Cryptohopper's AI configuration offers users advanced tools for tailoring trading strategies, including the 'neutral signals' setting. This feature is part of the platform's AI strategy scoring and signal processing functionality.
What are neutral signals?
Neutral signals represent periods when the AI evaluates market data but determines that neither 'buy' nor 'sell' criteria have been met. These signals are derived from widely-used market indicators. For instance, if key indicators, such as moving averages or other technical analysis tools, fail to meet thresholds for triggering buy or sell actions, the resulting evaluation is neutral. This outcome indicates market ambiguity or balance at that time.
The role of the 'neutral signals' setting
The 'neutral signals' setting allows users to assign a specific level of importance to these neutral evaluations when shaping the bot's trading behavior. This configuration ensures the AI reacts appropriately to varying market conditions. The impact of this setting depends on its value:
Higher values (closer to 100): These prioritize neutral signals more heavily, making the bot more cautious. In this configuration, the bot is less likely to act on buy or sell signals in market conditions deemed neutral.
Lower values (closer to 1): These reduce the importance of neutral signals while increasing the weightage given to buy or sell signals, making the bot more reactive to potential opportunities.
By adjusting this setting, traders can influence how the bot interprets neutrality, enabling strategies that capitalize on specific market characteristics, such as avoiding decision-making in indecisive markets (reducing the risk of overtrading) or seizing opportunities during volatility.
Configuring the setting for your strategy
To optimize the neutral signals feature:
Define Your Goals: Determine whether your focus is on reducing risk by avoiding decisions in neutral markets or on increasing responsiveness.
Test Various Levels: Experiment with different levels of the 'neutral signals' setting (e.g., starting at 50 for balance) in simulated or low-risk environments to assess impact.
Monitor Results: Regularly review the bot's performance to ensure the adjustments align with your strategy.