Mobshed AI Agents are autonomous trading programs designed to operate on your behalf, using advanced machine-learning models trained on real market data. Each agent acts as your personal trading engine - monitoring markets, executing trades, managing risk, and accumulating Mobshed tokens based on your performance.
You choose the strategy, configure the agent, and let it run continuously while the system handles the heavy lifting. Whether you want high-frequency activity, volatility-driven setups, or more selective trend-based trading, Mobshed Agents adapt to diverse conditions and optimize decisions in real time.
You can create your own fully customized AI Agent - an autonomous program that trades on your behalf using the strategy of your choice (Harvesters, Scavengers, Explorers or Celesters).
Each agent behaves independently, managing entries, exits, and allocations based on its assigned strategy. Users can create up to five agents at a time.
Key components of these strategies include:
Mobshed offers four distinct AI trading strategies, each trained and optimized for specific market conditions. These strategies are continuously refined using data from more than 150 cryptocurrencies since March 2022.
Every strategy is designed to respond differently depending on volatility, trend strength, and liquidity, ensuring that your agents can adapt to diverse market environments.
Key components of these strategies include:
The system continuously analyzes live market data - price movements, trends, volatility shifts, momentum changes, and other signals - to identify profitable setups. This real-time scanning enables fast reaction to short-term opportunities and evolving market structure.
All strategies evolve through ongoing machine-learning updates. They leverage historical patterns and current conditions to stay aligned with both trending and ranging markets. This allows the agents to maintain consistency in volatile environments and avoid stagnation in quieter ones.
When you create an agent, you also select a Mobshed Token (e.g., OCN, CLM, FNA, etc.) that the agent will accumulate as it generates profitable trades.
These tokens are automatically stored in your portfolio, where you can choose to hold them or sell them at any time.
Your token accumulation grows alongside your trading performance, allowing you to participate directly in the broader Mobshed ecosystem while your agents work for you.
When you create an agent, you also select a Mobshed Token (e.g., OCN, CLM, FNA, etc.) that the agent will accumulate as it generates profitable trades.
These tokens are automatically stored in your portfolio, where you can choose to hold them or sell them at any time.
Your token accumulation grows alongside your trading performance, allowing you to participate directly in the broader Mobshed ecosystem while your agents work for you.
Over the past 3 years, we’ve tested different strategies and ended up with four major approaches.
Yield-focused strategies built around Wilson Lower Bound, prioritizing setups that have the most statistically reliable edge rather than the flashiest raw win rates. Their job is to steadily “harvest” repeatable gains by selecting signals with proven consistency.
Opportunistic strategies that work inside the Flag Gating System, targeting win-rate setups where edge existsThey are built to extract value selectively, using pivot reversals, RSI exhaustion, drop-from-high behavior, and optional volume confirmation.
Precision-focused strategies that combine multinomial logic with the Microstructure Risk Method to target a statistically reliable edge. They are built to commit capital only when both contextual behavior and trade-quality structure align.
Discovery-driven strategies powered by the Microstructure Risk Method, designed to identify fresh trend transitions before they become obvious to slower systems. They use multi-timeframe alignment, EMA slope confirmation, and confirmed oscillator flips.
Momentum-aware strategies that combine Wilson scoring with streak logic to pursue a statistically grounded edge during sustained runs of strength. They help the system press into consistency while staying anchored to proven signal reliability.
Directional strategies that combine Machine Learning Scoring Method with uptrend confirmation to favor setups with positive market structure. They help the system deploy capital when predictive strength and trend alignment point the same way.
