Tag: stock-market

  • Pre-IPO API: SEC Filings, SPACs & Lockup Data

    Pre-IPO API: SEC Filings, SPACs & Lockup Data

    I built the Pre-IPO Intelligence API because I needed this data for my own trading systems and couldn’t find it in one place. If you’re building fintech applications, trading bots, or investment research tools, you know the pain: pre-IPO data is fragmented across dozens of SEC filing pages, paywalled databases, and stale spreadsheets. The Pre-IPO Intelligence API solves this by delivering real-time SEC filings, SPAC tracking, lockup expiration calendars, and M&A intelligence through a single, developer-friendly REST API — available now on RapidAPI with a free tier to get started.

    In this deep dive, we’ll cover what the API offers across its 42 endpoints, walk through practical code examples in both cURL and Python, and explore real-world use cases for developers and quant engineers. Whether you’re building the next algorithmic trading system or a portfolio intelligence dashboard, this guide will get you up and running in minutes.

    What Is the Pre-IPO Intelligence API?

    ๐Ÿ“Œ TL;DR: If you’re building fintech applications, trading bots, or investment research tools, you know the pain: pre-IPO data is fragmented across dozens of SEC filing pages, paywalled databases, and stale spreadsheets.
    ๐ŸŽฏ Quick Answer
    If you’re building fintech applications, trading bots, or investment research tools, you know the pain: pre-IPO data is fragmented across dozens of SEC filing pages, paywalled databases, and stale spreadsheets.

    The Pre-IPO Intelligence API (v3.0.1) is a comprehensive financial data service that aggregates, normalizes, and serves pre-IPO market intelligence through 42 RESTful endpoints. It covers the full lifecycle of companies going public — from early-stage private valuations and S-1 filings through SPAC mergers, IPO pricing, lockup expirations, and post-IPO M&A activity.

    Unlike scraping SEC.gov yourself or paying five-figure annual fees for enterprise terminals, this API gives you structured, machine-readable JSON data with sub-second response times. It’s designed for developers who need to integrate pre-IPO intelligence into their applications without building an entire data pipeline from scratch.

    Key Capabilities at a Glance

    • Company Intelligence: Search and retrieve detailed profiles on pre-IPO companies, including valuation history, funding rounds, and sector classification
    • SEC Filing Monitoring: Real-time tracking of S-1, S-1/A, F-1, and prospectus filings with parsed key data points
    • Lockup Expiration Calendar: Know exactly when insider selling restrictions expire — one of the most predictable catalysts for post-IPO price movement
    • SPAC Tracking: Monitor active SPACs, merger targets, trust values, redemption rates, and deal timelines
    • M&A Intelligence: Track merger and acquisition activity involving pre-IPO and recently-public companies
    • Market Overview: Aggregate statistics on IPO pipeline health, sector trends, and market sentiment indicators

    Getting Started: Subscribe on RapidAPI

    The fastest way to start using the API is through RapidAPI. The freemium model lets you explore endpoints with generous rate limits before committing to a paid plan. Here’s how to get set up:

    1. Visit the Pre-IPO Intelligence API page on RapidAPI
    2. Click “Subscribe to Test” and select the free tier
    3. Copy your X-RapidAPI-Key from the dashboard
    4. Start making requests immediately — no credit card required for the free plan

    Once subscribed, you’ll have access to all 42 endpoints. The free tier includes enough requests for development and testing, while paid tiers unlock higher rate limits and priority support for production workloads.

    Core Endpoint Reference

    Let’s walk through the five core endpoint groups with practical examples. All endpoints return JSON and accept standard query parameters for filtering, pagination, and sorting.

    The /api/companies/search endpoint is your entry point for finding pre-IPO companies. It supports full-text search across company names, tickers, sectors, and descriptions.

    cURL Example

    curl -X GET "https://pre-ipo-intelligence.p.rapidapi.com/api/companies/search?q=artificial+intelligence&sector=technology&limit=10" \
      -H "X-RapidAPI-Key: YOUR_RAPIDAPI_KEY" \
      -H "X-RapidAPI-Host: pre-ipo-intelligence.p.rapidapi.com"

    Python Example

    import requests
    
    url = "https://pre-ipo-intelligence.p.rapidapi.com/api/companies/search"
    params = {
        "q": "artificial intelligence",
        "sector": "technology",
        "limit": 10
    }
    headers = {
        "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
        "X-RapidAPI-Host": "pre-ipo-intelligence.p.rapidapi.com"
    }
    
    response = requests.get(url, headers=headers, params=params)
    companies = response.json()
    
    for company in companies.get("results", []):
        print(f"{company['name']} โ€” Valuation: ${company.get('valuation', 'N/A')}")
        print(f"  Sector: {company.get('sector')} | Stage: {company.get('stage')}")
        print()

    The response includes rich metadata: company name, latest valuation estimate, funding stage, sector, key executives, and links to relevant SEC filings. This is the same data that powers our Pre-IPO Valuation Tracker for companies like SpaceX, OpenAI, and Anthropic.

    2. SEC Filing Monitoring

    The /api/filings/recent endpoint delivers newly published SEC filings relevant to IPO-track companies. Stop polling EDGAR manually — let the API push structured filing data to your application.

    curl -X GET "https://pre-ipo-intelligence.p.rapidapi.com/api/filings/recent?type=S-1&days=7&limit=20" \
      -H "X-RapidAPI-Key: YOUR_RAPIDAPI_KEY" \
      -H "X-RapidAPI-Host: pre-ipo-intelligence.p.rapidapi.com"
    import requests
    
    url = "https://pre-ipo-intelligence.p.rapidapi.com/api/filings/recent"
    params = {"type": "S-1", "days": 7, "limit": 20}
    headers = {
        "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
        "X-RapidAPI-Host": "pre-ipo-intelligence.p.rapidapi.com"
    }
    
    response = requests.get(url, headers=headers, params=params)
    filings = response.json()
    
    for filing in filings.get("results", []):
        print(f"[{filing['filed_date']}] {filing['company_name']}")
        print(f"  Type: {filing['filing_type']} | URL: {filing['sec_url']}")
        print()

    Each filing record includes the company name, filing type (S-1, S-1/A, F-1, 424B, etc.), filing date, SEC URL, and extracted financial highlights such as proposed share price range, shares offered, and underwriters. This is invaluable for building IPO alert systems or AI-driven market signal pipelines.

