{"id":63114,"date":"2025-04-30T12:45:42","date_gmt":"2025-04-30T12:45:42","guid":{"rendered":"https:\/\/mycryptomania.com\/?p=63114"},"modified":"2025-04-30T12:45:42","modified_gmt":"2025-04-30T12:45:42","slug":"generate-a-watchlist-from-fmps-gainers-losers-api-using-a-gpt-prompt","status":"publish","type":"post","link":"https:\/\/mycryptomania.com\/?p=63114","title":{"rendered":"Generate a Watchlist from FMP\u2019s Gainers & Losers API Using a GPT Prompt"},"content":{"rendered":"

Turn Daily Market Movers into Actionable Watchlists Using <\/strong>FMP<\/strong><\/a>\u2019s API and GPT Intelligence<\/strong><\/h4>\n

Photo by Anna Nekrashevich<\/a><\/p>\n

Every trader has one key goal: identify market movers early<\/strong>. Whether it\u2019s a breakout stock surging by double digits or a falling knife catching attention\u200a\u2014\u200againers and losers often lead the narrative<\/strong>. But manually scanning these daily? Not efficient.<\/p>\n

That\u2019s where Financial Modeling Prep<\/strong><\/a>\u2019s Gainers & Losers API<\/strong> steps in. It delivers real-time data on stocks with the biggest intraday moves\u200a\u2014\u200astraight to your code. And when paired with a GPT prompt<\/strong>, this data turns into intelligent watchlists within\u00a0seconds.<\/p>\n

In this article, we\u2019ll show how\u00a0to:<\/p>\n

\u2022 Fetch market movers using FMP<\/a>\u2019s\u00a0API,<\/p>\n

\u2022 Process the data using\u00a0Python,<\/p>\n

\u2022 And prompt GPT to generate a smart, prioritized watchlist.<\/p>\n

No guesswork. Just actionable insight\u200a\u2014\u200aautomated.<\/p>\n

Understanding FMP\u2019s Gainers & Losers\u00a0API<\/strong><\/h3>\n

Before we automate watchlist generation, let\u2019s understand the two powerful FMP<\/a> endpoints we\u2019ll be working\u00a0with:<\/p>\n

1. Top Gainers\u00a0API<\/strong><\/h4>\n

Endpoint:<\/strong><\/p>\n

https:\/\/financialmodelingprep.com\/api\/v3\/stock_market\/gainers<\/a><\/p>\n

Purpose:<\/strong><\/p>\n

Fetches stocks with the highest positive price change during the trading\u00a0day.<\/p>\n

Key Data Points Returned:<\/strong><\/p>\n

\u2022 Ticker symbol (e.g., AAPL)
\u2022 Company name
\u2022 Current price
\u2022 Price change
\u2022 Percentage change<\/p>\n

2. Top Losers\u00a0API<\/strong><\/h4>\n

Endpoint:<\/strong><\/p>\n

https:\/\/financialmodelingprep.com\/api\/v3\/stock_market\/losers<\/a><\/p>\n

Purpose:<\/strong><\/p>\n

Fetches stocks showing the largest negative price movement.<\/p>\n

Key Data Points Returned:<\/strong><\/p>\n

Same structure as the Top Gainers\u00a0API.<\/p>\n

You\u2019ll need a valid FMP API key<\/a> to access this data. Simply append\u00a0?apikey=YOUR_API_KEY to the endpoint\u00a0URL.<\/p>\n

Why These APIs\u00a0Matter<\/strong><\/h4>\n

Instead of relying on noisy news articles or slow manual tracking, these APIs\u00a0offer:<\/p>\n

Real-time insights<\/strong> into fast\u00a0movers,Structured, machine-readable<\/strong> data,Easy integration<\/strong> into Python workflows.<\/p>\n

Fetching and Processing Data with\u00a0Python<\/strong><\/h3>\n

Now that we know what the FMP<\/a> APIs provide, let\u2019s fetch the data and get it ready for\u00a0GPT.<\/p>\n

Step 1: Install Required Libraries<\/strong><\/h4>\n

First, ensure you have these libraries installed:<\/p>\n

pip install requests pandas<\/p>\n

Step 2: Fetch Gainers and Losers\u00a0Data<\/strong><\/h4>\n

We\u2019ll use Python\u2019s requests library to hit the API and pandas to handle the response.<\/p>\n

import requests
import pandas as pd<\/p>\n

# Replace with your actual FMP API Key
API_KEY = ‘your_api_key_here’
# API URLs
GAINERS_URL = f”https:\/\/financialmodelingprep.com\/api\/v3\/stock_market\/gainers?apikey={API_KEY}”
LOSERS_URL = f”https:\/\/financialmodelingprep.com\/api\/v3\/stock_market\/losers?apikey={API_KEY}”
# Fetch data
gainers_response = requests.get(GAINERS_URL)
losers_response = requests.get(LOSERS_URL)
# Convert to DataFrame
gainers_df = pd.DataFrame(gainers_response.json())
losers_df = pd.DataFrame(losers_response.json())<\/p>\n

