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longbridge-behavioral-finance

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English
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Chinese

longbridge-behavioral-finance

longbridge-behavioral-finance

Apply behavioral finance theory to identify exploitable market inefficiencies — map common cognitive biases to measurable price/volume patterns using Longbridge data.
Response language: match the user's input language — Simplified Chinese / Traditional Chinese / English.
应用行为金融理论识别可利用的市场无效性——通过Longbridge数据将常见认知偏差映射为可量化的价格/成交量模式。
回复语言: 匹配用户输入语言——简体中文/繁体中文/英文。

When to use

使用场景

  • "这只股票是不是过度反应了", "did the market overreact to this news", "這隻股票是否過度反應"
  • "动量效应还是反转效应", "momentum or reversal for this sector"
  • "处置效应怎么影响散户行为", "how does disposition effect affect retail traders"
  • "现在市场有没有羊群效应", "is there herding in the market right now"
  • "锚定效应怎么影响股价", "how does anchoring bias affect stock prices"
For quantitative factor testing (IC/IR), use 
longbridge-factor-research
. For market temperature index, use 
longbridge-market-temp
.
  • "这只股票是不是过度反应了", "did the market overreact to this news", "這隻股票是否過度反應"
  • "动量效应还是反转效应", "momentum or reversal for this sector"
  • "处置效应怎么影响散户行为", "how does disposition effect affect retail traders"
  • "现在市场有没有羊群效应", "is there herding in the market right now"
  • "锚定效应怎么影响股价", "how does anchoring bias affect stock prices"
如需进行量化因子测试（IC/IR），请使用
longbridge-factor-research
。如需查看市场温度指数，请使用
longbridge-market-temp
。

Bias catalogue and tradeable signals

偏差目录与可交易信号

1. Overreaction (过度反应)

1. 过度反应

Theory: Investors overweight recent bad/good news, pushing prices beyond fundamental value. De Bondt & Thaler (1985).
Signal: Long-term reversal. Stocks down 30–50% over 12M outperform over the next 12M; top performers underperform.
Detect:
bash
longbridge kline <SYMBOL> --period day --count 252 --format json
Compare 12M return vs peer group. If a stock is in the bottom 10% of sector returns, screen for reversal setup.
理论依据: 投资者过度重视近期利空/利好消息，导致价格偏离基本面价值。（De Bondt & Thaler，1985）
交易信号: 长期反转。过去12个月下跌30%-50%的股票，在未来12个月表现优于市场；过去表现Top的股票则会跑输市场。
检测方法:
bash
longbridge kline <SYMBOL> --period day --count 252 --format json
将股票过去12个月的回报率与同行对比。若某股票在行业回报率中处于后10%，则可筛选为反转布局标的。

2. Underreaction (反应不足)

2. 反应不足

Theory: Investors are slow to update beliefs; price drifts gradually toward fair value after earnings surprises.
Signal: Post-earnings announcement drift (PEAD). Buy after positive earnings surprise; price continues rising for 1–3 months.
Detect: Use 
longbridge-earnings
to identify beats. Track price drift with 
longbridge kline --period day --count 60
.
理论依据: 投资者更新自身认知的速度较慢；财报超预期后，股价会逐渐向合理价值漂移。
交易信号: 财报公告后漂移（PEAD）。在财报正面超预期后买入，股价会在1-3个月内持续上涨。
检测方法: 使用
longbridge-earnings
识别超预期标的。通过
longbridge kline --period day --count 60
跟踪股价漂移情况。

3. Disposition Effect (处置效应)

3. 处置效应

Theory: Investors sell winners too early and hold losers too long (Shefrin & Statman, 1985).
Market impact: Selling pressure on recent winners creates resistance near recent highs; support near cost basis concentrations.
Detect: High capital inflows after a price surge = retail profit-taking.
bash
longbridge capital <SYMBOL> --format json
理论依据: 投资者过早卖出盈利股票，却长期持有亏损股票（Shefrin & Statman，1985）。
市场影响: 近期盈利股票面临抛压，在近期高点附近形成阻力；在成本密集区附近形成支撑。
检测方法: 价格暴涨后资金大幅流入=散户获利了结。
bash
longbridge capital <SYMBOL> --format json

4. Anchoring Bias (锚定效应)

4. 锚定效应

Theory: Investors anchor to arbitrary reference prices (52-week high, IPO price, round numbers).
Signal: 52-week high breakout tends to persist (stocks resist breaking prior highs but accelerate once broken).
Detect: Fetch 52-week high from 
longbridge calc-index <SYMBOL> --format json
or static data.
理论依据: 投资者会锚定任意参考价格（52周高点、IPO价格、整数位）。
交易信号: 突破52周高点的趋势往往会持续（股价在突破前会受阻于前期高点，但突破后会加速上涨）。
检测方法: 通过
longbridge calc-index <SYMBOL> --format json
或静态数据获取52周高点。

