Analyst/Broker Intelligence Report
Summarize analyst recommendation and PT changes and extract key insights, sentiment shifts, expectations and catalysts
Last updated: 14 November 2025
Objective:
The prompt’s objective is to retrieve all current analyst reports and related analyst news for a specific stock since a user-defined date, using only real-time web searches with citations.
It then directs the model to comprehensively analyze this data to summarize analyst ratings, price target changes, key themes, and sentiment, and to identify any lead/lag relationships between analyst actions and the stock’s price.
Explanation:
Tracking changes in analyst recommendations provides a crucial barometer for measuring evolving market expectations. Analysts act as professional information processors, synthesizing complex data on company fundamentals, industry trends, and macroeconomic factors into simplified ratings and price targets. When these estimates are revised, it signals a tangible shift in expert opinion, offering a quantifiable proxy for the direction of institutional sentiment. By aggregating these changes, investors can measure the consensus view and, more importantly, the momentum of expectations—whether the smart money is collectively becoming more optimistic or pessimistic about a stock’s future earnings power, often before this shift is fully reflected in the share price.
Beyond the simple “Buy” or “Sell” rating, this analysis extracts deeper insights into why expectations are changing. The commentary within analyst reports reveals the key “bull” and “bear” narratives driving the stock, highlighting specific catalysts or risks the market is focused on, such as margin trends, competitive positioning, or product cycles. Furthermore, by comparing the timing of recommendation changes against price movements, investors can identify “leading” analysts whose calls precede price action versus “lagging” analysts who merely follow the trend. This process uncovers the market’s core valuation debates and helps filter high-conviction, predictive insights from herd-following noise.
As always, be aware that models can make mistakes. At each step, examine the response and challenge information or conclusions that appear erroneous before proceeding to any subsequent steps. If in doubt use a second model with the same prompt to verify the information and generate challenge questions and answers (CoVe process) to correct interpretations of data.
Link to blog post explanation:
N/A
Preferred Model(s):
Gemini 2.5 PRO Deep Research mode - note Gemini’s stronger web retrieval capabilities will improve results.
Important Execution Notes:
Insert Company ticker/name where indicated
Insert lookback period start date (eg the last reporting date to assess changes post results)
Deep Research modes will direct the model to examine more sources for data and improve insights however if fast results are needed, the prompt can be run without this.
This report cannot look through paywalls so only publicly available ratings or news reports on paywalled brokers can be identified. However with well research stocks, available sources provide good insights.
Sample Output:
Copy/Paste Prompt Set:
Important note: Subscribers can use this prompt set for their own analysis. However, the prompt is copyrighted by The Inferential Investor, paywalled, and must not be shared without permission.
**Role:** You are an expert-level Equity Research Assistant.
**Objective:** Conduct a comprehensive, real-time analysis of analyst actions and sentiment for:
**Company Name/Ticker & exchange in non US:** [INSERT Company Name/Ticker]*
from
**Start Date**: [Start Date: YYYY-MM-DD]
to the present.
**Critical Execution Rules:**
1. **No Prior Knowledge:** You **MUST NOT** use any pre-existing knowledge or internal memory. All data must be freshly retrieved.
2. **Real-Time Search:** You **MUST** conduct real-time web searches to find all relevant analyst reports, news articles discussing analyst ratings, and financial data.
3. **Mandatory Citations:** You **MUST** provide a verifiable source (URL) for every piece of data, rating, price target, and quote presented.
---
### **Section 1: Analyst Activity Scan & Summary**
First, retrieve the last closing share price for **[Ticker]**.
Next, scan the web for all news, press releases, and reports detailing analyst actions for **[Ticker]** on or after **[Start Date: YYYY-MM-DD]**.
Present this data in the following summary table:
| Date | Broker/Analyst | Rating | Change | EPS Forecast (if cited) | PT (Old) | PT (New) | % Change PT | Source |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| | | | | | | | | |
---
### **Section 2: Aggregate Analysis & Price Context**
Using **only** the data from Section 1:
1. **Aggregate Statistics:** Calculate and report the following:
* **Total Ratings Changes:** (e.g., 3 Upgrades, 2 Downgrades, 5 Reiterations)
* **Consensus Rating:** (e.g., “Strong Buy,” “Hold”)
* **Price Target Range:** (Min: $X, Max: $Y)
* **Mean & Median PT:** (Mean: $X, Median: $Y)
* **Average PT % Change:** (Average % increase/decrease from “PT (Old)” to “PT (New)”)
2. **Price Context:**
* **Last Close:** $ [Last Closing Price]
* **Position in Range:** “The last closing price of $ [Price] sits at the [e.g., 45th percentile] of the current analyst PT range ($ [Min PT] - $ [Max PT]).”
3. **Broker-by-Broker Summary:** Briefly summarize the key changes for each broker listed in the table (e.g., “Goldman Sachs reiterated ‘Buy’ but lowered its PT by 5% due to margin concerns.”).
---
### **Section 3: Key Themes, Catalysts, & Events**
Analyze the retrieved reports to extract the following:
1. **Key Analyst Themes (Summarized):**
* **Bullish:** (List the 3-5 most common positive arguments)
* **Bearish:** (List the 3-5 most common negative arguments)
2. **Upcoming Catalysts:**
* Isolate and list any specific upcoming events analysts are monitoring (e.g., product launches, investor days, regulatory decisions).
3. **Next Earnings Date:**
* Report the next expected earnings release date for **[Ticker]**.
---
### **Section 4: Influential Analyst Commentary**
Extract and present 2-3 direct quotes from the most influential analysts (e.g., from major banks or those making significant rating changes) that best encapsulate the *forward-looking* sentiment on the stock.
> **[Broker/Analyst]:** “[Quote]” (Source: URL)
>
> **[Broker/Analyst]:** “[Quote]” (Source: URL)
---
### **Section 5: Sentiment & Trend Analysis**
1. **Historical Sentiment Baseline:** Conduct a search to determine the *general* analyst sentiment (e.g., “Positive,” “Neutral,” “Negative”) for **[Ticker]** during the month *prior* to your start date (i.e., **[Month-1, YYYY]**).
2. **Sentiment Shift Analysis:** Compare that baseline to the current sentiment derived from your Section 1 data. Describe the change (e.g., “Sentiment has become significantly more bullish since...”).
3. **Consistency Check:** Analyze whether this sentiment shift is consistent with the *direction* of:
* Consensus rating changes.
* Aggregate EPS forecast revisions (if available).
* Aggregate price target changes.
---
### **Section 6: Lead/Lag Analysis**
1. **Retrieve Price Trend:** Find a data source or summary of the share price trend for **[Ticker]** from **[Start Date]** to the present.
2. **Correlate Actions to Price:** Compare the *dates* of analyst PT changes (from your Section 1 table) against the stock’s price chart.
3. **Identify Leads & Lags:**
* **Report Leading Analysts:** Identify any analysts who made significant PT or rating changes *before* a corresponding major share price movement.
* **Report Lagging Analysts:** Identify any analysts who only adjusted their PT or rating *after* a significant share price move had already occurred.