Back to Details

stock-price-change

Compare original and translation side by side

🇺🇸

Original

English
🇨🇳

Translation

Chinese

Stock Price Change

股价变化

Retrieve comprehensive price change statistics across multiple time periods using the Octagon MCP server.
使用Octagon MCP服务器获取多个时间段内的全面股价变化统计数据。

Prerequisites

前提条件

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.
确保你的AI Agent（Cursor、Claude Desktop、Windsurf等）中已配置Octagon MCP。安装说明请参阅references/mcp-setup.md。

Workflow

操作流程

1. Identify the Stock

1. 确定目标股票

Determine the ticker symbol for the company you want to analyze (e.g., AAPL, MSFT, GOOGL).
确定你要分析的公司股票代码（例如：AAPL、MSFT、GOOGL）。

2. Execute Query via Octagon MCP

2. 通过Octagon MCP执行查询

Use the 
octagon-agent
tool with a natural language prompt:
Get stock price change statistics for the symbol <TICKER>.
MCP Call Format:
json
{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Get stock price change statistics for the symbol AAPL."
  }
}
使用
octagon-agent
工具，配合自然语言提示词：
Get stock price change statistics for the symbol <TICKER>.
MCP调用格式：
json
{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Get stock price change statistics for the symbol AAPL."
  }
}

3. Expected Output

3. 预期输出

The agent returns price change data across multiple timeframes:
Time PeriodPercentage Change
1 Day4.06%
5 Days4.80%
1 Month-0.37%
3 Months-0.13%
6 Months33.42%
Year-to-Date (YTD)-0.37%
1 Year18.42%
3 Years79.03%
5 Years100.02%
10 Years1,043.14%
All-Time High210,270.08%
Key Insight: Strong long-term growth with 10-year return of 1,043.14%, but recent short-term performance slightly negative.
Data Sources: octagon-stock-data-agent
Agent会返回多个时间段的股价变化数据：
时间段涨跌幅
1天4.06%
5天4.80%
1个月-0.37%
3个月-0.13%
6个月33.42%
年初至今（YTD）-0.37%
1年18.42%
3年79.03%
5年100.02%
10年1,043.14%
历史最高210,270.08%
关键洞察：长期增长强劲，10年回报率达1,043.14%，但近期短期表现略有下滑。
数据来源：octagon-stock-data-agent

4. Interpret Results

4. 结果解读

See references/interpreting-results.md for guidance on:
  • Evaluating short-term vs. long-term performance
  • Understanding momentum signals
  • Comparing to benchmarks
  • Assessing trend consistency
有关以下内容的指导，请参阅references/interpreting-results.md：
  • 评估短期与长期表现
  • 理解动量信号
  • 与基准对比
  • 评估趋势一致性

Example Queries

示例查询

Basic Query:
Get stock price change statistics for the symbol AAPL.
Multiple Stocks:
Compare price change statistics for AAPL, MSFT, and GOOGL.
Specific Focus:
What is the 1-year and 5-year return for TSLA?
YTD Performance:
What is the year-to-date performance of NVDA?
Long-Term Growth:
What is the 10-year cumulative return for AMZN?
基础查询：
Get stock price change statistics for the symbol AAPL.
多股票对比：
Compare price change statistics for AAPL, MSFT, and GOOGL.
特定聚焦：
What is the 1-year and 5-year return for TSLA?
年初至今表现：
What is the year-to-date performance of NVDA?
长期增长：
What is the 10-year cumulative return for AMZN?

Understanding Time Periods

时间段说明

Short-Term Periods

短期时间段

PeriodUse Case
1 DayDaily momentum
5 DaysWeekly trend
1 MonthRecent performance
3 MonthsQuarterly trend
时间段适用场景
1天日内动量
5天周度趋势
1个月近期表现
3个月季度趋势

Medium-Term Periods

中期时间段

PeriodUse Case
6 MonthsHalf-year momentum
YTDCalendar year performance
1 YearAnnual return
时间段适用场景
6个月半年度动量
YTD自然年表现
1年年度回报

Long-Term Periods

长期时间段

PeriodUse Case
3 YearsBusiness cycle
5 YearsMarket cycle
10 YearsSecular trend
All-TimeTotal return since inception
时间段适用场景
3年商业周期
5年市场周期
10年长期趋势
历史全部自上市以来总回报

Return Interpretation

回报解读

Performance Classification

表现分类

Return (1 Year)Classification
>50%Exceptional
25-50%Very strong
10-25%Strong
0-10%Moderate
-10 to 0%Weak
<-10%Poor
1年回报率分类
>50%卓越
25-50%非常强劲
10-25%强劲
0-10%温和
-10至0%疲软
<-10%糟糕

Long-Term Standards

长期标准

Return (10 Year)Classification
>500%Exceptional
200-500%Very strong
100-200%Strong
50-100%Moderate
0-50%Below average
<0%Poor
10年回报率分类
>500%卓越
200-500%非常强劲
100-200%强劲
50-100%温和
0-50%低于平均
<0%糟糕

Momentum Analysis

动量分析

Trend Consistency

趋势一致性

PatternInterpretation
All periods positiveStrong consistent uptrend
Short negative, long positivePullback in uptrend
Short positive, long negativeBounce in downtrend
All periods negativeConsistent downtrend
模式解读
所有时间段均为正强劲且持续的上涨趋势
短期为负、长期为正上涨趋势中的回调
短期为正、长期为负下跌趋势中的反弹
所有时间段均为负持续的下跌趋势

