Cuemacro Finmarketv0.3.3

Develop and backtest technical indicator strategies for G10 currency pairs (e.g., MACD crossover) using the framework. It supports multiple data sources and enforces next-bar execution to avoid look-ahead bias. Ideal for quantitative analysts evaluating FX trading systems.

Store large volumes of high-frequency tick data from FX markets into AWS S3 using ArcticDB and Parquet format for efficient compression and retrieval. This scenario enables scalable, cost-effective storage for historical tick data that can be accessed for backtesting or analytics.

Fetch economic and financial market data from Quandl (or other vendors) and cache it locally for repeated use. The framework handles data requests, field selection, and caching, reducing API calls and latency for market data consumers.

Run portfolio-level backtests on A-share, HK, or crypto assets using ZVT's pipeline from data collection to visualization. Supports custom factor computation and target selection, with strict semantic locks to prevent common pitfalls like look-ahead bias.

Develop and test quantitative strategies for A-share stocks, such as MA crossover or volume breakout, using free data sources like eastmoney or baostock. The framework guides users through data source selection, strategy parameters, and entity ID formatting.

Offer backtesting and data storage services to hedge funds and proprietary trading firms. The framework reduces development time for FX and equity strategies.

Provide high-frequency tick data storage and retrieval as a service (e.g., ArcticDB on S3). Clients pay for storage and compute when running historical analyses.

Use the framework to rapidly prototype and deliver custom trading strategies for clients. The consultancies leverage the integrated pipeline and lock system to ensure robust code.