How Crypto Investor Made Over $70,000 Creating a ChatGPT Trading Bot

In today’s dynamic market scenario, artificial intelligence (AI) is transforming various sectors, including crypto trading. A notable example is Rekt Fencer, a pseudonymous investor on X (formerly Twitter), who claims to achieve a substantial profit of $71,500 using a trading bot powered by AI.

This case highlights the expanding role of AI in automating complex trading operations.

How Rekt Fencer Created Crypto Trading Bot

Rekt Fencer developed his ChatGPT-assisted trading bot using the Bollinger Band indicator. Some traders use this indicator for its effectiveness in analyzing market trends.

His strategy was buying when the price rose above the Bollinger Band and selling when it fell below. This tactic takes advantage of market volatility, allowing traders to predict potential price movements based on statistical data.

Read more: 13 Best AI Crypto Trading Bots To Maximize Your Profits

Rekt Fencer Crypto Trading Bot Performance. Source: X (Twitter)

Rekt Fencer outlined a process for others to replicate, emphasizing AI’s capability to automate trading.

Initially, Fencer adjusted the Bollinger Band settings on TradingView, a popular analytical platform among traders. He then guided users through coding the bot, involving several upgrades to enhance its adaptability to changing market conditions. Integrating the bot with ChatGPT was crucial for refining the trading algorithm.

Subsequent steps involved duplicating the indicator’s source code, renaming it, and performing necessary upgrades. Finally, the trading logic was scripted into the system.

“Code strategy entries for this in pinescript v5. Enter a long when the price closes above the bollinger band, and short when price closes below the the lower bollinger band. Close the long when the short condition is met, and close the short when the long condition is met,” Rekt Fencer shared the ChatGPT prompt.

Fencer pasted the source code below the prompt to instruct ChatGPT to write the logic that automates trade entries and exits.

Fencer also stressed the importance of resolving coding errors, a typical challenge in programming. After pasting the entry and exit logic on TradingView, he also recommended using ChatGPT to diagnose and correct errors efficiently.

He also warned of the risks associated with trading. Fencer advised starting with smaller amounts to evaluate the strategy’s effectiveness before increasing the stakes.

This cautious approach highlights the need for risk management, especially when using automated systems capable of executing trades autonomously.

Users must connect their crypto exchange accounts with TradingView to fully automate the trading process. This integration allows the bot to perform trades directly based on the configured strategy.

Read more: Best Crypto Bots To Automate Trading

Although AI-driven trading bots like Fencer’s offer promising profit opportunities, they demand a thorough understanding of both technology and market principles. As AI technology evolves, its potential to enhance trading strategies grows, equipping traders with sophisticated tools to boost their market performance.

However, successful trading still relies on careful strategy planning and rigorous risk management.

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