n8n 自动化美股分析机器人：RSI 与 MACD 指标每小时推送 Slack 摘要

输入：股票代码列表；处理：定时触发 → Alpaca 数据获取 → Python 计算技术指标 → OpenAI 生成分析摘要；输出：Slack 频道/用户收到的分类买卖建议

给谁

需要自动化美股监控并接收 Slack 摘要的 n8n 用户

你会得到

美股交易时段每小时自动获取数据、计算 RSI/MACD、生成买卖信号并以 Slack 消息推送

你需要

n8n · slack

步骤

1. 配置定时触发与市场状态检查

   在 n8n 中添加 Schedule Trigger 节点，设置 Cron 表达式为 `0 30 6-14 * * 1-5`（周一至周五 6:30-14:30 PT 每小时触发）。随后添加 HTTP Request 节点调用 `https://paper-api.alpaca.markets/v2/clock` 检查市场是否开盘，再通过 If 节点判断 `{{ $json.is_open }}`：若为 true 继续执行，若为 false 则进入 NoOp 节点优雅退出。

2. 设置股票代码列表

   添加 Edit Fields (Set) 节点，在 JSON 输出中定义要监控的股票代码。默认列表为：AAPL, MSFT, NVDA, TSLA, AMZN, GOOGL, META, JPM, XOM, UNH, GME。可根据需要修改此列表。

3. 配置 Alpaca 股票数据获取

   添加 HTTP Request 节点，URL 设为 `=https://data.alpaca.markets/v2/stocks/bars`，认证方式选择 httpCustomAuth。查询参数：symbols 引用上一步的 `{{ $json.symbols }}`，timeframe=`1Day`，limit=`1000`，feed=`iex`（避免 SIP 权限错误），start 为 100 天前的日期，end 为当天日期。

4. 添加 Python 技术指标计算节点

   添加 Code 节点，语言选择 Python。该节点接收 Alpaca 返回的 bars 数据，计算 RSI(14) 和 MACD(12,26,9)，并根据阈值生成 Buy/Hold/Sell 信号。输出包含 stocks 列表和供 GPT 使用的 summary JSON 字符串。

   运行提示词 · 来源原文。Interpret Data 节点（n8n-nodes-base.code），language: python

   复制提示词

   import pandas as pd
   import numpy as np
   import json
   
   bars_by_symbol = items[0]['json']['bars']
   stocks = []
   
   for symbol, bars in bars_by_symbol.items():
       closes = [bar['c'] for bar in bars if 'c' in bar]
       if len(closes) < 30:
           continue
   
       df = pd.DataFrame({'close': closes})
   
       # RSI(14)
       delta = df['close'].diff()
       gain = delta.clip(lower=0)
       loss = -delta.clip(upper=0)
       avg_gain = gain.rolling(14).mean()
       avg_loss = loss.rolling(14).mean()
       rs = avg_gain / avg_loss
       df['rsi'] = 100 - (100 / (1 + rs))
   
       # MACD (12,26,9)
       ema12 = df['close'].ewm(span=12, adjust=False).mean()
       ema26 = df['close'].ewm(span=26, adjust=False).mean()
       df['macd'] = ema12 - ema26
       df['signal'] = df['macd'].ewm(span=9, adjust=False).mean()
   
       latest = df.iloc[-1]
       rsi = latest['rsi']
       macd = latest['macd']
       signal = latest['signal']
   
       status = "Hold"
       if rsi < 30 and macd > signal:
           status = "Buy"
       elif rsi > 70 and macd < signal:
           status = "Sell"
   
       stocks.append({
           "ticker": symbol,
           "rsi": round(float(rsi), 2),
           "macd": round(float(macd), 2),
           "signal": round(float(signal), 2),
           "status": status
       })
   
   return [{
       "json": {
           "summary": json.dumps({
               "stocks": stocks
           }, separators=(',', ':')),
         "stocks": stocks
       }
   }]

