Key highlights

Authoritative trading data

FiinQuant directly integrates real-time market data from exchanges (HOSE, HNX, UPCOM), ensuring accuracy, transparency, and reliability for analysis, trading, and research applications.

Real-time WebSocket connection

FiinQuant supports stable and high-performance WebSocket connections, enabling:

• Receiving tick-by-tick data or updates in batches (e.g., 1s, 5s, 1min)

• Automatically pushing data to dashboards, bots, and alert systems

• Continuous synchronization with historical data to support complex systems

WebSocket is integrated for both price and order book modules.

Minute-level aggregated data

The system supports tick-by-tick data down to minute-level, with full timeframes of 1', 5', 15', 1h, 4h, and 1D, allowing users to call data directly without needing to maintain their own server systems for historical data storage.

Readiness for combining historical and real-time data

FiinQuant provides built-in functions for merging and synchronizing historical and real-time data, which makes strategy development, model backtesting, and trading deployment easier and smoother.

Smart cash flow data – real-time & historical

Includes proactive indicators such as:

• BU-SD: Net buy/sell value of institutional/proactive investors.

• Foreign Investors: Real-time and time-series activities of foreign investors.

This is useful for identifying significant capital flows and short-to-medium term market trends.

Integration of popular technical analysis (TA) indicators

The library comes with integrated indicator sets such as:

• MA, EMA, RSI, MACD, Bollinger Bands

• Breakout Signals, Divergence

• Volume Profile and other market behavior indicator groups

Advanced financial functions for professional investors

FiinQuant provides many utility functions ready for deployment:

• Stock prediction: Forecast stock price trends using ML (Machine Learning)

• Similar chart: Search for stocks with similar chart patterns

• Rebalance index: Rebalance index portfolios periodically or based on signals

• Factor models: Analyze factors influencing stock performance

• Continuously update other financial models periodically

Using the FiinQuant library is not merely about data retrieval; it's about utilizing an ecosystem of built-in quantitative tools designed for investors.