万鑫AI策略解析专栏｜如何理解AI选金逻辑？

Core Insights - The article discusses the rising interest in gold as it surpasses $2400, questioning the ability of AI systems to understand and predict gold market dynamics amidst volatility and geopolitical tensions [1] - Wanxin AI reveals its underlying logic for gold investment, emphasizing not just the selection of gold but also the methodology behind it [1] Technical Foundation - Wanxin AI has accumulated over 10 years of futures market data, including various inputs such as K-line trends, ETF fund flows, central bank actions, CFTC positions, news sentiment, and policy events [1] - The platform employs a composite model architecture of "time series Transformer + reinforcement learning (RL)" to quickly adjust strategy weights based on macro disturbances like Federal Reserve rate decisions and inflation expectations [1] - The system treats gold as an asset reflecting macro fluctuations and risk aversion, assessing its "allocation cost-effectiveness" in different market phases based on event impact lags and historical success rates [1] Strategy Structure - Unlike many platforms that offer single-factor predictions, Wanxin AI adheres to a "multi-strategy + multi-cycle" integration design [2] Strategy System - The AI system automatically generates signals, adjusts positions, manages risks, and continuously learns in high-frequency trading to correct errors and reconstruct weights, ensuring adaptability across various market environments [3] Risk Control Design - Wanxin AI emphasizes transparency in trading, having obtained multiple licenses from the Hong Kong Securities and Futures Commission, and supports a T+0 withdrawal mechanism [5] - All signal generation, risk control triggers, and stop-loss paths are logged for third-party audits and regulatory reporting [5] User Engagement - Users receive monthly briefings on AI strategy factors, aimed at making the AI's decision-making process understandable, which is seen as a step towards building financial trust [6] Conclusion - Wanxin AI does not promote speculative trading in gold but aims to leverage AI technology to help users identify optimal entry and exit points, fostering a systematic understanding of risk and rational engagement [7] - The strategy models include trend-following, volatility arbitrage, event-driven, and multi-cycle optimization mechanisms [8] - The focus is on the best-performing strategy combinations and the main driving factors for position building, adjustment, and closure [9] - The founder emphasizes that the value of AI lies in empowerment rather than wealth creation, aiming to transition inclusive finance from storytelling to logical understanding [10]