finalytics

Finalytics Python Binding

Finalytics is a high-performance Python binding for the Finalytics Rust library, designed for retrieving financial data, security analysis, and portfolio optimization.
It provides a fast, modular interface for advanced analytics, and powers dashboards and applications across platforms.

🚀 Installation

pip install finalytics

🐍 Main Modules

Finalytics Python exposes four core modules for financial analytics:

1. Screener

Efficiently filter and rank securities (equities, crypto, etc.) using advanced metrics and custom filters.

Usage Example:

from finalytics import Screener

screener = Screener(
    quote_type="EQUITY",
    filters=[
        '{"operator": "eq", "operands": ["exchange", "NMS"]}'
    ],
    sort_field="intradaymarketcap",
    sort_descending=True,
    offset=0,
    size=10
)
screener.display()

2. Ticker

Analyze a single security in depth: performance, financials, options, news, and more.

Usage Example:

from finalytics import Ticker

ticker = Ticker(
    symbol="AAPL",
    start_date="2023-01-01",
    end_date="2024-12-31",
    interval="1d",
    benchmark_symbol="^GSPC",
    confidence_level=0.95,
    risk_free_rate=0.02
)

ticker.report("performance")
ticker.report("financials")
ticker.report("options")
ticker.report("news")

3. Tickers

Work with multiple securities at once—aggregate reports, batch analytics, and portfolio construction.

Usage Example:

from finalytics import Tickers

symbols = ["AAPL", "MSFT", "GOOG"]
tickers = Tickers(
    symbols=symbols,
    start_date="2023-01-01",
    end_date="2024-12-31",
    interval="1d",
    benchmark_symbol="^GSPC",
    confidence_level=0.95,
    risk_free_rate=0.02
)

tickers.report("performance")

4. Portfolio

Optimize and analyze portfolios using advanced objective functions and constraints.

Usage Example:

symbols = ["NVDA", "GOOG", "AAPL", "MSFT", "BTC-USD"]
portfolio = Portfolio(
    symbols=symbols,
    benchmark_symbol="^GSPC",
    start_date="2023-01-01",
    end_date="2024-12-31",
    interval="1d",
    confidence_level=0.95,
    risk_free_rate=0.02,
    objective_function="max_sharpe"
)

portfolio.report("performance")

📚 Documentation

• See the Quarto documentation for full details.

🗂️ Multi-language Bindings

Finalytics is also available in:

• Rust
• Node.js
• Go
• Web Application

Finalytics — Modular, high-performance financial analytics for Python.