Memo di investimento
Trasforma dati di mercato grezzi in note di investimento ad alta convinzione. Analisi approfondita, scenari rialzisti/ribassisti e raccomandazioni chiare con grafici visivi per decisioni informate.
Istruzioni
#### Description
Reject noise trading driven by market herd mentality. Perform comprehensive cleansing and integration of real-time market news, in-depth brokerage research reports, and historical financial data. Through a closed-loop process of "broad search → deep reading → logic internalization," build your own high-conviction investment notes—rather than merely obtaining a stock price number.
#### Core Task
For the **"Target Stock" $material (e.g., NVIDIA)** that the user is focused on. Goal: Collect **"Latest Earnings Analysis"** and **"Industry Analyst Perspectives"** from across the web, conduct deep reading to extract **3-5 key points of contention (Bull vs Bear)**, and ultimately generate a structured **"Investment Decision Memo"** with **visual data charts**.
Confirm the investment target with the user first.
#### Execution Steps
**Step 1: Broad Market Scanning**
- **Objective**: Capture the market's prevailing narratives and sentiment toward the target.
- **Actions**:
- **News Aggregation**: Use the Search tool to crawl high-engagement news about the stock from the past week across the web.
- **Sentiment Screening**: Quickly identify whether market sentiment leans "bullish" or "fearful," and flag the main events driving sentiment fluctuations (e.g., earnings release, new product launch).
**Step 2: Deep Research Report Reading**
- **Objective**: Cut through the noise to obtain institutional-grade analytical logic.
- **Actions**:
- **Material Acquisition**: Collect 3-5 in-depth long-form analyses or PDF research reports from across the web, and Save them as Materials.
- **Core Extraction**: AI conducts deep reading of these materials, distilling "earnings forecasts," "risk warnings," and "unique perspectives that differ from consensus."
- **Logic Alignment**: Compare contradictions between different research reports (e.g., Firm A is bullish due to AI demand; Firm B is bearish due to capacity bottlenecks).
**Step 3: Investment Note Generation (Thesis Synthesis)**
- **Objective**: Transform external information into personal investment decision criteria.
- **Output**:
- **Key Thesis Table**: List the Top 3 reasons for the current market's bull and bear cases.
- **Key Metrics Tracking**: Flag the KPIs most critical to monitor next quarter (e.g., data center revenue growth rate).
- **Decision Recommendation**: Based on the above analysis, generate a logic-driven document with "Buy/Hold/Watch" recommendations.
then create a visual data webpage for data presentation.
Memo di investimento
Trasforma dati di mercato grezzi in note di investimento ad alta convinzione. Analisi approfondita, scenari rialzisti/ribassisti e raccomandazioni chiare con grafici visivi per decisioni informate.
Istruzioni
#### Description
Reject noise trading driven by market herd mentality. Perform comprehensive cleansing and integration of real-time market news, in-depth brokerage research reports, and historical financial data. Through a closed-loop process of "broad search → deep reading → logic internalization," build your own high-conviction investment notes—rather than merely obtaining a stock price number.
#### Core Task
For the **"Target Stock" $material (e.g., NVIDIA)** that the user is focused on. Goal: Collect **"Latest Earnings Analysis"** and **"Industry Analyst Perspectives"** from across the web, conduct deep reading to extract **3-5 key points of contention (Bull vs Bear)**, and ultimately generate a structured **"Investment Decision Memo"** with **visual data charts**.
Confirm the investment target with the user first.
#### Execution Steps
**Step 1: Broad Market Scanning**
- **Objective**: Capture the market's prevailing narratives and sentiment toward the target.
- **Actions**:
- **News Aggregation**: Use the Search tool to crawl high-engagement news about the stock from the past week across the web.
- **Sentiment Screening**: Quickly identify whether market sentiment leans "bullish" or "fearful," and flag the main events driving sentiment fluctuations (e.g., earnings release, new product launch).
**Step 2: Deep Research Report Reading**
- **Objective**: Cut through the noise to obtain institutional-grade analytical logic.
- **Actions**:
- **Material Acquisition**: Collect 3-5 in-depth long-form analyses or PDF research reports from across the web, and Save them as Materials.
- **Core Extraction**: AI conducts deep reading of these materials, distilling "earnings forecasts," "risk warnings," and "unique perspectives that differ from consensus."
- **Logic Alignment**: Compare contradictions between different research reports (e.g., Firm A is bullish due to AI demand; Firm B is bearish due to capacity bottlenecks).
**Step 3: Investment Note Generation (Thesis Synthesis)**
- **Objective**: Transform external information into personal investment decision criteria.
- **Output**:
- **Key Thesis Table**: List the Top 3 reasons for the current market's bull and bear cases.
- **Key Metrics Tracking**: Flag the KPIs most critical to monitor next quarter (e.g., data center revenue growth rate).
- **Decision Recommendation**: Based on the above analysis, generate a logic-driven document with "Buy/Hold/Watch" recommendations.
then create a visual data webpage for data presentation.
