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Tickeron Launches a New Generation of AI Robots Driven by Fundamental Analysis

Tickeron, the quant-sourced marketplace for AI-powered stock trading tools, is pleased to introduce a new set of AI robots driven by fundamental analysis.

Tickeron’s previously released AI Robots have all relied on technical analysis (TA) to train our AI algorithms. To advance our technology and provide a more comprehensive AI tool to our investor community, we’re implementing sophisticated models that apply fundamental analysis (FA) to the AI Robot building process. As a result, we launch the new generation of user-friendly AI Robots with a low frequency of signals and a number of open positions.

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Fundamental analysis allows investors to evaluate a business’s balance sheet, earnings growth, and other key metrics that measure quality and fair value. Strong fundamental analysis can separate companies with solid growth prospects and competitive advantages from companies that are underperforming or poised to underperform.

Tickeron has researched hundreds of investment strategies based on different approaches – value, growth, momentum, factors, and volatility, to name a few. Our research on fundamental analysis focused on both classical models for assessing the value and quality of a company’s business (Graham, Fama-French, Piotroski, etc.) and more modern approaches (GARP, Greenblatt, Novy-Marx, etc.).

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Our mathematical algorithms performed thousands of backtests to evaluate each individual model’s effectiveness historically. Our team of quants used data and findings from our research to create a pool of unique investment strategies that combine the most effective elements of different approaches to fundamental analysis.

“Tickeron’s new line of AI Robots driven by fundamental analysis (FA) allows us to significantly expand our range of capabilities for developing trading strategies. As a result, we are getting even closer to real money trading for our clients,” said Sergey Savastiouk, Ph.D., CEO and Founder of Tickeron.

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[To share your insights with us, please write to sghosh@martechseries.com]

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