    3. Lockup Expiration Calendar

    The /api/lockup/calendar endpoint is a hidden gem for swing traders and quant funds. Lockup expirations — when insiders are first allowed to sell shares after an IPO — are among the most statistically significant and predictable events in equity markets. Studies consistently show that stocks decline an average of 1–3% around lockup expiry dates due to increased supply pressure.

    import requests
    from datetime import datetime, timedelta
    
    url = "https://pre-ipo-intelligence.p.rapidapi.com/api/lockup/calendar"
    params = {
        "start_date": datetime.now().strftime("%Y-%m-%d"),
        "end_date": (datetime.now() + timedelta(days=30)).strftime("%Y-%m-%d"),
    }
    headers = {
        "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
        "X-RapidAPI-Host": "pre-ipo-intelligence.p.rapidapi.com"
    }
    
    response = requests.get(url, headers=headers, params=params)
    lockups = response.json()
    
    for event in lockups.get("results", []):
        shares_pct = event.get("shares_percent", "N/A")
        print(f"{event['expiry_date']} โ€” {event['company_name']} ({event['ticker']})")
        print(f"  Shares unlocking: {shares_pct}% of float")
        print(f"  IPO Price: ${event.get('ipo_price')} | Current: ${event.get('current_price')}")
        print()

    This data pairs perfectly with a disciplined risk management framework. You can build automated alerts, backtest lockup-expiration strategies, or feed the calendar into a portfolio hedging system.

    4. SPAC Tracking

    SPACs (Special Purpose Acquisition Companies) remain an important vehicle for companies going public, especially in sectors like clean energy, fintech, and AI. The /api/spac/active endpoint provides real-time tracking of active SPACs and their merger pipelines.

    curl -X GET "https://pre-ipo-intelligence.p.rapidapi.com/api/spac/active?status=searching&min_trust_value=100000000" \
      -H "X-RapidAPI-Key: YOUR_RAPIDAPI_KEY" \
      -H "X-RapidAPI-Host: pre-ipo-intelligence.p.rapidapi.com"

    The response includes trust value, redemption rates, target acquisition sector, deadline dates, sponsor information, and merger status. For SPACs that have announced targets, you also get the target company profile, deal terms, and projected timeline to close.

    5. Market Overview & Pipeline Health

    The /api/market/overview endpoint provides a bird’s-eye view of the IPO market, including pipeline statistics, sector breakdowns, pricing trends, and sentiment indicators.

    import requests
    
    url = "https://pre-ipo-intelligence.p.rapidapi.com/api/market/overview"
    headers = {
        "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
        "X-RapidAPI-Host": "pre-ipo-intelligence.p.rapidapi.com"
    }
    
    response = requests.get(url, headers=headers)
    market = response.json()
    
    print(f"IPO Pipeline: {market.get('pipeline_count')} companies")
    print(f"Avg First-Day Return: {market.get('avg_first_day_return')}%")
    print(f"Market Sentiment: {market.get('sentiment')}")
    print(f"Most Active Sector: {market.get('top_sector')}")
    print(f"YTD IPOs: {market.get('ytd_ipo_count')}")

    This endpoint is especially useful for macro-level dashboards and for timing IPO-related strategies based on overall market appetite for new listings.

    Real-World Use Cases

    The Pre-IPO Intelligence API is built for developers and engineers who want to integrate financial intelligence into their applications. Here are four high-impact use cases we’ve seen from early adopters.

    Fintech & Investment Apps

    If you’re building a consumer investment app or brokerage platform, the API can power an entire “IPO Center” feature. Show users upcoming IPOs, lockup calendars, and filing alerts — the kind of data that was previously locked behind Bloomberg terminals. The company search and market overview endpoints give you everything needed to build a compelling IPO discovery experience.

    Algorithmic Trading Bots

    For quant developers building algorithmic trading systems, the lockup expiration calendar and filing endpoints provide structured event data that can be fed directly into signal generation engines. Lockup expirations, in particular, offer a well-documented statistical edge — the combination of pre-IPO data APIs can give your models a significant informational advantage.

    # Lockup Expiration Trading Signal Generator
    import requests
    from datetime import datetime, timedelta
    
    def get_lockup_signals(api_key, lookahead_days=14):
        """Fetch upcoming lockup expirations and generate trading signals."""
        url = "https://pre-ipo-intelligence.p.rapidapi.com/api/lockup/calendar"
        headers = {
            "X-RapidAPI-Key": api_key,
            "X-RapidAPI-Host": "pre-ipo-intelligence.p.rapidapi.com"
        }
        params = {
            "start_date": datetime.now().strftime("%Y-%m-%d"),
            "end_date": (datetime.now() + timedelta(days=lookahead_days)).strftime("%Y-%m-%d"),
        }
    
        response = requests.get(url, headers=headers, params=params)
        lockups = response.json().get("results", [])
    
        signals = []
        for lockup in lockups:
            shares_pct = lockup.get("shares_percent", 0)
            days_to_expiry = (
                datetime.strptime(lockup["expiry_date"], "%Y-%m-%d") - datetime.now()
            ).days
    
            # High-conviction signal: large unlock + near expiry
            if shares_pct > 20 and days_to_expiry <= 5:
                signals.append({
                    "ticker": lockup["ticker"],
                    "action": "MONITOR",
                    "conviction": "HIGH",
                    "expiry_date": lockup["expiry_date"],
                    "shares_unlocking_pct": shares_pct,
                    "rationale": f"{shares_pct}% float unlock in {days_to_expiry} days"
                })
    
        return signals
    
    # Usage
    signals = get_lockup_signals("YOUR_RAPIDAPI_KEY")
    for s in signals:
        print(f"[{s['conviction']}] {s['action']} {s['ticker']} โ€” {s['rationale']}")

    Investment Research Platforms

    Equity research teams and data-driven newsletters can use the API to automate IPO screening and filing analysis. Instead of manually checking EDGAR every morning, pipe the filings endpoint into a Slack alert or email digest. The company search endpoint lets analysts quickly pull structured profiles for due diligence workflows.

