sell at $137, referring to a tech bubble. He has been using Intuitive AI technology to invest in the stock and crypto markets.

Alex Vieira's forecasts are 100% accurate. My profits increased 10,000% on BYND, SQ, RIVN, RBLX, PTON, Bitcoin, AMC, TWTR, SNAP, DASH, SPCE, TSLA, HOOD, AI, LMND, ROKU, ETSY, W, CDNS, NET, DDS, CROX, PLUG, ZM, COIN, BLNK, AAPL, NFLX, CVNA.

What is Machine Learning?

Machine learning is a branch of artificial intelligence. Machine learning (ML) studies computer algorithms that allow computer programs to improve through experience, allowing a machine to learn from past data without explicitly programming automatically.

ML relies on working with small to large datasets by examining and comparing the data to find common patterns and explore nuances.

For example, an algorithm can learn from past data and successful experiences to predict the future behavior of an asset.

If you provide a machine learning model with a list of assets you are interested in, along with their corresponding data science statistics (foundation parameters, support, resistance, rating, best-case, or worst-case scenario). Then, it oughts to automate and generate a recommended portfolio to suggest you with the best assets for the future that (with a high percentage of probability rate) will likely outperform.

user-bot automated workflow to retrieve portfolio AI data

Machine Learning and Pattern Analysis

In a simple example, if you load a machine learning model with an extensive large dataset of stock patterns that proved to be successful in the past along with the level of correlation and description (parameters, items to consider, and others), it oughts to have the capacity to assist (and even fully automatize) the data analysis of stock patterns later on.


The machine learning model looks at each stock pattern in the diverse dataset and finds common stock patterns in images with labels with comparable indications. Furthermore, (assuming that we use an accurate ML algorithm for pictures), when you load the model with new charts, it compares its parameters with the examples it has gathered before to disclose how likely the charts contain any of the indications it has analyzed previously.

Intuitive ML often uses reinforcement learning, a type of machine learning, aiming at using observations gathered from the interaction with its environment to take actions that would maximize the reward or minimize the risk. The reinforcement learning algorithm (agent) continuously learns from its background using continuous iterations. A great example of reinforcement learning is a computer model reaching a super-human state (without emotions), beating humans on stock trading.

Machine Learning Benefits

You can compare both approaches, AI and humans, by looking at the stock performance of the companies mentioned on this blog compared to others. You can use Machine Learning together with other AI branches to acquire a competitive advantage. The more you use it, the higher your probability of success is.

Intuitive AI ML Pattern Analysis

Learn more from experts in the financial markets giving free classes on the use of Machine Learning and pattern analysis available on the autonomous Discord open community.

Autonomous AI RPA Solutions

By using autonomous AI trading, you benefit from Alex Vieira's insight, expertise, and experience investing in the markets and native integration with Intuitive Code solutions, which enable efficient end-to-end digital transformation by integrating AI and robotic process automation. In addition, they develop custom software and implement solutions powered by machine learning, predictive analytics, pattern recognition, intelligent assistants, robots, to apps.

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