构建一个系统来追踪市场叙事和行为信号
1 分•作者: mindquantai•5 个月前
我一直在思考新的市场叙事是如何形成的。
不是那些众所周知、人人都谈论的，而是早期阶段——当一个主题或股票代码悄无声息地开始在讨论中越来越多地出现，然后才成为主流。
大多数交易工具都侧重于价格、指标或信号。
但市场往往是因为关注度和叙事首先建立起来才开始变动。
因此，我一直在尝试一个小系统，试图跟踪类似以下的内容：
* 股票代码提及的突然增加
* 有多少独特的参与者在讨论一个主题
* 讨论是否持续存在于多个时间窗口
* 围绕一个叙事的关注度增长有多快
目标不是生成买入/卖出信号，而是了解市场关注度如何随时间演变。
最近，我还一直在探索一些想法，例如：
* 叙事阶段（出现 → 扩张 → 峰值 → 衰退）
* 跨社区的关注度持久性
* 关注度的转变是否往往先于价格变动
这个项目目前是一个不断发展的研究工具，我们称之为 MindQuant AI。
我们的想法是，用于理解市场的工具可能不应该是静态的——因为市场中的叙事和行为在不断变化。
所以我很好奇其他人对此的看法。
如果你正在构建一个市场情报系统，你希望它跟踪哪些信号？
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I’ve been thinking a lot about how new market narratives form.<p>Not the obvious ones everyone already talks about, but the early stage - when a theme or ticker quietly starts appearing more and more in discussions before it becomes mainstream.<p>Most trading tools focus on price, indicators, or signals.
But markets often move because attention and narratives build first.<p>So I’ve been experimenting with a small system that tries to track things like:
• sudden increases in ticker mentions
• how many unique participants are discussing a theme
• whether discussions persist across multiple time windows
• how quickly attention around a narrative grows<p>The goal isn’t to generate buy/sell signals, but to understand how market attention evolves over time.<p>Recently I’ve also been exploring ideas like:
• narrative phases (emerging → expanding → peak → fading)
• attention persistence across communities
• whether shifts in attention tend to precede price movement<p>This project is currently an evolving research tool we call MindQuant AI.<p>The idea is that tools for understanding markets probably shouldn’t be static - because narratives and behavior in markets constantly change.<p>So I’m curious how others think about this.<p>If you were building a market intelligence system, what signals would you want it to track?