    Portfolio Monitoring Dashboards

    If you manage a portfolio with exposure to recently-IPO’d stocks, the lockup calendar and SPAC endpoints are essential monitoring tools. Build a dashboard that surfaces upcoming lockup expirations for your holdings, tracks SPAC deal timelines, and alerts you to new SEC filings for companies on your watchlist. Combined with the market overview, you get a complete situational awareness layer for IPO-adjacent positions.

    API Architecture & Technical Details

    For developers who care about what’s under the hood, the Pre-IPO Intelligence API (v3.0.1) is built with the following characteristics:

    • Response Format: All endpoints return JSON with consistent envelope structure (results, meta, pagination)
    • Authentication: Via RapidAPI proxy — a single X-RapidAPI-Key header handles auth, rate limiting, and billing
    • Rate Limiting: Tier-based through RapidAPI. Free tier includes generous allowances for development. Paid tiers scale to thousands of requests per minute
    • Latency: Median response time under 200ms for search endpoints, under 500ms for aggregate endpoints
    • Pagination: Standard limit and offset parameters across all list endpoints
    • Error Handling: RESTful HTTP status codes with descriptive error messages in JSON
    • Uptime: 99.9% availability SLA on paid tiers

    The API is served through RapidAPI’s global edge network, which means low-latency access from anywhere. The underlying data is refreshed continuously from SEC EDGAR, exchange feeds, and proprietary data sources.

    Pricing: Start Free, Scale as Needed

    The API follows a freemium model on RapidAPI, making it accessible to solo developers and enterprise teams alike:

    • Free Tier: Perfect for development, testing, and personal projects. Includes enough monthly requests to build and prototype your application
    • Pro Tier: Higher rate limits and priority support for production applications. Ideal for startups and small teams shipping real products
    • Enterprise: Custom rate limits, dedicated support, and SLA guarantees for high-volume production workloads

    Check the Pre-IPO Intelligence API pricing page on RapidAPI for current rates and included quotas. The free tier requires no credit card — just sign up and start calling endpoints.

    Quick-Start Integration Guide

    ๐Ÿ”ง From my experience: The endpoint I use most in my own trading pipeline is /lockup-expirations. Lockup expiry dates create predictable selling pressure that’s visible days in advance. I pair this data with options flow analysis to find asymmetric setups around insider unlock dates.

    Here’s a complete, copy-paste-ready Python script that connects to the API and pulls a summary of the current IPO market with upcoming lockup events:

    #!/usr/bin/env python3
    """Pre-IPO Intelligence API โ€” Quick Start Demo"""
    
    import requests
    from datetime import datetime, timedelta
    
    API_KEY = "YOUR_RAPIDAPI_KEY"
    BASE_URL = "https://pre-ipo-intelligence.p.rapidapi.com"
    HEADERS = {
        "X-RapidAPI-Key": API_KEY,
        "X-RapidAPI-Host": "pre-ipo-intelligence.p.rapidapi.com"
    }
    
    def get_market_overview():
        """Get current IPO market conditions."""
        resp = requests.get(f"{BASE_URL}/api/market/overview", headers=HEADERS)
        resp.raise_for_status()
        return resp.json()
    
    def get_recent_filings(days=7):
        """Get SEC filings from the past N days."""
        resp = requests.get(
            f"{BASE_URL}/api/filings/recent",
            headers=HEADERS,
            params={"days": days, "limit": 5}
        )
        resp.raise_for_status()
        return resp.json()
    
    def get_upcoming_lockups(days=30):
        """Get lockup expirations in the next N days."""
        now = datetime.now()
        resp = requests.get(
            f"{BASE_URL}/api/lockup/calendar",
            headers=HEADERS,
            params={
                "start_date": now.strftime("%Y-%m-%d"),
                "end_date": (now + timedelta(days=days)).strftime("%Y-%m-%d"),
            }
        )
        resp.raise_for_status()
        return resp.json()
    
    def search_companies(query):
        """Search for pre-IPO companies."""
        resp = requests.get(
            f"{BASE_URL}/api/companies/search",
            headers=HEADERS,
            params={"q": query, "limit": 5}
        )
        resp.raise_for_status()
        return resp.json()
    
    if __name__ == "__main__":
        # 1. Market Overview
        print("=== IPO Market Overview ===")
        market = get_market_overview()
        for key, val in market.items():
            if key != "meta":
                print(f"  {key}: {val}")
    
        # 2. Recent Filings
        print("\n=== Recent SEC Filings (7 days) ===")
        filings = get_recent_filings()
        for f in filings.get("results", []):
            print(f"  [{f['filed_date']}] {f['company_name']} โ€” {f['filing_type']}")
    
        # 3. Upcoming Lockups
        print("\n=== Upcoming Lockup Expirations (30 days) ===")
        lockups = get_upcoming_lockups()
        for l in lockups.get("results", []):
            print(f"  {l['expiry_date']} โ€” {l['company_name']} ({l.get('shares_percent', '?')}% unlock)")
    
        # 4. Company Search
        print("\n=== AI Companies in Pre-IPO Stage ===")
        results = search_companies("artificial intelligence")
        for c in results.get("results", []):
            print(f"  {c['name']} โ€” {c.get('sector', 'N/A')} โ€” Est. Valuation: ${c.get('valuation', 'N/A')}")

    If you’re serious about building quantitative trading systems or financial applications, I highly recommend Python for Finance by Yves Hilpisch. It’s the definitive guide to using Python for financial analysis, algorithmic trading, and computational finance — and it pairs perfectly with the kind of data the Pre-IPO Intelligence API provides. For a deeper dive into systematic strategy development, Quantitative Trading by Ernest Chan is another essential read for quant-minded developers.

    Why Choose Pre-IPO Intelligence Over Alternatives?

