Portfolio Analytics

StockAPIS gives you real-time marks, P&L, and exposure across crypto and equity holdings from a single normalized feed spanning 80+ exchanges, brokers, and market-data providers.

Stop reconciling positions across a dozen venues by hand. Pull live prices, OHLCV history, and order-book depth through one API and compute portfolio value the instant the market moves.

The Portfolio Analytics Challenge

Tracking a multi-asset portfolio means following hundreds of instruments across exchanges, brokers, and data vendors — each with its own symbology, latency, and quirks.

Fragmented Pricing

• Logging into multiple exchange and broker dashboards to read marks
• Copying last-trade prices into spreadsheets per position
• Hours spent rebuilding portfolio value each day
• High risk of stale quotes and manual entry errors

Stale Marks

• Waiting on end-of-day files instead of streaming prices
• Outdated NAV affecting allocation and risk decisions
• Missing intraday moves on volatile crypto pairs
• Difficulty justifying valuations to LPs or risk committees

Fragmented Market Intelligence

• No unified view of P&L across crypto and equities
• Cannot easily compare venues or spot the best execution price
• Limited visibility into news and sentiment moving each holding
• Hard to forecast exposure when data lives in silos

Inefficient Operations

• Cannot mark all positions to market simultaneously
• Manual monitoring of order-book depth before sizing trades
• Time-consuming reporting for investors and auditors
• Difficulty scaling coverage as the book grows

Limited Cross-Venue Visibility

• No systematic way to track the same asset across Binance, Coinbase, and NYSE-listed proxies
• Missing arbitrage and rebalancing signals across markets
• Cannot benchmark portfolio returns against indices
• Incomplete data on liquidity and on-chain flows

The StockAPIS Solution

StockAPIS provides a unified analytics layer with automated, normalized data collection from 80+ crypto exchanges, stock exchanges, brokers, and financial-data APIs worldwide.

Key Capabilities

• Real-Time Marks: Streaming last-trade and mid prices for every position
• P&L Tracking: Unrealized and realized P&L computed from a single feed
• Multi-Asset Analytics: One dashboard for crypto, equities, and ETFs
• Exposure Breakdown: Net and gross exposure by asset, sector, and venue
• Liquidity Checks: Order-book depth and spreads before you rebalance
• Benchmarking: Compare returns against indices and on-chain metrics
• Investor Reporting: Generate position and NAV reports in minutes

Data Coverage

Access prices, OHLCV, order books, news, and sentiment from sources including:

• Crypto Exchanges: Binance, Coinbase, Kraken, Bybit, OKX
• Stock Exchanges & Brokers: NYSE, CME Group, Interactive Brokers, Robinhood
• Data APIs: Polygon, Alpha Vantage, Finnhub, Twelve Data, Yahoo Finance
• News & Signals: Bloomberg, Reuters, CNBC, StockTwits, Reddit
• 80+ total sources with consistent, normalized symbology — see all platforms

How It Works

Mark Positions to Market

Pull live prices across every holding in one pass:

from stockapis import StockAPIS
 
api = StockAPIS(api_key='your_api_key')
 
# Define portfolio positions (symbol, venue, quantity)
positions = [
    ('BTC-USD', 'binance', 1.5),
    ('ETH-USD', 'coinbase', 12.0),
    ('AAPL', 'nyse', 200),
]
 
# Mark each position to market
for symbol, venue, qty in positions:
    quote = api.platforms.get_quote(venue, symbol)
    market_value = quote.last * qty
 
    print(f"\n{symbol} @ {venue}")
    print(f"  Last: ${quote.last:,.2f}")
    print(f"  Market Value: ${market_value:,.2f}")

Compute P&L

Track unrealized P&L against your cost basis:

# Position with cost basis
symbol, venue, qty, cost_basis = 'BTC-USD', 'binance', 1.5, 58000.00
 
quote = api.platforms.get_quote(venue, symbol)
 
market_value = quote.last * qty
cost = cost_basis * qty
pnl = market_value - cost
pnl_pct = (pnl / cost) * 100
 
print(f"Cost Basis: ${cost:,.2f}")
print(f"Market Value: ${market_value:,.2f}")
print(f"Unrealized P&L: ${pnl:,.2f} ({pnl_pct:.1f}%)")

Check Liquidity Before Rebalancing

Read order-book depth so you size trades against real liquidity:

# Pull top-of-book depth for an asset
book = api.platforms.get_order_book('binance', 'BTC-USD', depth=20)
 
best_bid = book.bids[0].price
best_ask = book.asks[0].price
spread = best_ask - best_bid
bid_liquidity = sum(level.size for level in book.bids)
 
print(f"\nBTC-USD Order Book")
print(f"  Best Bid / Ask: ${best_bid:,.2f} / ${best_ask:,.2f}")
print(f"  Spread: ${spread:,.2f}")
print(f"  Bid Depth (20 levels): {bid_liquidity:,.4f} BTC")

Track Exposure and Trends

Pull OHLCV history to monitor exposure drift across markets:

# Get daily OHLCV for portfolio assets
assets = [('BTC-USD', 'binance'), ('ETH-USD', 'coinbase'), ('AAPL', 'nyse')]
 
for symbol, venue in assets:
    candles = api.platforms.get_ohlcv(venue, symbol, interval='1d', limit=30)
 
    first_close = candles[0].close
    last_close = candles[-1].close
    change_pct = ((last_close - first_close) / first_close) * 100
 
    print(f"\n{symbol} @ {venue} (30d)")
    print(f"  Close: ${last_close:,.2f}")
    print(f"  30d Change: {change_pct:.1f}%")

Surface News and Sentiment

Catch the headlines and social signals moving each holding:

# Pull recent news and sentiment for portfolio symbols
for symbol in ['BTC-USD', 'AAPL']:
    news = api.platforms.get_news(symbol, limit=5)
 
    print(f"\n{symbol} — latest headlines")
    for item in news:
        print(f"  [{item.sentiment}] {item.source}: {item.headline}")

Quick Start

from stockapis import StockAPIS
 
api = StockAPIS(api_key='your_api_key')
 
# Mark a single position
quote = api.platforms.get_quote('binance', 'BTC-USD')
 
print(f"Symbol: BTC-USD")
print(f"Last Price: ${quote.last:,.2f}")
print(f"24h Change: {quote.change_pct:.1f}%")

For detailed code examples and advanced usage, see our API getting started guide, explore the crypto exchange and financial data API integrations, or contact us about pricing.