6 prompts for neural networks used by a trader with 200,000 subscribers
A crypto trader with an audience of over 200,000 on X, known by the pseudonym Tyler Durden, published a set of six prompts for neural networks. According to him, these commands help him make more informed trading decisions and manage risks. Let's break down each one and assess their practical value.
Risk/Reward
This prompt forces the neural network to break down a trade into a potential loss-to-profit ratio. The output provides the trader with a recommended entry point, stop-loss level, and target profit-taking levels. This approach instills discipline and filters out trades with unfavorable ratios, which is critically important for the long-term sustainability of the deposit.
"Apply a risk/reward framework to [my trading setup]. Calculate the optimal entry point, stop-loss level, and target levels."
Macro Overview
Instead of focusing on the chart of a specific asset, this prompt shifts attention to the macroeconomic picture. The neural network assesses how key factors—interest rates, inflation, and the strength of the dollar—impact the price. This is especially useful during periods when the market is driven not by technical signals but by central bank decisions.
"Use macro analysis to evaluate [the asset]. Assess how interest rates, inflation, and the strength of the dollar affect the price direction."
Liquidity Map
This prompt aims to identify zones where liquidity is concentrated—clusters of retail traders' stop orders and large institutional orders. The idea is that price often gravitates toward these levels. Understanding such zones helps anticipate movements and avoid triggering one's own stops.
"Create a liquidity map for [the asset]. Identify where stop clusters and institutional orders are most likely concentrated."
Correlation Matrix
This tool analyzes how closely the assets in a portfolio are related. If several positions move in sync, the portfolio only appears diversified but actually carries concentrated risk. The neural network helps uncover such hidden connections and assess real, rather than apparent, diversification.
"Use correlation analysis on [my portfolio]. Identify hidden risk concentration between assets."
On-Chain Signals
This prompt uses blockchain data—public transaction history and wallet behavior. The neural network looks for accumulation patterns (when large holders increase positions) or distribution patterns (when they offload assets). Such patterns can sometimes precede price movements and serve as an additional signal alongside technical analysis.
"Apply on-chain analysis to [Bitcoin/crypto asset]. Identify accumulation or distribution patterns based on wallet behavior."
Portfolio Stress Test
This prompt tests the portfolio's resilience against adverse scenarios. The neural network models potential drawdowns—such as a sharp market decline—and shows which positions would suffer the most. This helps pre-assess the maximum possible loss and understand which assets make the portfolio most vulnerable.
"Use stress testing to evaluate [my portfolio]. Model drawdown scenarios and identify the weakest positions."
Expert comment: Using AI for analysis is a powerful tool, but it does not replace the need for your own verification. Neural networks can make mistakes, especially in volatile markets. The key advantage of these prompts lies not in predicting the future, but in structuring the approach to risk and discipline. All decisions should be made with a full understanding of potential losses.