    We’ve compared the landscape of finance APIs for pre-IPO data, and here’s what sets this API apart:

    • Breadth: 42 endpoints covering the full pre-IPO lifecycle, from private company intelligence to post-IPO lockup tracking. Most competitors focus on a single slice
    • Freshness: Data is refreshed continuously, not on daily or weekly batch cycles. SEC filings appear within minutes of publication
    • Developer Experience: Clean JSON responses, consistent pagination, proper error codes. No XML parsing, no SOAP, no proprietary SDKs required
    • Pricing Transparency: Freemium through RapidAPI with clear tier pricing. No sales calls required, no hidden fees, no annual commitments for basic plans
    • Integration Speed: From signup to first API call in under 2 minutes via RapidAPI

    Start Building Today

    The Pre-IPO Intelligence API is live and ready for integration. Whether you’re prototyping a weekend project or architecting a production trading system, the free tier gives you everything needed to evaluate the data quality and build your proof of concept.

    👉 Subscribe to the Pre-IPO Intelligence API on RapidAPI →

    Already using the API? We’d love to hear what you’re building. Drop a comment below or reach out through the RapidAPI discussion page.


    Related reading on Orthogonal:

    References

    1. RapidAPI โ€” “Pre-IPO Intelligence API Documentation”
    2. U.S. Securities and Exchange Commission (SEC) โ€” “EDGAR – Search and Access SEC Filings”
    3. GitHub โ€” “Pre-IPO Intelligence API Python SDK”
    4. RapidAPI Blog โ€” “How to Use the Pre-IPO Intelligence API for Financial Data”
    5. Crunchbase โ€” “SPAC Tracking and Pre-IPO Data Overview”
  • Track Pre-IPO Valuations: SpaceX, OpenAI & More

    Track Pre-IPO Valuations: SpaceX, OpenAI & More

    SpaceX is being valued at $2 trillion by the market. OpenAI at $1.3 trillion. Anthropic at over $500 billion. But none of these companies are publicly traded. There’s no ticker symbol, no earnings call, no 10-K filing. So how do we know what the market thinks they’re worth?

    The answer lies in a fascinating financial instrument that most developers and even many finance professionals overlook: publicly traded closed-end funds that hold shares in pre-IPO companies. And now there’s a free pre-IPO valuation API that does all the math for you โ€” turning raw fund data into real-time implied valuations for the world’s most anticipated IPOs.

    In this post, I’ll explain the methodology, walk you through the current data, and show you how to integrate this pre-IPO valuation tracker into your own applications using a few simple API calls.

    The Hidden Signal: How Public Markets Price Private Companies

    ๐Ÿ“Œ TL;DR: SpaceX is being valued at $2 trillion by the market. OpenAI at $1.3 trillion . Anthropic at over $500 billion .
    Quick Answer: Use SEC EDGAR filings, Crunchbase API, and PitchBook to track pre-IPO valuations for companies like SpaceX and OpenAI. Focus on closed-end fund data from DXYZ and VCX, secondary market prices, and funding round disclosures for the most accurate real-time implied valuations.

    There are two closed-end funds trading on the NYSE that give us a direct window into how the public market values private tech companies:

    Unlike typical venture funds, these trade on public exchanges just like any stock. That means their share prices are set by supply and demand โ€” real money from real investors making real bets on the future value of these private companies.

    Here’s the key insight: these funds publish their Net Asset Value (NAV) and their portfolio holdings (which companies they own, and what percentage of the fund each company represents). When the fund’s market price diverges from its NAV โ€” and it almost always does โ€” we can use that divergence to calculate what the market implicitly values each underlying private company at.

    The Math: From Fund Premium to Implied Valuation

    The calculation is straightforward. Let’s walk through it step by step:

    Step 1: Calculate the fund’s premium to NAV

    Fund Premium = (Market Price - NAV) / NAV
    
    Example (DXYZ):
     Market Price = $65.00
     NAV per share = $8.50
     Premium = ($65.00 - $8.50) / $8.50 = 665%

    Yes, you read that right. DXYZ routinely trades at 6-8x its net asset value. Investors are paying $65 for $8.50 worth of assets because they believe those assets (SpaceX, Stripe, etc.) are dramatically undervalued on the fund’s books.

    Step 2: Apply the premium to each holding

    Implied Valuation = Last Round Valuation ร— (1 + Fund Premium) ร— (Holding Weight Adjustment)
    
    Example (SpaceX via DXYZ):
     Last private round: $350B
     DXYZ premium: ~665%
     SpaceX weight in DXYZ: ~33%
     Implied Valuation โ‰ˆ $2,038B ($2.04 trillion)

    The API handles all of this automatically โ€” pulling live prices, applying the latest NAV data, weighting by portfolio composition, and outputting a clean implied valuation for each company.

    The Pre-IPO Valuation Leaderboard: $7 Trillion in Implied Value

    Here’s the current leaderboard from the AI Stock Data API, showing the top implied valuations across both funds. These are real numbers derived from live market data:

    RankCompanyImplied ValuationFundLast Private RoundPremium to Last Round
    1SpaceX$2,038BDXYZ$350B+482%
    2OpenAI$1,316BVCX$300B+339%
    3Stripe$533BDXYZ$65B+720%
    4Databricks$520BVCX$43B+1,109%
    5Anthropic$516BVCX$61.5B+739%

    Across 21 tracked companies, the total implied market valuation exceeds $7 trillion. To put that in perspective, that’s roughly equivalent to the combined market caps of Apple and Microsoft.

    Some of the most striking data points:

    • Databricks at +1,109% over its last round โ€” The market is pricing in explosive growth in the enterprise data/AI platform space. At an implied $520B, Databricks would be worth more than most public SaaS companies combined.
    • SpaceX at $2 trillion โ€” Making it (by implied valuation) one of the most valuable companies on Earth, public or private. This reflects both Starlink’s revenue trajectory and investor excitement around Starship.
    • Stripe’s quiet resurgence โ€” At an implied $533B, the market has completely repriced Stripe from its 2023 down-round doldrums. The embedded finance thesis is back.
    • The AI trio โ€” OpenAI ($1.3T), Anthropic ($516B), and xAI together represent a massive concentration of speculative capital in foundation model companies.

