{"id":"gen-1784513964-u1irHmAXmFCfukw6mZdU","choices":[{"finish_reason":"stop","index":0,"logprobs":null,"message":{"content":"```html\n\n\n\n \n \n S&P 500 Momentum Picks\n \n\n\n

S&P 500 Momentum Radar

Top 10 momentum picks using rolling 1M, 3M, and 6M performance.

Last update: —

\n\n

\n \n \n\n \n Model\n \n \n\n \n \n Positive 1M/3M/6M only\n \n

\n\n

\n \n Ready.\n

\n\n

Stocks Analyzed

Universe Size

Top Pick

—

Avg Top-10 Score

—

\n\n

Top 10 Picks

\n\n

Leaderboard

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n

#	Ticker	Company	Sector	1M	3M	6M	12M	Score

\n\n \n

\n\n \n\n\n```","refusal":null,"role":"assistant","annotations":null,"audio":null,"function_call":null,"tool_calls":null,"reasoning":"**Creating financial website**\n\nI need to answer the user's request to create a financial website that provides the top ten momentum picks for the S&P 500. That likely means I'll need to output HTML/CSS/JS code, possibly using static and dynamic elements. Since the response needs to render in an iframe, I should ensure to include all HTML—including script tags—in one code block without mentioning the iframe.\n\nI'll also figure out a data source, maybe using free APIs like stooq or AlphaVantage, but I might include sample data to avoid needing an API key.**Considering web API limitations**\n\nI’m aware that CORS issues might arise when making API calls in a browser, especially if using an iframe. One option could be yfinance, but that might be blocked. FinancialModelingPrep could work with a demo key, especially at the endpoint for S&P 500 constituents, but I'm not entirely sure. \n\nAlternatively, I could build the site using an example dataset for momentum calculation, potentially providing a static snapshot for the top picks, rather than real-time data. Using a free endpoint, like from the SEC, could also be an option to fetch historical prices, but that may be complicated.**Calculating momentum for S&P 500**\n\nI could calculate momentum using a 6-month performance metric from a quote endpoint, specifically the \"changesPercentage.\" However, for the top momentum picks from the S&P 500, it makes sense to look at performance over various periods.\n\nUsing the Financial Modeling Prep API could be an option, but it requires a key. Yahoo Finance's Spark API might be simpler since it doesn’t need a key, but CORS issues could arise when calling from a browser. \n\nI could also consider using third-party CORS proxies, though their reliability might be uncertain. Finally, to satisfy the user's request for a website, I might bundle the S&P 500 list with hard-coded returns while explaining it allows for future API replacements.**Building an interactive financial website**\n\nIt seems the user is expecting a fully interactive website featuring the top 10 momentum picks derived from live data. I can create this without using external libraries. Using a CORS proxy, I could compute momentum from 6 and 12-month returns with specific weightings.\n\nThe output will likely be an HTML code block, and I should include instructions for saving it as index.html. Features might include a header, description, a \"Refresh Picks\" button, options for momentum lookback (3M, 6M, 12M), and a display table for tickers and returns. I’ll also gather the S&P 500 constituents, possibly using a static list of the first 100 to simplify data fetching.**Determining momentum data sources**\n\nTo identify the top 10 momentum picks from the S&P 500, I'll need to retrieve data for all 500 companies, which could be heavy. The FinancialModelingPrep API has a stock screener endpoint that could provide numerous stock details, but it lacks momentum metrics. \n\nUsing their endpoint for constituents could work, and I can then call the quote endpoint in batches. CORS may complicate accessing some data, but APIs like Alpha Vantage or Finnhub could help. I might consider fetching from Wikipedia or Yahoo Finance, while being aware of potential CORS issues. Ultimately, including a fallback with mock data might be useful if an API fetch fails, allowing for a functional demonstration of the website.**Evaluating data sources for momentum picks**\n\nIn exploring how to create a financial website for top ten S&P 500 momentum picks, I see that the FinancialModelingPrep API provides a demo key that may work for most endpoints. However, there might be limitations on the number of constituents it can return. A potential fallback could be to use a publicly available CSV for stock data. \n\nI think it’d be wise to include features like a lookback period selector and a refresh button. I’ll need to design the HTML carefully along with an algorithm for calculating momentum scores. Using recent price changes to determine momentum seems feasible, potentially accessing multiple endpoints to gather the necessary data. Alternatively, scraping a performance webpage could provide data without relying on an API key. Using allorigins to bypass CORS restrictions may allow for successfully fetching that data.