Research Firm Runs Cross-Venue Crypto Analysis

A boutique crypto research firm used StockAPIS to merge prices, OHLCV, order books, and on-chain signals from 30+ venues into one normalized feed — expanding asset coverage 8x while cutting data costs by 55%.

Company Profile

Industry: Crypto and digital-asset market research
Products: Cross-venue market reports and quantitative analytics subscriptions
Clients: Hedge funds, prop trading desks, and institutional allocators
Team Size: 7 analysts and quants

The Challenge

The firm published liquidity and arbitrage research covering 4 major exchanges, paying for separate market-data subscriptions on each. Clients wanted coverage across the full venue landscape — centralized exchanges, derivatives venues, and on-chain markets — which meant a near-linear blowup in data costs and integration work.

Key Problems

Data costs: ~$9K monthly for just 4 venues
Expanding to 30+ venues would have pushed spend past $70K monthly
Each exchange exposed a different REST/WebSocket schema for prices and order books
No single source for normalized OHLCV across spot and perpetuals
On-chain and news/sentiment data lived in entirely separate pipelines
Manual reconciliation of symbols and timestamps consumed ~110 analyst hours/month

The Solution

The firm replaced its patchwork of per-exchange subscriptions with a single StockAPIS integration spanning crypto exchanges, crypto data providers, financial news, and social signals.

Implementation

Built a unified cross-venue analytics layer:

Normalized spot and perpetual prices across 30+ venues (Binance, Coinbase, Kraken, Bybit, OKX, and more)
Standardized OHLCV and order-book snapshots into one schema
On-chain metrics joined to market data on a common asset key
News and sentiment signals attached to each asset timeline
Automated cross-venue spread, basis, and liquidity reports

Cross-Venue Analysis System


from stockapis import StockAPIS
 
api = StockAPIS(api_key='api_key')
 
# Universe of venues to compare
venues = load_target_venues()  # 30+ centralized & on-chain venues
 
def build_asset_report(symbol):
    # Pull normalized order books across all venues
    books = api.platforms.crypto_exchanges.get_order_books(
        symbol=symbol,
        venues=venues,
    )
 
    # Daily OHLCV for trend + volatility context
    ohlcv = api.platforms.crypto_data.get_ohlcv(symbol=symbol, interval='1d')
 
    # On-chain + sentiment overlays
    onchain = api.platforms.crypto_data.get_onchain_metrics(symbol=symbol)
    sentiment = api.platforms.social_signals.get_sentiment(symbol=symbol)
 
    report = {
        'symbol': symbol,
        'best_bid': max(b.bid for b in books),
        'best_ask': min(b.ask for b in books),
        'cross_venue_spread': calc_spread(books),
        'volatility_30d': calc_volatility(ohlcv),
        'active_addresses': onchain.active_addresses,
        'sentiment_score': sentiment.score,
    }
 
    return report
 
# Generate reports across the full asset universe
for symbol in load_asset_universe():
    report = build_asset_report(symbol)
    publish_to_client_portal(report)

See the API getting-started guide for the full client and authentication setup.

Results

Coverage and Cost

Venues Covered: Expanded from 4 to 30+ (8x increase)
Data Cost: Reduced from $9K to $4K monthly (55% reduction)
Time Saved: ~95 analyst hours monthly on data wrangling
Data Quality: One normalized schema for prices, OHLCV, and order books
Historical Depth: Multi-year OHLCV access for backtesting and trend work

Business Impact

New Clients: 38 additional subscriptions in 12 months
Revenue Growth: ~$480K additional annual revenue
Profit Margin: Improved from 42% to 64%
Market Position: Became a reference source for cross-venue liquidity research
Competitive Advantage: Broader venue coverage than incumbents at lower cost

Client Impact

Cleaner arbitrage and basis signals across spot and perpetuals
Coverage of long-tail tokens and secondary venues
On-chain and sentiment context alongside market data
Faster turnaround on bespoke research requests

Product Features

Venue Rankings

Rank 30+ venues by:

Liquidity depth at top of book
Cross-venue spread
Volume and turnover
Funding and basis on perpetuals

Comparative Analysis

Side-by-side comparison of:

Multiple venues for the same asset
Spot vs. derivatives pricing
Historical liquidity and volatility trends

Custom Reports

Automated generation of:

Daily liquidity and spread snapshots
Weekly basis and funding analysis
Bespoke client research on specific assets or venues

Client Dashboard

Self-service portal with:

Real-time normalized prices and order books
Custom alerts on spreads, funding, and sentiment shifts
Export to CSV and downstream quant pipelines

Key Learnings

What Worked

A single normalized schema removed weeks of per-exchange integration work
One feed across spot, perps, and on-chain enabled true cross-venue signals
Sentiment and news overlays became a clear differentiator
Broader venue coverage attracted larger, more demanding clients

Best Practices

Normalize symbols and timestamps once, at ingestion, not per report
Treat on-chain and sentiment as joinable overlays on the price timeline
Automate routine spread and basis reporting
Give clients self-service export into their own models

Testimonial

“StockAPIS let us go from 4 exchanges to 30+ venues on one feed while cutting data costs by 55%. We became the go-to source for cross-venue liquidity intelligence.”

— Head of Research

Implementation Timeline

Week 1: API integration and symbol normalization
Week 2: Built cross-venue order-book and OHLCV pipeline
Week 3-4: Added on-chain and sentiment overlays, built dashboard
Week 5: Migration off per-exchange subscriptions
Week 6: Launch of expanded venue coverage
Month 3: 30+ venues fully operational

Client Testimonial

“Their cross-venue spread and funding data surfaced arbitrage windows we were missing on single-exchange feeds. The ROI has been exceptional.”

— Quant Fund Client

Get Started

Building cross-venue crypto research products? Start with the Binance integration, explore all supported platforms, check pricing, or contact us.