As a financial analyst, writer, and AI specialist, I've always pushed for innovations that merge artificial intelligence with actionable trading tools. In the fast-paced world of modern markets, where volatility demands quick decisions, Tickeron's new "My Trades Aggregator (from AI Robots Followed)" aggregator stands out as a revolutionary feature. Launched to meet the growing need for multi-robot oversight, this centralized dashboard lets users follow and monitor trades from multiple AI robots simultaneously. No more toggling between screens or drowning in data silos—whether you're tracking three Signal Agents for quick scalps or ten Brokerage Agents for high-frequency plays, everything converges in one intuitive board. Built for Tickeron's AI Trading suite, it streamlines portfolio management, boosting efficiency for traders at all levels.
Demystifying AI Trading Agents: Signal, Virtual, and Brokerage
Tickeron's AI Trading ecosystem leverages machine learning algorithms trained on 5-, 15-, and 60-minute timeframes to deliver real-time trading signals. Each agent type caters to different trader needs, ensuring flexibility without compromising on accuracy.
The AI Trading (Signal Agents) focus on simplicity and immediacy. These bots generate signals optimized for copy trading, using fixed trade amounts and requiring no minimum balance. Ideal for beginners or those seeking straightforward execution, they provide actionable alerts to mimic professional moves instantly, reducing decision fatigue in fast-paced sessions.
For more sophisticated users, AI Trading (Virtual Agents) introduces money management features. With customizable virtual balances, these agents simulate trades while incorporating risk controls like position sizing and stop losses. This allows traders to test strategies in a risk-free environment before going live, all powered by the same robust ML models that analyze short-term market patterns.
At the professional level, AI Trading (Brokerage Agents) integrates tick-level brokerage data for ultra-precise signals, including dynamic trade amounts based on live market depth. These agents excel in high-frequency environments, offering traders an edge through granular insights into liquidity and volatility, directly executable via connected brokers.
By consolidating these agents on the My Trades Aggregator, users gain a unified view, making it easier to diversify across strategies without juggling multiple platforms.
Core Fields on the My Trades Aggregator: Your All-in-One Tracking Hub
The board's intuitive interface displays a comprehensive set of fields, ensuring no detail slips through the cracks. Here's how it structures your oversight:
This layout transforms fragmented data into a cohesive narrative. Imagine overseeing five robots: one Signal Agent hunting quick scalps, two Virtual Agents managing balanced portfolios, and two Brokerage Agents chasing tick-driven opportunities. The board aggregates everything, flagging underperformers or scaling winners seamlessly.
Unlocking Benefits: Efficiency, Transparency, and Scalability
In an era of algorithmic dominance, the My Trades Aggregator addresses key pain points for multi-robot traders. Centralization reduces cognitive overload—studies show traders lose up to 20% efficiency when switching tools, but here, all signals and metrics converge. Transparency shines through the "Source of Idea" field, letting you audit AI decisions and refine your follow list.
Scalability is another boon: Track 3 robots for a starter portfolio or 10+ for advanced diversification. Recent performance snapshots, like Closed Trades from last week (e.g., 15 wins out of 22 for a Virtual Agent), provide instant ROI insights. No more manual spreadsheets or delayed alerts; everything updates in real-time, aligning with the 24/7 market grind.
From a financial analyst's lens, this board mitigates risks by promoting data-driven adjustments. If a Brokerage Agent's tick-level signals yield 8% weekly profits but high drawdowns, you can pause it via the dashboard. AI specialist perspective: The underlying ML evolves with market data, adapting to anomalies like earnings surprises, ensuring signals remain predictive.
Tickeron and Financial Learning Models (FLMs): The AI Backbone
At the heart of these agents lie Tickeron's Financial Learning Models (FLMs), a fusion of AI and technical analysis championed by Sergey Savastiouk, Ph.D., CEO of Tickeron. Savastiouk emphasizes FLMs' role in taming volatility: "By integrating machine learning with proven technical patterns, traders spot opportunities with greater accuracy, turning market noise into actionable intelligence."
FLMs power the board's robots by processing vast datasets—price action, volume, and sentiment—across timeframes. Beginner-friendly options, like liquidity-focused stock robots, offer real-time insights with minimal jargon, while advanced users benefit from pattern recognition that rivals human experts. This blend enhances control: Traders aren't blindly following bots but actively overseeing AI-enhanced decisions, fostering transparency in opaque markets.
Performance at a Glance: Recent Trades Insights
The board's analytics section spotlights momentum. For instance, Recent Trades might tally 45 actions across agents, with 28 Opened Trades signaling active strategies and 17 Closed Trades last week boasting a 65% win rate (average +2.3% profit). These metrics, segmented by agent type, help benchmark performance—Signal Agents for volume, Virtual for consistency, Brokerage for precision.
In summary, the My Trades board isn't just a tracker; it's a strategic command center for AI-augmented trading. By consolidating Signal, Virtual, and Brokerage Agents, it democratizes multi-robot oversight, backed by FLMs' intelligent core. For traders eyeing 5+ bots, this tool promises efficiency gains and sharper edges. Dive in, and let AI handle the heavy lifting while you focus on growth.
SOXL saw its Momentum Indicator move above the 0 level on September 10, 2025. This is an indication that the stock could be shifting in to a new upward move. Traders may want to consider buying the stock or buying call options. Tickeron's A.I.dvisor looked at 78 similar instances where the indicator turned positive. In of the 78 cases, the stock moved higher in the following days. The odds of a move higher are at .
The Moving Average Convergence Divergence (MACD) for SOXL just turned positive on September 10, 2025. Looking at past instances where SOXL's MACD turned positive, the stock continued to rise in of 47 cases over the following month. The odds of a continued upward trend are .
SOXL moved above its 50-day moving average on September 05, 2025 date and that indicates a change from a downward trend to an upward trend.
The 50-day moving average for SOXL moved above the 200-day moving average on August 08, 2025. This could be a long-term bullish signal for the stock as the stock shifts to an upward trend.
Following a 3-day Advance, the price is estimated to grow further. Considering data from situations where SOXL advanced for three days, in of 321 cases, the price rose further within the following month. The odds of a continued upward trend are .
The 10-day RSI Indicator for SOXL moved out of overbought territory on August 15, 2025. This could be a bearish sign for the stock. Traders may want to consider selling the stock or buying put options. Tickeron's A.I.dvisor looked at 37 similar instances where the indicator moved out of overbought territory. In of the 37 cases, the stock moved lower in the following days. This puts the odds of a move lower at .
The Stochastic Oscillator has been in the overbought zone for 2 days. Expect a price pull-back in the near future.
Following a 3-day decline, the stock is projected to fall further. Considering past instances where SOXL declined for three days, the price rose further in of 62 cases within the following month. The odds of a continued downward trend are .
SOXL broke above its upper Bollinger Band on August 13, 2025. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options.
The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
Category Trading