    API Walkthrough: Get Pre-IPO Valuations in 30 Seconds

    The AI Stock Data API is available on RapidAPI with a free tier (500 requests/month) โ€” no credit card required. Here’s how to get started.

    1. Get the Valuation Leaderboard

    This single endpoint returns all tracked pre-IPO companies ranked by implied valuation:

    # Get the full pre-IPO valuation leaderboard (FREE tier)
    curl "https://ai-stock-data-api.p.rapidapi.com/companies/leaderboard" -H "X-RapidAPI-Key: YOUR_KEY" -H "X-RapidAPI-Host: ai-stock-data-api.p.rapidapi.com"

    Response includes company name, implied valuation, source fund, last private round valuation, premium percentage, and portfolio weight โ€” everything you need to build a pre-IPO tracking dashboard.

    2. Get Live Fund Quotes with NAV Premium

    Want to track the DXYZ fund premium or VCX fund premium in real time? The quote endpoint gives you the live price, NAV, premium percentage, and market data:

    # Get live DXYZ quote with NAV premium calculation
    curl "https://ai-stock-data-api.p.rapidapi.com/funds/DXYZ/quote" -H "X-RapidAPI-Key: YOUR_KEY" -H "X-RapidAPI-Host: ai-stock-data-api.p.rapidapi.com"
    
    # Get live VCX quote
    curl "https://ai-stock-data-api.p.rapidapi.com/funds/VCX/quote" -H "X-RapidAPI-Key: YOUR_KEY" -H "X-RapidAPI-Host: ai-stock-data-api.p.rapidapi.com"

    3. Premium Analytics: Bollinger Bands & Mean Reversion

    For quantitative traders, the API offers Bollinger Band analysis on fund premiums โ€” helping you identify when DXYZ or VCX is statistically overbought or oversold relative to its own history:

    # Premium analytics with Bollinger Bands (Pro tier)
    curl "https://ai-stock-data-api.p.rapidapi.com/funds/DXYZ/premium/bands" -H "X-RapidAPI-Key: YOUR_KEY" -H "X-RapidAPI-Host: ai-stock-data-api.p.rapidapi.com"

    The response includes the current premium, 20-day moving average, upper and lower Bollinger Bands (2ฯƒ), and a z-score telling you exactly how many standard deviations the current premium is from the mean. When the z-score exceeds +2 or drops below -2, you’re looking at a potential mean-reversion trade.

    4. Build It Into Your App (JavaScript Example)

    // Fetch the pre-IPO valuation leaderboard
    const response = await fetch(
     'https://ai-stock-data-api.p.rapidapi.com/companies/leaderboard',
     {
     headers: {
     'X-RapidAPI-Key': process.env.RAPIDAPI_KEY,
     'X-RapidAPI-Host': 'ai-stock-data-api.p.rapidapi.com'
     }
     }
    );
    
    const leaderboard = await response.json();
    
    // Display top 5 companies by implied valuation
    leaderboard.slice(0, 5).forEach((company, i) => {
     console.log(
     `${i + 1}. ${company.name}: $${company.implied_valuation_b}B ` +
     `(+${company.premium_pct}% vs last round)`
     );
    });
    # Python example: Track SpaceX valuation over time
    import requests
    
    headers = {
     "X-RapidAPI-Key": "YOUR_KEY",
     "X-RapidAPI-Host": "ai-stock-data-api.p.rapidapi.com"
    }
    
    # Get the leaderboard
    resp = requests.get(
     "https://ai-stock-data-api.p.rapidapi.com/companies/leaderboard",
     headers=headers
    )
    companies = resp.json()
    
    # Filter for SpaceX
    spacex = next(c for c in companies if "SpaceX" in c["name"])
    print(f"SpaceX implied valuation: ${spacex['implied_valuation_b']}B")
    print(f"Premium over last round: {spacex['premium_pct']}%")
    print(f"Source fund: {spacex['fund']}")

    Who Should Use This API?

    The Pre-IPO & AI Valuation Intelligence API is designed for several distinct audiences:

    Fintech Developers Building Pre-IPO Dashboards

    If you’re building an investment platform, portfolio tracker, or market intelligence tool, this API gives you data that simply doesn’t exist elsewhere in a structured format. Add a “Pre-IPO Watchlist” feature to your app and let users track implied valuations for SpaceX, OpenAI, Anthropic, and more โ€” updated in real time from public market data.

    Quantitative Traders Monitoring Closed-End Fund Arbitrage

    Closed-end fund premiums are notoriously mean-reverting. When DXYZ’s premium spikes to 800% on momentum, it tends to compress back. When it dips on a market-wide selloff, it tends to recover. The API’s Bollinger Band and z-score analytics are purpose-built for this closed-end fund premium trading strategy. Track premium expansion/compression, identify regime changes, and build systematic mean-reversion models.

    VC/PE Analysts Tracking Public Market Sentiment

    If you’re in venture capital or private equity, implied valuations from DXYZ and VCX give you a real-time sentiment indicator for private companies. When the market implies SpaceX is worth $2T but the last round was $350B, that tells you something about public market appetite for space and Starlink exposure. Use this data to inform your own valuation models, LP communications, and market timing.

    Financial Journalists & Researchers

    Writing about the pre-IPO market? This API gives you verifiable, data-driven valuation estimates derived from public market prices โ€” not anonymous sources or leaked term sheets. Every number is mathematically traceable to publicly available fund data.