**Exploring data retrieval options**\n\nI’m unsure about the reliability of Slickcharts due to potential bot-blocking. Exploring other sources, such as Yahoo Finance and Wikipedia, may face similar issues with dynamic content. I could opt for Barchart or Stooq for weighted alpha rankings but would need to navigate API key requirements. \n\nCreating a website involving a user-input API key seems practical, ensuring the UI isn't blank with fallback data. I may structure it to fetch S&P 500 constituents while computing momentum scores, enabling a top ten display. I must handle potential rate limits and incorporate a fallback dataset. Scraping performance tables from Slickcharts through Allorigins could also be an effective solution.**Evaluating data fetching strategies**\n\nI'm considering using Stooq's quote endpoint for multiple symbols, but it may not provide the momentum returns I need, so I’ll look into other options. I have the idea of obtaining historical data to compute momentum over 6 months, but fetching this for 500 symbols can be a challenge. I could explore Yahoo Finance with direct calls first, and if CORS fails, I might use the Allorigins proxy as a fallback. Using Datahub’s JSON for S&P 500 constituents seems reliable, while carefully handling symbol format changes will be crucial. I'll implement robust error handling for optimal performance.**Parsing and processing data**\n\nI'm working on a function to parse data from Yahoo, mapping their symbols to names from the Datahub constituents map. I need to ensure that symbols like \"BRK.B\" are formatted correctly. After chunking the symbols, I'll compute momentum scores using helper functions to find returns for different time periods.\n\nThe momentum score formula will weigh the six-month, three-month, and one-month returns. I'll set up an interface with controls for refreshing data and possibly filtering for positive returns. My goal is to ensure the site handles fetch requests efficiently, incorporating fallback data if necessary, ensuring users see meaningful results.**Rendering UI for momentum picks**\n\nI'm developing a function to render the top ten momentum stocks. I want to create a dynamic table and display loading animations, ensuring the data updates correctly. I'm designing the final HTML structure with sections for controls, metrics, and picks.\n\nFor symbols analysis, I'm planning to fetch the necessary data, handle potential errors gracefully, and provide fallback options if live data isn't available. Metrics will display universe and analyzed counts. I’ll also add styling to make the interface visually appealing, with responsive design elements and gradient backgrounds.**Loading stock constituents and data**\n\nI'm implementing a function to load S&P 500 constituents by fetching data from a specified URL and mapping the results into a structured format. For the price returns, I'll chunk requests to handle potential rate limits effectively, possibly introducing pauses between requests.\n\nNext, I'll compute core metrics like momentum returns based on price data while ensuring all data is valid. As the program runs, I’ll maintain user status updates, manage fallback data, and ensure I'm providing clear metrics and error handling. Lastly, I’ll prepare functions for rendering tables and downloading CSVs with properly formatted outputs.**Crafting final HTML structure**\n\nI'm aiming to create a full HTML document for an S&P 500 Momentum Picks tool. It should include the necessary structure, styles, and scripts. I'll make sure that CSS variables are used for styling and maintain a user-friendly interface with features like a refresh button and CSV download option. It's important that the response is concise and doesn't include unnecessary details like iframes. Disclaimers will also be part of the content to clarify usage, and I want to ensure everything is clear and organized.**Completing the script logic**\n\nI’m wrapping up the script that handles my S&P 500 Momentum Picks tool. I’ve defined essential constants and created functions for data manipulation and rendering. It includes features like downloading a CSV of the top picks and loading live data from a specific URL for constituents. I’ll also ensure a user-friendly experience, including updating the UI to show loading statuses. Finally, I’ll confirm all aspects align with user expectations, providing clear outputs for informed decisions.