Interview with Bitget Managing Director Gracy Chen: What Are the Advantages and Limitations of CTA AI Trading Bots?
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Interview with Bitget Managing Director Gracy Chen: What Are the Advantages and Limitations of CTA AI Trading Bots?
What are the differences between CTA AI strategies and traditional commodity trading algorithms?
Navigating Web3 tides with focused insightsBy: Zhiyuan Sun
Gracy Chen, Managing Director at Bitget, detailed the advantages and limitations of the CTA AI strategy in an interview with Cointelegraph, the third in a series of AI trading initiatives launched this year. One area where artificial intelligence (AI) technology is rapidly converging with blockchain is cryptocurrency exchanges. Since the beginning of the year, Binance has introduced an AI-powered non-fungible token (NFT) generator for verified users. Meanwhile, OKX launched an AI integration to monitor market volatility. Bybit has also integrated ChatGPT into its AI-driven trading tools.
On the other hand, cryptocurrency exchange Bitget began rolling out a series of AI trading bots starting in June. On July 27, the exchange launched a new Commodity Trading Advisor (CTA) AI bot. In an interview with Cointelegraph, Bitget's Managing Director Gracy Chen elaborated on its benefits and risk factors.
Cointelegraph (CT): How does the CTA AI strategy differ from ordinary commodity trading algorithms?
Gracy Chen (GC): The AI bot incorporates strategies based on MACD (Moving Average Convergence Divergence) and Bollinger Bands indicators. It continuously receives historical strategy data, analyzes and processes it, and achieves self-learning to generate new strategic logic. As a result, the AI strategy eliminates the need to manually input complex parameters as required in traditional algorithms, helping users intuitively select and create strategies using only simple return figures and price charts.
CT: While AI models perform well under normal conditions, they often become unstable during sudden events such as sharp price surges or drops. Are there any safeguards in place for users in such cases?
GC: This is undoubtedly a major challenge for any trading platform. Particularly, the biggest impact on CTA AI strategy returns comes from receiving numerous false signals during operations, which could lead to potential losses. That said, we protect users' interests in two ways: First, our AI strategies are based on large K-line timeframes (minimum candlestick period of one hour) when calculating indicators. Thus, many short-term anomalies are smoothed out over longer periods, effectively reducing the impact of false signals. Second, we provide users with take-profit and stop-loss options in advanced settings, which can automatically help secure profits and limit losses, protecting account equity.
CT: Given that CTA strategies are primarily used for exchange-traded commodities like soybeans or crude oil, how is this strategy particularly applicable to cryptocurrencies?
GC: In principle, CTA strategies capitalize on market volatility by analyzing the relationship between volume and price. They are more effective in highly volatile markets—such as the cryptocurrency market. Due to cutting-edge technologies, rapid advancements, and diverse global participants, coins and tokens are more prone to significant price swings.
CT: In previous discussions, you mentioned that multiple departments at Bitget are experimenting with AI; could you give a specific example?
GC: We use AI technology to train, analyze, and process samples based on individual users’ trading behaviors, providing intelligent content recommendations tailored to different user groups. Additionally, we are using AI to automate manual tasks such as generating posters, writing copy, and coding simple scripts.
CT: What advantages do AI-based trading methods offer compared to human or algorithmic trading approaches?
GC: AI strategies help users intuitively choose and create trading strategies through simple return figures and price charts, eliminating the need to configure complex parameters as required in algorithmic trading.
Chen also explained that Bitget will draw lessons from the success of large language models (LLMs) like ChatGPT to improve its AI bots. "We recognize that ChatGPT’s success largely stems from two aspects: massive sample data and intelligent learning models. Our AI strategies will build upon these two foundations to enhance profitability," she said.
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