    Premium Features: What Pro and Ultra Unlock

    The free tier gives you the leaderboard, fund quotes, and basic holdings data โ€” more than enough to build a prototype or explore the data. But for production applications and serious quantitative work, the paid tiers unlock significantly more power:

    Pro Tier ($19/month) โ€” Analytics & Signals

    • Premium Analytics: Bollinger Bands, RSI, and mean-reversion signals on fund premiums
    • Risk Metrics: Value at Risk (VaR), portfolio concentration analysis, and regime detection
    • Historical Data: 500+ trading days of historical data for DXYZ, enabling backtesting and trend analysis
    • 5,000 requests/month with priority support

    Ultra Tier ($59/month) โ€” Full Quantitative Toolkit

    • Scenario Engine: Model “what if SpaceX IPOs at $X” and see the impact on fund valuations
    • Cross-Fund Cointegration: Statistical analysis of how DXYZ and VCX premiums move together (and when they diverge)
    • Regime Detection: ML-based identification of market regime shifts (risk-on, risk-off, rotation)
    • Priority Processing: 20,000 requests/month with the fastest response times

    Understanding the Data: What These Numbers Mean (And Don’t Mean)

    Before you start building on this data, it’s important to understand what implied valuations actually represent. These are not “real” valuations in the way a Series D term sheet is. They’re mathematical derivations based on how the public market prices closed-end fund shares.

    A few critical nuances:

    • Fund premiums reflect speculation, not fundamentals. When DXYZ trades at 665% premium to NAV, that’s driven by supply/demand dynamics in a low-float stock. The premium can (and does) swing wildly on retail sentiment.
    • NAV data may be stale. Closed-end funds report NAV periodically (often quarterly for private holdings). Between updates, the NAV is an estimate. The API uses the most recent available NAV.
    • The premium is uniform across holdings. When we say SpaceX’s implied valuation is $2T via DXYZ, we’re applying DXYZ’s overall premium to SpaceX’s weight. In reality, some holdings may be driving more of the premium than others.
    • Low liquidity amplifies distortions. Both DXYZ and VCX have relatively low trading volumes compared to major ETFs. This means large orders can move prices significantly.

    Think of these implied valuations as a market sentiment indicator โ€” a real-time measure of how badly public market investors want exposure to pre-IPO tech companies, and which companies they’re most excited about.

    Why This Matters: The Pre-IPO Valuation Gap

    We’re living in an unprecedented era of private capital. Companies like SpaceX, Stripe, and OpenAI have chosen to stay private far longer than their predecessors. Google IPO’d at a $23B valuation. Facebook at $104B. Today, SpaceX is raising private rounds at $350B and the public market implies it’s worth $2T.

    This creates a massive information asymmetry. Institutional investors with access to secondary markets can trade these shares. Retail investors cannot. But retail investors can buy DXYZ and VCX โ€” and they’re paying enormous premiums to do so.

    The AI Stock Data API democratizes the analytical layer. You don’t need a Bloomberg terminal or a secondary market broker to track how the public market values these companies. You need one API call.

    Getting Started: Your First API Call in 60 Seconds

    Ready to start tracking pre-IPO valuations? Here’s how:

    1. Sign up on RapidAPI (free): https://rapidapi.com/dcluom/api/ai-stock-data-api
    2. Subscribe to the Free tier โ€” 500 requests/month, no credit card needed
    3. Copy your API key from the RapidAPI dashboard
    4. Make your first call:
    # Replace YOUR_KEY with your RapidAPI key
    curl "https://ai-stock-data-api.p.rapidapi.com/companies/leaderboard" -H "X-RapidAPI-Key: YOUR_KEY" -H "X-RapidAPI-Host: ai-stock-data-api.p.rapidapi.com"

    That’s it. You’ll get back a JSON array of every tracked pre-IPO company with their implied valuations, source funds, and premium calculations. From there, you can build dashboards, trading signals, research tools, or anything else your imagination demands.

    The AI Stock Data API is the only pre-IPO valuation API that combines live market data, closed-end fund analysis, and quantitative analytics into a single developer-friendly interface. Try the free tier today and see what $7 trillion in hidden value looks like.


    Disclaimer: The implied valuations presented and returned by the API are mathematical derivations based on publicly available closed-end fund market prices and reported holdings data. They are not investment advice, price targets, or recommendations to buy or sell any security. Closed-end fund premiums reflect speculative market sentiment and can be highly volatile. NAV data used in calculations may be stale or estimated. Past performance does not guarantee future results. Always conduct your own due diligence and consult a qualified financial advisor before making investment decisions.


    Related Reading

    Looking for a comparison of all available finance APIs? See: 5 Best Finance APIs for Tracking Pre-IPO Valuations in 2026

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    Subscribe Free →

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    References

    1. Forbes โ€” “SpaceX Valuation Hits $137 Billion After Secondary Share Sale”
    2. Crunchbase โ€” “OpenAI Overview”
    3. SEC โ€” “10X Capital Venture Acquisition Corp SEC Filings”
    4. Nasdaq โ€” “Understanding Closed-End Funds”
    5. TechCrunch โ€” “Anthropic Raises $580M to Build Next-Gen AI Systems”
  • 5 Best Finance APIs for Tracking Pre-IPO Valuations in 2026

    5 Best Finance APIs for Tracking Pre-IPO Valuations in 2026

    Why Pre-IPO Valuation Tracking Matters in 2026

    ๐Ÿ“Œ TL;DR: Why Pre-IPO Valuation Tracking Matters in 2026 The private tech market has exploded. SpaceX is now valued at over $2 trillion by public markets, OpenAI at $1.3 trillion, and the total implied market cap of the top 21 pre-IPO companies exceeds $7 trillion .
    Quick Answer: The top 5 finance APIs for pre-IPO valuations in 2026 are AI Stock Data API, SEC EDGAR, Crunchbase, PitchBook, and CB Insights โ€” with the free AI Stock Data API offering the best pre-IPO coverage by deriving implied valuations from publicly traded closed-end funds like DXYZ and VCX.

    The private tech market has exploded. SpaceX is now valued at over $2 trillion by public markets, OpenAI at $1.3 trillion, and the total implied market cap of the top 21 pre-IPO companies exceeds $7 trillion. For developers building fintech applications, having access to this data via APIs is crucial.

    But here’s the problem: these companies are private. There’s no ticker symbol, no Bloomberg terminal feed, no Yahoo Finance page. So how do you get valuation data?

    The Closed-End Fund Method

    Two publicly traded closed-end funds โ€” DXYZ (Destiny Tech100) and VCX (Fundrise Growth Tech) โ€” hold shares in these private companies. They trade on the NYSE, publish their holdings weights, and report NAV periodically. By combining market prices with holdings data, you can derive implied valuations for each portfolio company.

