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加密貨幣影響者 Rekt Fencer 分享了使用 OpenAI 的 ChatGPT 進行比特幣交易的演算法,引發了對該機器人效能的懷疑。該機器人是使用布林線指標創建的,據稱為 Rekt Fencer 創造了 71,500 美元的利潤。然而,用戶質疑結果的真實性,這表明交易者可能使用了回測數據,而不是實際的即時市場利潤。
Crypto Influencer's Bitcoin Trading Algorithm Raises Doubts Amid Skeptical Scrutiny
加密貨幣影響者的比特幣交易演算法在懷疑的審查中引發質疑
Cryptocurrency influencer Rekt Fencer's recent claim to have created a profitable Bitcoin (BTC) trading algorithm using OpenAI's ChatGPT has sparked a wave of skepticism within the crypto community.
加密貨幣影響者 Rekt Fencer 最近聲稱使用 OpenAI 的 ChatGPT 創建了一種可獲利的比特幣 (BTC) 交易演算法,這在加密社群內引發了一波懷疑。
Trading algorithms are commonly used in financial markets to automate trading decisions based on predefined rules and mathematical models. Rekt Fencer alleges to have developed such an algorithm that reportedly generated $71,500 in profits.
交易演算法通常用於金融市場,根據預先定義的規則和數學模型自動做出交易決策。 Rekt Fencer 聲稱開發了這樣一種演算法,據說創造了 71,500 美元的利潤。
According to Rekt Fencer's Twitter thread on April 25th, the algorithm utilizes the Bollinger Bands Indicator on the TradingView platform. He claims to have built the bot in just 10 minutes using ChatGPT's AI prompts, which were also used to resolve coding errors and technical glitches.
根據 Rekt Fencer 4 月 25 日的 Twitter 帖子,該演算法利用 TradingView 平台上的布林線指標。他聲稱使用 ChatGPT 的人工智慧提示僅用了 10 分鐘就建立了該機器人,該提示也用於解決編碼錯誤和技術故障。
However, many users have expressed doubts about the authenticity of Rekt Fencer's claims. They argue that the alleged profits are the result of backtesting, a simulation process that does not reflect actual market conditions.
不過,不少用戶對Rekt Fencer說法的真實性表示懷疑。他們認為,所謂的利潤是回測的結果,這是一個不反映實際市場狀況的模擬過程。
Backtesting involves testing a trading strategy on historical data, which can provide misleading results compared to real-time trading. Skeptics point out that Rekt Fencer's thread only mentions profits and not losses, a scenario that is highly unlikely in live market trading.
回測涉及根據歷史數據測試交易策略,與即時交易相比,這可能會提供誤導性結果。懷疑論者指出,Rekt Fencer 的貼文只提到了利潤,沒有提到損失,這種情況在即時市場交易中極不可能出現。
Furthermore, critics argue that creating a trading algorithm is a complex process that requires significant technical expertise. They question whether AI bots like ChatGPT are capable of generating effective trading strategies, given their potential limitations in understanding the intricacies of financial markets.
此外,批評者認為創建交易演算法是一個複雜的過程,需要大量的技術專業知識。他們質疑像 ChatGPT 這樣的人工智慧機器人是否能夠產生有效的交易策略,因為它們在理解金融市場的複雜性方面存在潛在的限制。
"Making a trading algo it's complicated and can't be based on a retail indicator," commented GP Crypto Chief, a prominent crypto analyst. "Profit factor of 2.20 in testing is way too low and likely he excluded the settings where fees are not calculated."
著名加密貨幣分析師 GP Crypto Chief 評論道:“制定交易演算法很複雜,而且不能基於零售指標。” “測試中 2.20 的利潤係數太低了,他可能排除了不計算費用的設定。”
The debate surrounding Rekt Fencer's trading algorithm highlights the importance of caution when using automated trading systems, especially those based on unproven AI technology. Users should thoroughly evaluate the credibility of such systems before deploying real capital.
圍繞 Rekt Fencer 交易演算法的爭論凸顯了使用自動交易系統時謹慎的重要性,尤其是那些基於未經驗證的人工智慧技術的交易系統。使用者在部署真實資本之前應徹底評估此類系統的可信度。
It is crucial to note that while AI and machine learning can assist traders in analyzing data and identifying trends, they should not be solely relied upon for making investment decisions. Traders should always exercise due diligence, conduct thorough research, and understand the risks associated with automated trading.
值得注意的是,雖然人工智慧和機器學習可以幫助交易者分析數據和識別趨勢,但不應僅依賴它們來做出投資決策。交易者應始終進行盡職調查,進行徹底的研究,並了解與自動交易相關的風險。
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