This research paper focuses on the integration of Artificial Intelligence (AI) into the currency trading landscape, positing the development of personalized AI models, essentially functioning as intelligent personal assistants tailored to the idiosyncrasies of individual traders. The paper posits that AI models are capable of identifying nuanced patterns within the trader's historical data, facilitating a more accurate and insightful assessment of psychological risk dynamics in currency trading. The PRI is a dynamic metric that experiences fluctuations in response to market conditions that foster psychological fragility among traders. By employing sophisticated techniques, a classifying decision tree is crafted, enabling clearer decision-making boundaries within the tree structure. By incorporating the user's chronological trade entries, the model becomes adept at identifying critical junctures when psychological risks are heightened. The real-time nature of the calculations enhances the model's utility as a proactive tool, offering timely alerts to traders about impending moments of psychological risks. The implications of this research extend beyond the confines of currency trading, reaching into the realms of other industries where the judicious application of personalized modeling emerges as an efficient and strategic approach. This paper positions itself at the intersection of cutting-edge technology and the intricate nuances of human psychology, offering a transformative paradigm for decision making support in dynamic and high-pressure environments.

翻译：本研究聚焦于人工智能在外汇交易领域的集成应用，提出开发个性化人工智能模型——本质上作为适配个体交易者特质的智能个人助理。本文论证了人工智能模型能够识别交易者历史数据中的微妙模式，从而更准确、更深刻地评估外汇交易中的心理风险动态。心理风险指数（PRI）是一个动态指标，会随诱发交易者心理脆弱的市场条件而波动。通过采用复杂技术构建分类决策树，可在树状结构中形成更清晰的决策边界。通过纳入用户按时间顺序的交易记录，该模型能精准识别心理风险加剧的关键节点。计算的实时性增强了模型作为主动预警工具的价值，能及时向交易者发出心理风险临近的警报。本研究的应用价值超越外汇交易范畴，延伸至其他行业——在这些领域中，明智运用个性化建模可成为高效且具有战略意义的方法。本文立于前沿技术与人类心理微妙机制的交汇点，为动态高压环境下的决策支持提供了变革性范式。