Step 3: Quick Look at the\u00a0Data<\/strong><\/h4>\n

Let\u2019s check what we received:<\/p>\n

print(“Top Gainers:”)
print(gainers_df.head())<\/p>\n

print(“nTop Losers:”)
print(losers_df.head())<\/p>\n

You\u2019ll see fields\u00a0like:<\/p>\n

\u2022 symbol
\u2022 name
\u2022 price
\u2022 changesPercentage
\u2022 change<\/p>\n

Step 4: Merge and Clean the Data (Optional)<\/strong><\/h4>\n

If you want a combined view<\/strong> for GPT input, you can label the stocks and merge\u00a0them:<\/p>\n

gainers_df[‘movement’] = ‘Gainer’
losers_df[‘movement’] = ‘Loser’<\/p>\n

# Combine
market_movers_df = pd.concat([gainers_df, losers_df], ignore_index=True)
# Optional: Select only the important columns
market_movers_df = market_movers_df[[‘symbol’, ‘name’, ‘price’, ‘changesPercentage’, ‘movement’]]<\/p>\n

Now you have a clean dataset ready for GPT to understand!<\/p>\n

Crafting a GPT Prompt for Watchlist Generation<\/strong><\/h3>\n

Once we have a clean list of gainers and losers, the next step is to guide GPT<\/strong> to turn this raw data into a smart, curated watchlist<\/strong>.<\/p>\n

The key\u00a0here?<\/p>\n

A good prompt = better\u00a0results.<\/strong><\/p>\n

Step 1: Format the Data for the\u00a0Prompt<\/strong><\/h4>\n

Let\u2019s create a simple text format that GPT can easily understand.<\/p>\n

def format_for_prompt(df):
prompt_text = “”
for _, row in df.iterrows():
prompt_text += f”{row[‘symbol’]} ({row[‘name’]}): {row[‘movement’]} with {row[‘changesPercentage’]} changen”
return prompt_text<\/p>\n

formatted_data = format_for_prompt(market_movers_df)
print(formatted_data)<\/p>\n

This would produce something like:<\/p>\n

AAPL (Apple Inc.): Gainer with +3.5% change
TSLA (Tesla Inc.): Loser with -2.1% change
…<\/p>\n

Short, clean, human-readable.<\/p>\n

Step 2: Craft the GPT\u00a0Prompt<\/strong><\/h4>\n

Now, embed this formatted data into a clear instruction for\u00a0GPT:<\/p>\n

prompt = f”””
Based on the following stock movements, generate a watchlist of 5 stocks that seem promising for further research.
Consider factors like large gains, recovery potential after losses, or big moves worth monitoring.Stock Movements:
{formatted_data}
Provide the output in a list format, with a one-line reason for each stock selection.
“””<\/p>\n

This prompt will nudge GPT\u00a0to:<\/p>\n

Analyze<\/strong> both gainers and\u00a0losers,Pick 5 candidates<\/strong> intelligently,Give a reason<\/strong> why each stock was selected.<\/p>\n

Step 3: Example of GPT\u00a0Output<\/strong><\/h4>\n

Here\u2019s what GPT might\u00a0return:<\/p>\n

1. AAPL (Apple Inc.) \u2013 Strong intraday gain indicating potential momentum.
2. AMZN (Amazon.com Inc.) \u2013 Sharp recovery after recent losses, worth monitoring.
3. TSLA (Tesla Inc.) \u2013 Significant dip, could be a rebound opportunity.
4. NVDA (NVIDIA Corporation) \u2013 Continues strong uptrend with consistent gains.
5. MSFT (Microsoft Corp.) \u2013 Minor loss despite overall market weakness, shows resilience.<\/p>\n

Exactly what you want from a smart watchlist\u200a\u2014\u200aactionable and\u00a0concise!<\/p>\n

Automating the\u00a0Workflow<\/strong><\/h3>\n

Now that we have all the pieces\u200a\u2014\u200adata fetching, formatting, and GPT prompt creation\u200a\u2014\u200awhy not automate the entire\u00a0flow<\/strong>?<\/p>\n