    Top 5 Finance APIs for Pre-IPO Data

    1. AI Stock Data API (Pre-IPO Intelligence) โ€” Best Overall

    Price: Free tier (500 requests/mo) | Pro $19/mo | Ultra $59/mo

    Endpoints: 44 endpoints covering valuations, premium analytics, risk metrics

    Best for: Developers who need complete pre-IPO analytics

    This API tracks implied valuations for 21 companies across both VCX and DXYZ funds. The free tier includes the valuation leaderboard (SpaceX at $2T, OpenAI at $1.3T) and live fund quotes. Pro tier adds Bollinger Bands on NAV premiums, RSI signals, and historical data spanning 500+ trading days.

    curl "https://ai-stock-data-api.p.rapidapi.com/companies/leaderboard" \
     -H "X-RapidAPI-Key: YOUR_KEY" \
     -H "X-RapidAPI-Host: ai-stock-data-api.p.rapidapi.com"

    Try it free on RapidAPI โ†’

    2. Yahoo Finance API โ€” Best for Public Market Data

    Price: Free tier available

    Best for: Getting live quotes for DXYZ and VCX (the funds themselves)

    Yahoo Finance gives you real-time price data for the publicly traded funds, but not the implied private company valuations. You’d need to build the valuation logic yourself.

    3. SEC EDGAR API โ€” Best for Filing Data

    Price: Free

    Best for: Accessing official SEC filings for fund holdings

    The SEC EDGAR API provides access to N-PORT and N-CSR filings where closed-end funds disclose their holdings. However, this data is quarterly and requires significant parsing.

    4. PitchBook API โ€” Best for Enterprise

    Price: Enterprise pricing (typically $10K+/year)

    Best for: VCs and PE firms with big budgets

    PitchBook has the most complete private company data, but it’s priced for institutional investors, not indie developers.

    5. Crunchbase API โ€” Best for Funding Rounds

    Price: Starts at $99/mo

    Best for: Tracking funding rounds and company profiles

    Crunchbase tracks funding rounds and valuations at the time of investment, but doesn’t provide real-time market-implied valuations.

    Comparison Table

    FeatureAI Stock DataYahoo FinanceSEC EDGARPitchBookCrunchbase
    Implied Valuationsโœ…โŒโŒโœ…โŒ
    Real-time Pricesโœ…โœ…โŒโœ…โŒ
    Premium Analyticsโœ…โŒโŒโŒโŒ
    Free Tierโœ… (500/mo)โœ…โœ…โŒโŒ
    API on RapidAPIโœ…โœ…โŒโŒโœ…

    Getting Started

    The fastest way to start tracking pre-IPO valuations is with the AI Stock Data API’s free tier:

    1. Sign up at RapidAPI
    2. Subscribe to the free Basic plan (500 requests/month)
    3. Call the leaderboard endpoint to see all 21 companies ranked by implied valuation
    4. Use the quote endpoint for real-time fund data with NAV premiums

    Disclaimer: Implied valuations are mathematical derivations based on publicly available fund data. They are not official company valuations and should not be used as investment advice. Both VCX and DXYZ trade at significant premiums to NAV.

    Real API Examples: From curl to Python

    Let's get practical. Here are real API calls you can run today to start pulling pre-IPO valuation data. I'll walk through curl for quick testing, then Python for building something more permanent.

    curl: Quick Leaderboard Check

    # Get the full valuation leaderboard
    curl -s "https://ai-stock-data-api.p.rapidapi.com/companies/leaderboard" \
      -H "X-RapidAPI-Key: YOUR_KEY" \
      -H "X-RapidAPI-Host: ai-stock-data-api.p.rapidapi.com" | python3 -m json.tool

    A typical response looks like this:

    {
      "leaderboard": [
        {
          "rank": 1,
          "company": "SpaceX",
          "implied_valuation": "$2.01T",
          "fund_source": "DXYZ",
          "weight_pct": 28.5,
          "change_30d": "+12.3%"
        },
        {
          "rank": 2,
          "company": "OpenAI",
          "implied_valuation": "$1.31T",
          "fund_source": "DXYZ",
          "weight_pct": 15.2,
          "change_30d": "+8.7%"
        },
        {
          "rank": 3,
          "company": "Stripe",
          "implied_valuation": "$412B",
          "fund_source": "VCX",
          "weight_pct": 12.8,
          "change_30d": "-2.1%"
        }
      ],
      "metadata": {
        "last_updated": "2026-03-28T16:00:00Z",
        "total_companies": 21,
        "data_source": "SEC filings + market data"
      }
    }

    Python: Building a Tracking Dashboard

    import requests
    import pandas as pd
    
    RAPIDAPI_KEY = "your_key_here"
    BASE_URL = "https://ai-stock-data-api.p.rapidapi.com"
    HEADERS = {
        "X-RapidAPI-Key": RAPIDAPI_KEY,
        "X-RapidAPI-Host": "ai-stock-data-api.p.rapidapi.com"
    }
    
    def get_leaderboard():
        "Fetch the pre-IPO valuation leaderboard."
        resp = requests.get(f"{BASE_URL}/companies/leaderboard", headers=HEADERS)
        resp.raise_for_status()
        return resp.json()["leaderboard"]
    
    def get_fund_quote(symbol):
        "Get real-time quote for DXYZ or VCX."
        resp = requests.get(f"{BASE_URL}/quote/{symbol}", headers=HEADERS)
        resp.raise_for_status()
        return resp.json()
    
    # Build a tracking dashboard
    leaderboard = get_leaderboard()
    df = pd.DataFrame(leaderboard)
    print(df[["rank", "company", "implied_valuation", "change_30d"]].to_string(index=False))
    
    # Get live fund data with NAV premium
    for symbol in ["DXYZ", "VCX"]:
        quote = get_fund_quote(symbol)
        print(f"\n{symbol}: ${quote['price']:.2f} | NAV Premium: {quote['nav_premium']}%")