5. 配置 OpenAI 股票分析助手

   添加 OpenAI 节点，resource 选择 assistant。在 text 字段输入动态内容引用技术指标数据与时间戳。需在 OpenAI 平台预先创建 Assistant，并配置系统提示词使其生成 Slack 友好的 Markdown 格式，将股票分为 Buy Watchlist / Neutral Hold / Caution Sell 三类。

   运行提示词 · 来源原文。Stock Analysis Assistant 节点的 text 字段（OpenAI Assistant 消息输入）

   复制提示词

   =Here is the technical indicator data as JSON:
   
   {{ $json.summary }}
   
   Pulled as of {{ $now }}

   运行提示词 · 来源原文。OpenAI Assistant 系统/指令提示词（在 OpenAI 平台配置 Assistant 时使用；Sticky Note10 记录预期行为）

   复制提示词

   You are a financial assistant writing a quick, readable market update for a general audience. Your job is to help people understand how well-known stocks are behaving — even if they aren’t professional traders.
   
   You’ll be given:
   
   A list of stocks with technical indicators (e.g., momentum data)
   A timestamp (in RFC 3339 or ISO format) for when the data was pulled.
   📌 Your task:
   Group the stocks into three categories:
   🟢 Buy Watchlist – Stocks showing signs of recovery or upward momentum
   ⚪ Neutral Hold – Stocks with steady or unclear direction
   🔴 Caution / Sell – Stocks that appear overbought or may pull back
   For each stock:
   Write a short, plain-language insight about what’s happening
   Use familiar terms like “gaining steam,” “cooling off,” or “showing hesitation”
   Avoid technical jargon like RSI or MACD unless context makes it helpful
   Add a helpful tip or comment for each stock (e.g.,
   “This pattern often signals hesitation” or
   “This dip might attract bargain hunters”)
   Finish with a summary line using the timestamp like this:
   Summary as of October 2, 2025 – Most stocks were stable with one or two worth watching.
   📦 Respond in Slack Markdown Only:
   Example Format:
   
   *📊 Market Summary (as of October 2, 2025)*
   
   🟢 *Buy Watchlist*  
   • TSLA – Recovering after a dip; gaining steam. This type of rebound often attracts early buyers.
   
   ⚪ *Neutral Hold*  
   • AAPL – Holding steady. This often means the market is waiting on new developments.  
   • GOOGL – Moving sideways. A sign of consolidation before potential breakout.  
   • MSFT – Little movement. Could be digesting prior gains.  
   • NVDA – Slight back-and-forth. May indicate indecision in the market.
   
   🔴 *Caution / Sell*  
   • None at this time.
   
   _Summary as of October 2, 2025: Most stocks appear steady. TSLA could be one to watch if momentum holds._
   🚫 Do NOT:
   Return raw JSON
   Use code blocks unless formatting Slack markdown (no YAML or tags)
   Use technical finance language unless simplified

6. 配置 Slack 消息发送

   添加 Slack 节点，select 选择 user 或 channel，在 text 字段填入 `{{ $json.output }}` 以发送 OpenAI 生成的摘要。需提前配置 Slack API 凭证并确保 bot 有对应频道或用户的发消息权限。

7. 保存并激活工作流

   确认工作流时区设置为 America/Los_Angeles，检查所有凭证已正确配置，保存并激活工作流。首次运行建议手动测试以验证 Alpaca 数据获取和 OpenAI 输出格式。

你是一个美股分析工作流搭建助手。用户将提供 n8n 实例访问权限、Alpaca API key、OpenAI API key 和 Slack bot token。请协助按以下顺序完成：1) 配置定时触发与市场状态检查；2) 设置股票代码列表；3) 配置 Alpaca 数据获取节点；4) 添加 Python 技术指标计算；5) 配置 OpenAI Assistant 节点（需预先在 OpenAI 平台创建 Assistant 并粘贴系统提示词）；6) 配置 Slack 发送节点；7) 测试并激活。注意：OpenAI Assistant ID 和 Slack 用户/频道 ID 需要用户自行提供。