Here\u2019s how you can build a simple daily watchlist generator.<\/p>\n

Step 1: Full Workflow\u00a0Script<\/strong><\/h4>\n

Here\u2019s a Python script that puts everything together:<\/p>\n

import requests
import pandas as pd<\/p>\n

# Function to fetch market movers
def fetch_market_movers(api_key):
gainers_url = f”https:\/\/financialmodelingprep.com\/api\/v3\/stock_market\/gainers?apikey={api_key}”
losers_url = f”https:\/\/financialmodelingprep.com\/api\/v3\/stock_market\/losers?apikey={api_key}”<\/p>\n

gainers = pd.DataFrame(requests.get(gainers_url).json())
losers = pd.DataFrame(requests.get(losers_url).json())<\/p>\n

gainers[‘movement’] = ‘Gainer’
losers[‘movement’] = ‘Loser’<\/p>\n

combined = pd.concat([gainers, losers], ignore_index=True)
return combined[[‘symbol’, ‘name’, ‘price’, ‘changesPercentage’, ‘movement’]]<\/p>\n

# Function to format data for GPT prompt
def format_for_gpt(df):
prompt_text = “”
for _, row in df.iterrows():
prompt_text += f”{row[‘symbol’]} ({row[‘name’]}): {row[‘movement’]} with {row[‘changesPercentage’]} changen”
return prompt_text<\/p>\n

# Function to generate final prompt
def create_watchlist_prompt(formatted_data):
return f”””
Based on the following stock movements, generate a watchlist of 5 stocks that seem promising for further research.
Consider factors like large gains, recovery potential after losses, or big moves worth monitoring.
Stock Movements:
{formatted_data}
Provide the output in a list format, with a one-line reason for each stock selection.
“””<\/p>\n

# Main
if __name__ == “__main__”:
API_KEY = “your_api_key_here”<\/p>\n

market_data = fetch_market_movers(API_KEY)
formatted_text = format_for_gpt(market_data)
final_prompt = create_watchlist_prompt(formatted_text)<\/p>\n

print(final_prompt)<\/p>\n

This script\u00a0will:<\/p>\n

Pull fresh gainers and\u00a0losers,Format the\u00a0data,Generate a ready-to-use prompt for\u00a0GPT.<\/p>\n

Step 2: Optional\u200a\u2014\u200aFully Automate It\u00a0Daily<\/strong><\/h4>\n

You can automate this script to run every morning<\/strong>\u00a0using:<\/p>\n

Task Scheduler<\/strong> on\u00a0Windows,Cron Jobs<\/strong> on Mac\/Linux,Cloud functions<\/strong> if you prefer serverless (AWS Lambda, Google Cloud Functions).<\/p>\n

You can even extend it\u00a0to:<\/p>\n

Send the prompt to GPT automatically,Email the generated watchlist to yourself,Or save it into a Notion page or a Google\u00a0Sheet!<\/p>\n

In just a few lines of code, you create a personalized, intelligent watchlist generator<\/strong>\u200a\u2014\u200awithout lifting a finger every\u00a0day.<\/p>\n

Free Stock Market API and Financial Statements API…<\/a><\/p>\n

Conclusion<\/h3>\n

Building a smart stock watchlist doesn\u2019t have to be manual or time-consuming.<\/p>\n

By combining FMP<\/strong><\/a>\u2019s Gainers & Losers <\/strong>API<\/strong><\/a> with a simple GPT prompt<\/strong>, you can automate watchlist generation based on real-time market movements.<\/p>\n

This approach not only saves time but also ensures you\u2019re always aligned with market trends\u200a\u2014\u200awith just a few lines of\u00a0code.<\/p>\n

Generate a Watchlist from FMP\u2019s Gainers & Losers API Using a GPT Prompt<\/a> was originally published in Coinmonks<\/a> on Medium, where people are continuing the conversation by highlighting and responding to this story.<\/p>","protected":false},"excerpt":{"rendered":"

Turn Daily Market Movers into Actionable Watchlists Using FMP\u2019s API and GPT Intelligence Photo by Anna Nekrashevich Every trader has one key goal: identify market movers early. Whether it\u2019s a breakout stock surging by double digits or a falling knife catching attention\u200a\u2014\u200againers and losers often lead the narrative. But manually scanning these daily? Not efficient. […]<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-63114","post","type-post","status-publish","format-standard","hentry","category-interesting"],"_links":{"self":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts\/63114"}],"collection":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=63114"}],"version-history":[{"count":0,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts\/63114\/revisions"}],"wp:attachment":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=63114"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=63114"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=63114"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}