**Finalizing the HTML code**\n\nI’m wrapping up the single-file HTML website for this financial tool. I want to ensure my style classes for success and warnings are defined with the right borders and colors, and that my status class has a default “info” style. \n\nGiven potential issues with fetching data due to CORS, I've included a fallback to sample data from built-in options when necessary. I’ll provide clear instructions to save the file as index.html. Now, I'll present the complete HTML code in one block with everything included! \n\n```html\n\n\n\n \n \n Financial Dashboard\n \n\n\n \n\n \n\n\n```","reasoning_details":[{"type":"reasoning.summary","summary":"**Creating financial website**\n\nI need to answer the user's request to create a financial website that provides the top ten momentum picks for the S&P 500. That likely means I'll need to output HTML/CSS/JS code, possibly using static and dynamic elements. Since the response needs to render in an iframe, I should ensure to include all HTML—including script tags—in one code block without mentioning the iframe.\n\nI'll also figure out a data source, maybe using free APIs like stooq or AlphaVantage, but I might include sample data to avoid needing an API key.**Considering web API limitations**\n\nI’m aware that CORS issues might arise when making API calls in a browser, especially if using an iframe. One option could be yfinance, but that might be blocked. FinancialModelingPrep could work with a demo key, especially at the endpoint for S&P 500 constituents, but I'm not entirely sure. \n\nAlternatively, I could build the site using an example dataset for momentum calculation, potentially providing a static snapshot for the top picks, rather than real-time data. Using a free endpoint, like from the SEC, could also be an option to fetch historical prices, but that may be complicated.**Calculating momentum for S&P 500**\n\nI could calculate momentum using a 6-month performance metric from a quote endpoint, specifically the \"changesPercentage.\" However, for the top momentum picks from the S&P 500, it makes sense to look at performance over various periods.\n\nUsing the Financial Modeling Prep API could be an option, but it requires a key. Yahoo Finance's Spark API might be simpler since it doesn’t need a key, but CORS issues could arise when calling from a browser. \n\nI could also consider using third-party CORS proxies, though their reliability might be uncertain. Finally, to satisfy the user's request for a website, I might bundle the S&P 500 list with hard-coded returns while explaining it allows for future API replacements.**Building an interactive financial website**\n\nIt seems the user is expecting a fully interactive website featuring the top 10 momentum picks derived from live data. I can create this without using external libraries. Using a CORS proxy, I could compute momentum from 6 and 12-month returns with specific weightings.\n\nThe output will likely be an HTML code block, and I should include instructions for saving it as index.html. Features might include a header, description, a \"Refresh Picks\" button, options for momentum lookback (3M, 6M, 12M), and a display table for tickers and returns. I’ll also gather the S&P 500 constituents, possibly using a static list of the first 100 to simplify data fetching.**Determining momentum data sources**\n\nTo identify the top 10 momentum picks from the S&P 500, I'll need to retrieve data for all 500 companies, which could be heavy. The FinancialModelingPrep API has a stock screener endpoint that could provide numerous stock details, but it lacks momentum metrics. \n\nUsing their endpoint for constituents could work, and I can then call the quote endpoint in batches. CORS may complicate accessing some data, but APIs like Alpha Vantage or Finnhub could help. I might consider fetching from Wikipedia or Yahoo Finance, while being aware of potential CORS issues. Ultimately, including a fallback with mock data might be useful if an API fetch fails, allowing for a functional demonstration of the website.**Evaluating data sources for momentum picks**\n\nIn exploring how to create a financial website for top ten S&P 500 momentum picks, I see that the FinancialModelingPrep API provides a demo key that may work for most endpoints. However, there might be limitations on the number of constituents it can return. A potential fallback could be to use a publicly available CSV for stock data. \n\nI think it’d be wise to include features like a lookback period selector and a refresh button. I’ll need to design the HTML carefully along with an algorithm for calculating momentum scores. Using recent price changes to determine momentum seems feasible, potentially accessing multiple endpoints to gather the necessary data. Alternatively, scraping a performance webpage could provide data without relying on an API key. Using allorigins to bypass CORS restrictions may allow for successfully fetching that data.