fasiondog/hikyuu

Features

• Trading Strategy Backtesters - Provides a comprehensive engine for simulating trading strategy performance using historical data with realistic costs.
• Backtesting Engines - Simulates trading strategy performance on historical data with realistic slippage and transaction costs.
• Technical Indicator Calculators - Calculates and processes technical indicators and quantitative factors to identify market trends.
• Factor Analysis - Evaluates and manages financial factors to determine their specific impact on asset pricing.
• Factor Time Series Generation - Manages the creation, storage, and batch calculation of quantitative factors with serialization and date alignment.
• Algorithmic Asset Selection - Identifies target stocks from a universe based on quantitative signals, multi-factor scores, and fixed criteria.
• Automated Trading Engines - Bridges quantitative models with brokerage accounts for real-time order execution and portfolio management.
• Automated Trading Execution - Connects quantitative models to brokerage interfaces for automated live market order execution.
• Financial Portfolio Management Systems - Manages asset allocation and security selection across multiple trading systems using custom weight algorithms.
• Live Trading Execution - Connects strategy signals to real-world brokerage accounts for real-time trade execution.
• Quantitative Trading Platforms - Offers an integrated platform for developing, backtesting, and executing high-speed quantitative trading strategies.
• Quantitative Signal Generators - Identifies buy and sell opportunities using technical indicators, crossovers, and custom boolean logic.
• Systematic Strategy Composition - Combines signal indicators, risk controls, and money management to build a complete, systematic trading system.
• Systematic Trading Development - Implements a comprehensive system for the design, implementation, and modular composition of automated trading rules.
• Performance Evaluation - Generates detailed performance statistics, including equity curves and drawdown, to evaluate strategy effectiveness.
• Trading Strategy Execution Engines - Coordinates trading logic by managing account assets, tracking orders, and interfacing with market data.
• Time Series Data Storage - Provides optimized storage and retrieval for financial time-series K-line data and price history.
• Tick Data Retrieval - Implements high-frequency tick-level data handling and retrieval for precise transaction analysis.
• Cross-Sectional Transformations - Implements statistical normalization techniques like z-scoring and ranking across asset cohorts to determine relative rankings.
• Financial Data Import - Provides tools for downloading and loading historical K-line, dividend, and financial data from external sources.
• Financial Data Processing - Implements a high-performance pipeline for importing and processing large volumes of K-line and tick data.
• Candlestick Data Processing - Converts financial time-series records into arrays or data frames specifically for technical analysis.
• Financial Time-Series Libraries - Ships a comprehensive engine for managing K-line data, calculating technical indicators, and performing factor analysis.
• Security Metadata Management - Manages critical financial security information including stock instances, market details, and trading calendars.
• Quantitative Factor Definitions - Allows the creation of custom financial factors using technical indicators or mathematical formulas.
• Asset Allocation Optimization - Distributes capital across assets using fixed weights, amounts, or factor-based proportions.
• Corporate Action Price Adjustments - Calculates adjusted price and volume sequences based on stock dividends and rights issue data.
• Indicator Computation Engines - Utilizes a high-performance engine to compute indicator values for securities across defined time ranges.
• Multi-Factor Research Models - Provides tools for creating and scoring quantitative factors to rank securities and identify market trends.
• Parallel Financial Computation - Processes millions of data points in milliseconds using a multi-threaded core for high-speed financial calculations.
• Quantitative Financial Modeling - Provides high-speed computing tools for developing and simulating quantitative financial models and trading strategies.
• Technical Indicator Engines - Provides a dedicated engine for computing financial metrics such as moving averages and volatility.
• Backtesting Simulations - Ships an event-driven simulation environment to validate trading strategies by reacting to discrete market events.
• Multi-Core Parallelization - Utilizes a high-speed multi-core parallelization engine to process millions of data points for technical indicator generation.
• Asset Filtering Engines - Selects assets based on quantitative scoring criteria such as rank percentiles and minimum trading volume.
• Walk-Forward Optimizers - Evaluates trading strategy robustness by sequentially training and testing on rolling historical time windows.
• Factor Collection Management - Groups multiple quantitative factors into named sets to organize and retrieve related indicators for batch processing.
• Factor Data Persistence - Saves factor metadata and computed values to a database to avoid redundant calculations of complex indicators.
• Factor Normalization - Provides tools to standardize and neutralize factor data across securities to ensure comparability during scoring.
• Strategy Portfolio Grouping - Coordinates asset selection and weighting by grouping strategies into portfolios for multi-account execution.
• Abstract Broker Interfaces - Provides an architectural abstraction layer that decouples trading research logic from specific brokerage API implementations.
• Stock Trade Executions - Executes buy, sell, and short operations while tracking cash and positions across a timeline.
• Multi-Strategy Capital Allocation - Distributes capital and calculates trading units based on risk parameters or fixed capital allocations.
• Automated Exit Strategies - Automates trade exits using stop-loss and take-profit strategies based on price levels or percentages.
• Multi-Asset Holdings Trackers - Tracks position details, buy-sell frequencies, and manages the export of financial holding records.
• Risk Management Tools - Controls position sizing and risk through specialized capital allocation algorithms and fund managers.
• Pluggable Market - Uses a pluggable data source abstraction to persist market data across multiple backends for balanced performance.
• Candlestick Charts - Generates flexible candlestick charts to analyze market trends across non-standard timeframes.
• Financial Market Visualizers - Provides interactive financial market visualization for rendering K-line charts and technical indicators.
• Financial Time-Series Analysis - Analyzes quantitative trends by calculating rank proportions and signed power operations on financial time-series.
• Market Data Event Handlers - Triggers custom callback functions automatically when market quotations change or new data is received.
• Market Data Providers - Provides interfaces for fetching historical and real-time price and volume data for specific securities.
• Pluggable Storage Engines - Features a pluggable storage architecture allowing developers to swap database engines for optimizing financial data read-write speeds.
• Strategy Result Visualizers - Renders K-lines, indicators, and trade signals in an interactive environment for strategy validation.
• Trading Signal Plotting - Marks buy and sell signals and market environment judgments directly on financial charts.
• Composite Signal Models - Implements algorithms for combining multiple financial factors into composite signals using weighted or equal-weight methods.
• Multi-Factor Scoring - Combines multiple financial factors using weighted or equal-weight algorithms to determine asset rankings.
• Stock Order Placements - Submits buy or sell orders for equities specifying shares, lots, or portfolio percentages.
• Portfolio Performance Metrics - Calculates equity curves, maximum drawdown, and periodic profit percentages to evaluate strategy effectiveness.
• Trade Performance Analyzers - Analyzes simulated trade performance and asset growth to identify the best trading system from a candidate pool.
• Risk Management Simulations - Implements capital allocation and position sizing mechanisms to manage portfolio risk and control drawdowns.
• Slippage Simulators - Applies distribution algorithms to model realistic order execution prices and market impact during backtesting.
• Indicator Suite Aggregators - Combines data from multiple time intervals to generate aggregate indicators for comprehensive market analysis.
• Financial Data Buffering - Balances memory usage and access speed through configurable lazy-loading and preloading of financial data.
• Modular Program Composition - Provides a modular architecture to combine signal, risk, and fund management components into complex trading systems.
• Polyglot Component Models - Supports loading strategy logic and factor libraries written in different languages to extend functionality without recompilation.
• Security Selection Filters - Selects stocks based on specific criteria, blocks, or multi-factor rankings using cross-sectional scoring.
• Trading and Backtesting - High-performance C++/Python quant framework.
• Trading Frameworks - C++/Python framework for quantitative research and trading.

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