Tickeron, Inc., a leader in AI-driven stock trading bots, introduces a new line of advanced trading robots. These robots use Tickeron's proprietary Financial Learning Models (FLMs) and advanced technical analysis. They are designed for day traders, integrating classical models with modern quantitative analytics to optimize trading strategies with high liquidity and high volatility Stocks.

Tickeron's new robots, stock price impulse actions with high volatility, initiate trades during 5%+ volatility surges, maximizing profit opportunities. FLMs analyze historical data and current conditions to predict stock performance. Continuous learning ensures up-to-date insights, giving users a strategic trading edge.

High Volatility: Designed to capitalize on significant spikes in market volatility, maximizing profit during rapid price movements.
Price Action: Trades are executed based on detailed price action analysis, ensuring precise and timely market entries and exits.
Average Holding Period: Positions held for an average of 1 day, suitable for day traders seeking short-term gains.
Trade Execution: Trades are conducted at market openings to leverage early-day volatility and capture initial market movements.
Stop Loss: Set within a range of 2-10% per trade, safeguarding against significant losses and protecting capital.
Win Rate: With a high win rate, the bot offers a high probability of successful trades, instilling confidence in its strategy.

Sergey Savastiouk, Ph.D., CEO of Tickeron, emphasized the importance of technical analysis in stock trading with high volatility. He stated, "Technical analysis helps traders select stocks confidently, reducing the impact of market volatility. Financial Learning Models (FLMs) use machine learning to identify patterns in financial data and conditions when they work. Training FLMs using technical analysis, Tickeron's platform equips traders with AI tools to achieve their financial goals, especially in high-liquidity stocks."

About Tickeron
Tickeron provides AI-driven tools for traders. Its Financial Learning Models (FLMs) use machine learning to enhance financial education and decision-making. These FLMs offer insights into market trends, trading strategies, and investment options, tailored to users' knowledge levels. Real-time data and predictive analytics help users understand financial markets and improve trading decisions. Disclosures

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