**Exploring data retrieval options**\n\nI’m unsure about the reliability of Slickcharts due to potential bot-blocking. Exploring other sources, such as Yahoo Finance and Wikipedia, may face similar issues with dynamic content. I could opt for Barchart or Stooq for weighted alpha rankings but would need to navigate API key requirements. \n\nCreating a website involving a user-input API key seems practical, ensuring the UI isn't blank with fallback data. I may structure it to fetch S&P 500 constituents while computing momentum scores, enabling a top ten display. I must handle potential rate limits and incorporate a fallback dataset. Scraping performance tables from Slickcharts through Allorigins could also be an effective solution.**Evaluating data fetching strategies**\n\nI'm considering using Stooq's quote endpoint for multiple symbols, but it may not provide the momentum returns I need, so I’ll look into other options. I have the idea of obtaining historical data to compute momentum over 6 months, but fetching this for 500 symbols can be a challenge. I could explore Yahoo Finance with direct calls first, and if CORS fails, I might use the Allorigins proxy as a fallback. Using Datahub’s JSON for S&P 500 constituents seems reliable, while carefully handling symbol format changes will be crucial. I'll implement robust error handling for optimal performance.**Parsing and processing data**\n\nI'm working on a function to parse data from Yahoo, mapping their symbols to names from the Datahub constituents map. I need to ensure that symbols like \"BRK.B\" are formatted correctly. After chunking the symbols, I'll compute momentum scores using helper functions to find returns for different time periods.\n\nThe momentum score formula will weigh the six-month, three-month, and one-month returns. I'll set up an interface with controls for refreshing data and possibly filtering for positive returns. My goal is to ensure the site handles fetch requests efficiently, incorporating fallback data if necessary, ensuring users see meaningful results.**Rendering UI for momentum picks**\n\nI'm developing a function to render the top ten momentum stocks. I want to create a dynamic table and display loading animations, ensuring the data updates correctly. I'm designing the final HTML structure with sections for controls, metrics, and picks.\n\nFor symbols analysis, I'm planning to fetch the necessary data, handle potential errors gracefully, and provide fallback options if live data isn't available. Metrics will display universe and analyzed counts. I’ll also add styling to make the interface visually appealing, with responsive design elements and gradient backgrounds.**Loading stock constituents and data**\n\nI'm implementing a function to load S&P 500 constituents by fetching data from a specified URL and mapping the results into a structured format. For the price returns, I'll chunk requests to handle potential rate limits effectively, possibly introducing pauses between requests.\n\nNext, I'll compute core metrics like momentum returns based on price data while ensuring all data is valid. As the program runs, I’ll maintain user status updates, manage fallback data, and ensure I'm providing clear metrics and error handling. Lastly, I’ll prepare functions for rendering tables and downloading CSVs with properly formatted outputs.**Crafting final HTML structure**\n\nI'm aiming to create a full HTML document for an S&P 500 Momentum Picks tool. It should include the necessary structure, styles, and scripts. I'll make sure that CSS variables are used for styling and maintain a user-friendly interface with features like a refresh button and CSV download option. It's important that the response is concise and doesn't include unnecessary details like iframes. Disclaimers will also be part of the content to clarify usage, and I want to ensure everything is clear and organized.**Completing the script logic**\n\nI’m wrapping up the script that handles my S&P 500 Momentum Picks tool. I’ve defined essential constants and created functions for data manipulation and rendering. It includes features like downloading a CSV of the top picks and loading live data from a specific URL for constituents. I’ll also ensure a user-friendly experience, including updating the UI to show loading statuses. Finally, I’ll confirm all aspects align with user expectations, providing clear outputs for informed decisions.**Finalizing the HTML code**\n\nI’m wrapping up the single-file HTML website for this financial tool. I want to ensure my style classes for success and warnings are defined with the right borders and colors, and that my status class has a default “info” style. \n\nGiven potential issues with fetching data due to CORS, I've included a fallback to sample data from built-in options when necessary. I’ll provide clear instructions to save the file as index.html. Now, I'll present the complete HTML code in one block with everything included! \n\n```html\n\n\n\n \n \n Financial Dashboard\n \n\n\n \n\n \n\n\n```","format":"azure-openai-responses-v1","index":0},{"type":"reasoning.encrypted","data":"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SnP500 momentum picker