    SEC EDGAR: Free Holdings Data

    SEC EDGAR is completely free but requires a bit more work to parse. Here's how to pull the latest N-PORT filing for Destiny Tech100 (DXYZ):

    import requests
    
    # Get latest N-PORT filing for Destiny Tech100 (DXYZ)
    # CIK for Destiny Tech100 Inc: 0001515671
    CIK = "0001515671"
    url = f"https://efts.sec.gov/LATEST/search-index?q=%22destiny+tech%22&dateRange=custom&startdt=2026-01-01&forms=N-PORT"
    
    headers = {"User-Agent": "MaxTrader [email protected]"}
    resp = requests.get(url, headers=headers)
    
    # SEC requires User-Agent header โ€” they'll block you without one
    print(f"Found {resp.json().get('hits', {}).get('total', 0)} filings")

    Cost Comparison: What You'll Actually Pay

    Pricing is the elephant in the room. Here's what each API actually costs when you move past the free tier:

    APIFree TierStarterProEnterprise
    AI Stock Data API500 req/mo$9/mo (2,000 req)$19/mo (10,000 req)$59/mo (100,000 req)
    Yahoo Finance (via RapidAPI)500 req/mo$10/mo$25/moCustom
    SEC EDGARUnlimited (10 req/sec)โ€”โ€”โ€”
    PitchBookNoneโ€”โ€”~$15,000/yr
    CrunchbaseNone$99/mo$199/moCustom

    For an indie developer or small fintech startup, the realistic options are AI Stock Data API (best implied valuations), Yahoo Finance (best public market data), and SEC EDGAR (free but requires heavy parsing). PitchBook is institutional-grade and priced accordingly. Crunchbase is good for funding round data but doesn't do real-time valuations.

    I run my tracker on a $19/month Pro plan, which gives me enough requests to poll every 5 minutes during market hours. Total monthly cost including my TrueNAS server electricity: about $25.

    What I Learned Building a Pre-IPO Tracker

    I've been running a pre-IPO valuation tracker on my TrueNAS homelab since early 2026. Here's what I learned the hard way:

    1. NAV Premiums Are Wild

    DXYZ regularly trades at 200โ€“400% above NAV. The implied valuations include this premium, so SpaceX at "$2T" reflects what the market is willing to pay through DXYZ shares, not necessarily what SpaceX would IPO at. Always track NAV discount/premium alongside valuation. If you ignore the premium, you're fooling yourself about what these companies are actually worth on a fundamental basis.

    2. SEC EDGAR Data Is Stale

    Fund holdings are reported quarterly, sometimes with a 60-day lag. By the time the N-PORT filing drops, the portfolio might have changed significantly. Use SEC data for weight validation, not real-time tracking. I cross-reference EDGAR data with the live API to catch discrepancies โ€” when holdings weights diverge more than 5%, something interesting is probably happening.

    3. Rate Limiting Is Real

    SEC EDGAR will throttle you to 10 requests per second. RapidAPI enforces monthly quotas. If you don't handle this gracefully, your tracker will silently fail at the worst possible moment. Build in exponential backoff from day one:

    import time
    import requests
    
    def api_call_with_retry(url, headers, max_retries=3):
        for attempt in range(max_retries):
            resp = requests.get(url, headers=headers)
            if resp.status_code == 200:
                return resp.json()
            if resp.status_code == 429:  # rate limited
                wait = 2 ** attempt
                print(f"Rate limited. Waiting {wait}s...")
                time.sleep(wait)
                continue
            resp.raise_for_status()
        raise Exception(f"Failed after {max_retries} retries")

    4. Cache Aggressively

    Pre-IPO valuations don't change tick-by-tick like public stocks. A 5-minute cache is perfectly fine for this data. I store results in SQLite on my TrueNAS box โ€” simple, reliable, zero dependencies:

    import sqlite3
    import json
    from datetime import datetime, timedelta
    
    DB_PATH = "/mnt/data/trading/preipo_cache.db"
    
    def get_cached_or_fetch(endpoint, max_age_minutes=5):
        conn = sqlite3.connect(DB_PATH)
        conn.execute(
            "CREATE TABLE IF NOT EXISTS cache "
            "(endpoint TEXT PRIMARY KEY, data TEXT, fetched_at TEXT)"
        )
    
        row = conn.execute(
            "SELECT data, fetched_at FROM cache WHERE endpoint = ?",
            (endpoint,)
        ).fetchone()
    
        if row:
            fetched = datetime.fromisoformat(row[1])
            if datetime.now() - fetched < timedelta(minutes=max_age_minutes):
                return json.loads(row[0])
    
        # Cache miss โ€” fetch from API
        data = api_call_with_retry(f"{BASE_URL}{endpoint}", HEADERS)
        conn.execute(
            "INSERT OR REPLACE INTO cache VALUES (?, ?, ?)",
            (endpoint, json.dumps(data), datetime.now().isoformat())
        )
        conn.commit()
        return data

    5. Build Alerts, Not Dashboards

    After a week of staring at numbers, I realized what I actually wanted was alerts. "Tell me when SpaceX implied valuation crosses $2.5T" or "Alert when VCX NAV premium drops below 100%." A cron job plus a Pushover notification beats a fancy dashboard every time. Dashboards are for showing off; alerts are for making money. Set your thresholds, write a 20-line script, and let the machine watch the market while you do something more productive.


    Related Reading

    For a deeper dive into how implied valuations are calculated and a complete API walkthrough, check out: How to Track Pre-IPO Valuations for SpaceX, OpenAI, and Anthropic with a Free API

    Get Weekly Security & DevOps Insights

    Join 500+ engineers getting actionable tutorials on Kubernetes security, homelab builds, and trading automation. No spam, unsubscribe anytime.

    Subscribe Free →

    Delivered every Tuesday. Read by engineers at Google, AWS, and startups.

    References

    1. Crunchbase โ€” “Crunchbase API Documentation”
    2. CB Insights โ€” “CB Insights API Overview”
    3. PitchBook โ€” “PitchBook API Documentation”
    4. Nasdaq โ€” “Nasdaq Data Link API”
    5. Alpha Vantage โ€” “Alpha Vantage API Documentation”
Also by us: StartCaaS — AI Company OS · Hype2You — AI Tech Trends