5. Herding (羊群效应)

5. 羊群效应

Theory: Investors follow the crowd, amplifying trends beyond fundamentals.
Signal: Abnormal volume + price acceleration without fundamental catalyst = herding. Also: analyst consensus clustering.
Detect:
bash
longbridge market-temp --format json          # Market sentiment index 0-100
longbridge capital <SYMBOL> --format json     # Capital flow concentration
If market temperature > 80 and a single sector dominates capital inflow → herding warning.
理论依据: 投资者跟风操作，导致趋势被放大至超出基本面支撑的程度。
交易信号: 成交量异常+价格加速上涨但无基本面催化=羊群行为。此外，分析师共识高度集中也属于此类信号。
检测方法:
bash
longbridge market-temp --format json          # 市场情绪指数 0-100
longbridge capital <SYMBOL> --format json     # 资金流向集中度
若市场温度>80且单一板块主导资金流入→发出羊群行为预警。

6. Overconfidence (过度自信)

6. 过度自信

Theory: Investors overestimate precision of their forecasts, leading to under-diversification and excess trading.
Market impact: High turnover in bull markets; individual stocks show higher volatility than fundamentals justify.
Detect: Turnover rate spike from 
longbridge quote <SYMBOL> --format json
(turnover_rate field).
理论依据: 投资者高估自身预测的准确性，导致投资组合分散不足、交易过度。
市场影响: 牛市中换手率居高不下；个股波动率高于基本面支撑的合理水平。
检测方法: 通过
longbridge quote <SYMBOL> --format json
中的turnover_rate字段检测换手率飙升情况。

Workflow

工作流程

  1. Identify which bias the user is asking about (or scan all six).
  2. Fetch relevant data (kline / market-temp / capital flow).
  3. Map observed price/volume pattern to the bias.
  4. Quantify signal strength: magnitude, duration, persistence.
  5. Suggest a trading implication (entry / exit / avoid) with explicit caveats.
  1. 识别用户询问的偏差类型（或扫描全部6种偏差）。
  2. 获取相关数据（K线/市场温度/资金流向）。
  3. 将观察到的价格/成交量模式对应到偏差类型。
  4. 量化信号强度：幅度、持续时间、持续性。
  5. 给出交易建议（入场/离场/规避）并明确提示风险。

CLI

命令行工具（CLI）

bash
longbridge kline --help
longbridge market-temp --help
longbridge capital --help

longbridge market-temp --format json
longbridge kline <SYMBOL> --period day --count 60 --format json
longbridge capital <SYMBOL> --format json
bash
longbridge kline --help
longbridge market-temp --help
longbridge capital --help

longbridge market-temp --format json
longbridge kline <SYMBOL> --period day --count 60 --format json
longbridge capital <SYMBOL> --format json

Output

输出内容

Present:
  1. Identified bias and academic basis.
  2. Observable evidence from Longbridge data (specific numbers).
  3. Tradeable implication (signal direction, horizon, conviction).
  4. Risks: when the bias does not persist (e.g. mean-reversion fails in trending markets).
  5. Disclaimer: behavioral signals are probabilistic, not deterministic.
需呈现：
  1. 识别出的偏差类型及学术依据。
  2. 来自Longbridge数据的可观测证据（具体数值）。
  3. 可交易建议（信号方向、时间周期、置信度）。
  4. 风险提示：偏差不持续的情况（如趋势市场中均值回归失效）。
  5. 免责声明：行为信号是概率性的，而非确定性的。

Error handling

错误处理

Situation简体回复繁體回覆English reply
command not found: longbridge
请安装 longbridge-terminal 或检查 MCP 配置。請安裝 longbridge-terminal 或檢查 MCP 配置。Install longbridge-terminal or check MCP config.
stderr: 
not logged in
请运行 
longbridge auth login
。		請執行 
longbridge auth login
。		Run 
longbridge auth login
.
Insufficient price history历史数据不足，无法可靠识别偏差信号，请延长观察期。歷史數據不足，請延長觀察期。Insufficient history to identify bias reliably; extend the lookback.
场景简体回复繁體回覆English reply
command not found: longbridge
请安装 longbridge-terminal 或检查 MCP 配置。請安裝 longbridge-terminal 或檢查 MCP 配置。Install longbridge-terminal or check MCP config.
stderr: 
not logged in
请运行 
longbridge auth login
。		請執行 
longbridge auth login
。		Run 
longbridge auth login
.
Insufficient price history历史数据不足，无法可靠识别偏差信号，请延长观察期。歷史數據不足，請延長觀察期。Insufficient history to identify bias reliably; extend the lookback.

Related skills

相关技能

  • longbridge-market-temp
    — market sentiment temperature index
  • longbridge-capital-flow
    — intraday capital flow and large/small order split
  • longbridge-factor-research
    — quantitative factor IC/IR analysis
  • longbridge-anomaly
    — unusual price/volume movements
  • longbridge-market-temp
    — 市场情绪温度指数
  • longbridge-capital-flow
    — 日内资金流向及大单/小单拆分
  • longbridge-factor-research
    — 量化因子IC/IR分析
  • longbridge-anomaly
    — 异常价格/成交量波动

File layout

文件结构

skills/longbridge-behavioral-finance/
└── SKILL.md
skills/longbridge-behavioral-finance/
└── SKILL.md