investment-simulation

Investment Return Simulation

Available Tools

This skill can call the following MCP data services, selected as needed during the execution process:

Yingmi Financial Data (qieman)

Service address:https://dashscope.aliyuncs.com/api/v1/mcps/Qieman/sse
Core capabilities: fund search/diagnosis, portfolio analysis/backtesting, asset allocation plans, CFP toolchain, chart rendering
Main tools for this skill:MonteCarloSimulate, GetFundsBackTest, AnalyzePortfolioRisk, RenderEchart

Hundsun Juyuan Financial Data (gildata-aidata)

Service address: obtained after activating the Hundsun Juyuan MCP service, in the format https://dashscope.aliyuncs.com/api/v1/mcps/<your-mcp-id>/mcp
Core capabilities: individual stock research (A/H/US), financial statements, capital flows, research report sentiment, wealth management products, macro data
Optional tools for this skill:IndexDailyQuote

Core Principles

Charts first, concise text. The core value of return simulation lies in visualization—probability distributions, three-scenario comparisons, etc. must be presented through RenderEchart generated charts, with text used only for plain-language interpretation.

Input Requirements

Required Information

Investment portfolio or asset allocation plan (fund code + weight or major asset class + weight)
Investment amount

Optional Information

Investment horizon (default: 1 year/3 years/5 years, three tiers)
Regular investment mode (monthly additional amount)
Target return rate

Execution Process

Step 1: Parse the investment plan

Extract asset allocation weights
If fund codes are provided, map them to major asset classes

Step 2: Monte Carlo simulation

Call MonteCarloSimulate pass in the asset weight configuration
Obtain return distributions for different periods (1 year/3 years/5 years)
Extract key quantiles: 5%/25%/50%/75%/95%

Step 3: Supplement with historical backtesting

Call GetFundsBackTest to perform historical backtesting on the portfolio
Call AnalyzePortfolioRisk to obtain portfolio risk indicators
Optional: call IndexDailyQuote(gildata-aidata) to obtain historical market data for benchmark indices, for backtest comparison reference

Step 4: Generate visualization charts (must be executed, cannot be skipped)

Mustsequentially call RenderEchart to generate the following charts:

Chart 1: Three-scenario return comparison bar chart (must be generated)

Use the three-scenario return data for 1 year/3 years/5 years to generate a grouped bar chart. ECharts option reference:

{
  "title": { "text": "预期收益模拟", "left": "center", "subtext": "基于蒙特卡洛模拟" },
  "tooltip": { "trigger": "axis" },
  "legend": { "top": "bottom" },
  "xAxis": { "type": "category", "data": ["1年", "3年", "5年"] },
  "yAxis": { "type": "value", "axisLabel": { "formatter": "{value}%" } },
  "series": [
    { "name": "悲观(25%分位)", "type": "bar", "data": [-5.2, 1.8, 8.5], "itemStyle": { "color": "#ee6666", "borderRadius": [4,4,0,0] } },
    { "name": "中性(50%分位)", "type": "bar", "data": [4.8, 16.2, 30.1], "itemStyle": { "color": "#fac858", "borderRadius": [4,4,0,0] } },
    { "name": "乐观(75%分位)", "type": "bar", "data": [15.3, 35.8, 58.2], "itemStyle": { "color": "#91cc75", "borderRadius": [4,4,0,0] } }
  ]
}

Replace with actual simulation data.

Chart 2: Asset allocation pie chart (must be generated)

Use the input asset allocation weights to generate a pie chart, so clients can intuitively see how the money is allocated. ECharts option reference:

{
  "title": { "text": "投资组合配置", "left": "center" },
  "tooltip": { "trigger": "item", "formatter": "{b}: {d}%" },
  "color": ["#5470c6", "#91cc75", "#fac858", "#ee6666", "#73c0de"],
  "series": [{
    "type": "pie",
    "radius": ["40%", "70%"],
    "center": ["50%", "55%"],
    "itemStyle": { "borderRadius": 8 },
    "label": { "formatter": "{b}\n{d}%" },
    "data": [
      { "name": "权益类", "value": 40 },
      { "name": "固收类", "value": 35 },
      { "name": "现金类", "value": 15 },
      { "name": "另类", "value": 10 }
    ]
  }]
}

Replace with actual allocation data.

Chart 3: Profit/loss probability bar chart (must be generated)

Use the profit probability, probability of annualized >5%, and probability of loss >10% for different horizons to generate a bar chart. ECharts option reference:

{
  "title": { "text": "盈亏概率分析", "left": "center" },
  "tooltip": { "trigger": "axis", "formatter": "{b}<br/>{a}: {c}%" },
  "legend": { "top": "bottom" },
  "xAxis": { "type": "category", "data": ["1年", "3年", "5年"] },
  "yAxis": { "type": "value", "max": 100, "axisLabel": { "formatter": "{value}%" } },
  "series": [
    { "name": "盈利概率", "type": "bar", "data": [62, 78, 89], "itemStyle": { "color": "#91cc75", "borderRadius": [4,4,0,0] } },
    { "name": "年化>5%概率", "type": "bar", "data": [45, 60, 72], "itemStyle": { "color": "#5470c6", "borderRadius": [4,4,0,0] } },
    { "name": "亏损>10%概率", "type": "bar", "data": [15, 8, 3], "itemStyle": { "color": "#ee6666", "borderRadius": [4,4,0,0] } }
  ]
}

Replace with actual probability data.

Output Template

Output according to the following structure,Charts are embedded in the corresponding sections, with plain and concise text：

## 投资收益模拟 | {投资金额}万

### 一、投资方案

{资产配置饼图}

### 二、收益模拟

{三情景收益对比柱状图}

| 投资期限 | 悲观 | 中性 | 乐观 |
|----------|------|------|------|
| 1年 | {X}万({Y}%) | {X}万({Y}%) | {X}万({Y}%) |
| 3年 | {X}万({Y}%) | {X}万({Y}%) | {X}万({Y}%) |
| 5年 | {X}万({Y}%) | {X}万({Y}%) | {X}万({Y}%) |

### 三、盈亏概率

{盈亏概率柱状图}

### 四、历史回测参考
- **年化收益**：{X}%
- **最大回撤**：{X}%
- **夏普比率**：{X}

### 五、通俗解读
> {2-3句客户听得懂的解读，如"投10万持有3年，大概率能赚1-3万，亏损超过1万的概率不到10%"}

---
*模拟基于历史数据和统计模型，不代表实际收益承诺。市场有风险，投资需谨慎。*

Notes

Charts are mandatory: return simulation bar chart, allocation pie chart, and profit/loss probability chart are required items
Not a return promise: repeatedly emphasize "simulation," "probability," and "reference"
Plain interpretation: translate probability data into specific amounts and everyday language that clients can understand
Show the risk side: show not only returns but also the probability of loss
Concise text: keep the full text within 600-1000 words (excluding charts)