Momentum Signals

动量信号

SignalPattern
AcceleratingReturns increasing across periods
DeceleratingReturns decreasing across periods
StableConsistent returns across periods
ReversalSign change between periods
信号模式
加速各时间段回报率递增
减速各时间段回报率递减
稳定各时间段回报率一致
反转时间段间回报率正负转换

Example Analysis

示例分析

From AAPL data:
  • 1 Day: +4.06% (strong daily)
  • 1 Month: -0.37% (slight pullback)
  • 1 Year: +18.42% (solid annual)
  • 10 Year: +1,043.14% (exceptional long-term)
Interpretation: Long-term compounder with recent consolidation.
从AAPL数据来看：
  • 1天：+4.06%（强劲日内表现）
  • 1个月：-0.37%（小幅回调）
  • 1年：+18.42%（稳健年度表现）
  • 10年：+1,043.14%（卓越长期表现）
解读：长期复利增长标的，近期处于盘整阶段。

Annualized Returns

年化回报率

Calculation

计算公式

Annualized Return = (1 + Total Return)^(1/Years) - 1
年化回报率 = (1 + 总回报率)^(1/年数) - 1

Example

示例

From AAPL data:
  • 10-Year Return: 1,043.14%
  • Annualized: (1 + 10.4314)^(1/10) - 1 = 27.3% per year
根据AAPL数据：
  • 10年总回报率：1,043.14%
  • 年化回报率：(1 + 10.4314)^(1/10) - 1 = 年化27.3%

Annualized Benchmarks

年化基准

Annual ReturnRating
>25%Exceptional
15-25%Very strong
10-15%Strong
7-10%Market-like
<7%Below market
年化回报率评级
>25%卓越
15-25%非常强劲
10-15%强劲
7-10%市场水平
<7%低于市场

Comparison Analysis

对比分析

vs. Benchmarks

与基准对比

BenchmarkWhat to Compare
S&P 500Market performance
Sector ETFIndustry performance
PeersCompetitive position
基准对比维度
S&P 500市场整体表现
行业ETF行业表现
同行公司竞争地位

Alpha Calculation

Alpha值计算

Alpha = Stock Return - Benchmark Return
Alpha = 个股回报率 - 基准回报率

Example

示例

If AAPL 1-year return is +18.42% and S&P 500 is +10%:
  • Alpha: +8.42% outperformance
若AAPL 1年回报率为+18.42%，S&P 500为+10%：
  • Alpha值：+8.42%（跑赢基准）

Time Period Relationships

时间段关系

Healthy Patterns

健康模式

PatternInterpretation
Long > ShortHealthy uptrend
Positive all periodsConsistent strength
Improving short-termMomentum building
模式解读
长期回报率 > 短期健康上涨趋势
所有时间段均为正持续强劲
短期表现改善动量积累

Warning Patterns

警示模式

PatternInterpretation
Long << ShortMean reversion risk
Long > 0, Short < 0Trend weakening
All negativeFundamental issues
模式解读
长期回报率 << 短期均值回归风险
长期正、短期负趋势走弱
所有时间段均为负基本面问题

All-Time High Analysis

历史最高位分析

Distance from ATH

与历史最高位的差距

Distance = (ATH - Current) / ATH × 100%
差距 = (历史最高位 - 当前价格) / 历史最高位 × 100%

ATH Context

历史最高位语境

PositionInterpretation
At ATHMaximum strength
0-10% belowNear highs
10-20% belowCorrection
20-40% belowBear market
>40% belowSevere decline
位置解读
处于历史最高位最强表现
低于历史最高0-10%接近高位
低于历史最高10-20%回调阶段
低于历史最高20-40%熊市阶段
低于历史最高>40%大幅下跌

Common Use Cases

常见使用场景

Performance Summary

表现汇总

What are the returns for AAPL across all time periods?
What are the returns for AAPL across all time periods?

Trend Analysis

趋势分析

Is MSFT in an uptrend or downtrend based on recent returns?
Is MSFT in an uptrend or downtrend based on recent returns?

Long-Term Growth

长期增长

What is the 10-year cumulative return for the FAANG stocks?
What is the 10-year cumulative return for the FAANG stocks?

Momentum Check

动量检查

Is NVDA showing positive momentum in the short-term?
Is NVDA showing positive momentum in the short-term?

Comparison

对比分析

Compare 1-year returns for major tech stocks.
Compare 1-year returns for major tech stocks.

Analysis Tips

分析技巧

  1. Don't rely on one period: Use multiple timeframes.
  2. Compare to benchmarks: Returns mean more in context.
  3. Consider consistency: Smooth vs. volatile returns.
  4. Annualize long-term: For fair comparison.
  5. Watch for divergence: Short vs. long-term signals.
  6. Factor in dividends: Total return vs. price return.
  1. 不要依赖单一时间段：使用多个时间段综合分析。
  2. 与基准对比：结合语境的回报率更具意义。
  3. 考虑一致性：平稳回报 vs 波动回报。
  4. 长期回报年化：确保公平对比。
  5. 关注背离信号：短期与长期信号的分歧。
  6. 考虑股息因素：总回报 vs 价格回报。

Integration with Other Skills

与其他技能集成

SkillCombined Use
stock-quoteCurrent price context
stock-performanceDaily price data
stock-historical-indexvs. market returns
financial-metrics-analysisFundamentals behind returns
技能组合用途
stock-quote当前价格语境补充
stock-performance日度价格数据
stock-historical-index与市场回报对比
financial-metrics-analysis回报背后的基本面分析