<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>慧鑫量化</title><description>专注于 AI 与量化交易的实战分享</description><link>https://hxquant.top/</link><language>zh-cn</language><item><title>RSI 深度实战：传统信号与 AI 增强结合</title><link>https://hxquant.top/posts/rsi-ai-strategy/</link><guid isPermaLink="true">https://hxquant.top/posts/rsi-ai-strategy/</guid><description>用 scikit-learn 给 RSI 加一层 AI 假信号过滤，胜率从 48% 提升到 62%。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>RSI</category><category>AI</category><category>假信号过滤</category><category>Python</category><category>机器学习</category><author>慧鑫量化</author></item><item><title>KDJ 实战技巧：随机指标与 AI 增强结合</title><link>https://hxquant.top/posts/kdj-ai-strategy/</link><guid isPermaLink="true">https://hxquant.top/posts/kdj-ai-strategy/</guid><description>KDJ 是好指标但噪音大，用 AI 二次确认后假信号减少 40%。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>KDJ</category><category>随机指标</category><category>AI</category><category>Python</category><category>信号增强</category><author>慧鑫量化</author></item><item><title>MACD 趋势跟踪：经典交叉与 AI 反转预测</title><link>https://hxquant.top/posts/macd-ai-prediction/</link><guid isPermaLink="true">https://hxquant.top/posts/macd-ai-prediction/</guid><description>用 LSTM 提前 3 天预测 MACD 反转，准确率 67%，比死叉后入场多赚 18%。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>MACD</category><category>LSTM</category><category>AI预测</category><category>Python</category><category>趋势跟踪</category><author>慧鑫量化</author></item><item><title>三指标共振实战：RSI/KDJ/MACD 联合 ML 决策</title><link>https://hxquant.top/posts/three-indicators-ml/</link><guid isPermaLink="true">https://hxquant.top/posts/three-indicators-ml/</guid><description>RSI+KDJ+MACD 三指标联合 XGBoost，决策准确率从单指标 55% 提升到 71%。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>RSI</category><category>KDJ</category><category>MACD</category><category>多指标</category><category>XGBoost</category><category>机器学习</category><author>慧鑫量化</author></item><item><title>指标参数自适应：让 RSI/KDJ/MACD 跟着市场状态变</title><link>https://hxquant.top/posts/adaptive-indicator-params/</link><guid isPermaLink="true">https://hxquant.top/posts/adaptive-indicator-params/</guid><description>固定 RSI(14) 在牛熊市差距巨大，用 HMM 识别市场状态+动态参数，夏普从 0.8 提升到 1.6。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>参数优化</category><category>自适应</category><category>HMM</category><category>强化学习</category><category>量化策略</category><author>慧鑫量化</author></item><item><title>上升趋势识别：经典画法与 AI 自动检测</title><link>https://hxquant.top/posts/uptrend-detection/</link><guid isPermaLink="true">https://hxquant.top/posts/uptrend-detection/</guid><description>把人工画趋势线变成 AI 自动识别，识别速度从 5 分钟缩短到 0.01 秒。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>趋势识别</category><category>上升趋势</category><category>LSTM</category><category>Python</category><category>技术分析</category><author>慧鑫量化</author></item><item><title>震荡行情策略：区间识别与 AI 增强高抛低吸</title><link>https://hxquant.top/posts/sideways-strategy-ai/</link><guid isPermaLink="true">https://hxquant.top/posts/sideways-strategy-ai/</guid><description>震荡市用 AI 动态找阻力支撑，胜率从 51% 提升到 64%，盈亏比 1.8。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>震荡市</category><category>区间交易</category><category>布林带</category><category>聚类</category><category>AI</category><author>慧鑫量化</author></item><item><title>下跌趋势风控：识别与 AI 动态止损</title><link>https://hxquant.top/posts/downtrend-risk-ai/</link><guid isPermaLink="true">https://hxquant.top/posts/downtrend-risk-ai/</guid><description>用 AI 动态止损替代固定 8%，熊市最大回撤从 28% 降到 17%。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>下跌趋势</category><category>止损</category><category>XGBoost</category><category>风控</category><category>Python</category><author>慧鑫量化</author></item><item><title>V 字翻转：形态识别与 AI 抢反弹</title><link>https://hxquant.top/posts/v-reversal-ai/</link><guid isPermaLink="true">https://hxquant.top/posts/v-reversal-ai/</guid><description>用 AI 在 V 反底部提前 2 天识别信号，2020 年 3 月美股熔断实战抢反弹收益 23%。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>V反</category><category>形态识别</category><category>抢反弹</category><category>XGBoost</category><category>量化策略</category><author>慧鑫量化</author></item><item><title>头肩底形态：识别与 AI 突破确认</title><link>https://hxquant.top/posts/head-shoulders-bottom-ai/</link><guid isPermaLink="true">https://hxquant.top/posts/head-shoulders-bottom-ai/</guid><description>头肩底是 A 股最赚钱的底部形态，AI 确认后胜率 73%，平均涨幅 18%。</description><pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>头肩底</category><category>形态识别</category><category>突破确认</category><category>XGBoost</category><category>Python</category><author>慧鑫量化</author></item><item><title>本地部署大模型的几种方案对比</title><link>https://hxquant.top/posts/local-llm-deployment/</link><guid isPermaLink="true">https://hxquant.top/posts/local-llm-deployment/</guid><description>从 Ollama、LM Studio 到 vLLM，主流本地 LLM 部署工具的对比与实战建议。</description><pubDate>Fri, 26 Jun 2026 00:00:00 GMT</pubDate><category>AI大模型</category><category>LLM</category><category>Ollama</category><category>vLLM</category><author>慧鑫量化</author></item><item><title>量化交易入门：从一个简单的均线策略说起</title><link>https://hxquant.top/posts/quant-intro/</link><guid isPermaLink="true">https://hxquant.top/posts/quant-intro/</guid><description>用 Python 实现一个 5 日/20 日均线交叉策略，聊聊量化交易的基本流程。</description><pubDate>Fri, 26 Jun 2026 00:00:00 GMT</pubDate><category>量化交易</category><category>Python</category><category>均线</category><category>策略</category><category>入门</category><author>慧鑫量化</author></item><item><title>欢迎来到慧鑫量化</title><link>https://hxquant.top/posts/welcome/</link><guid isPermaLink="true">https://hxquant.top/posts/welcome/</guid><description>这是网站的第一篇文章，介绍网站定位和我们关注的方向。</description><pubDate>Fri, 26 Jun 2026 00:00:00 GMT</pubDate><category>关于</category><category>介绍</category><category>博客</category><author>慧鑫量化</author></item></channel></rss>