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Projects sharing features with Orderflow
21 open-source projects similar to focus1691/orderflow, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
- cryptosignal/crypto-signal
CryptoSignal/crypto-signal
5,578View on GitHubcrypto-signal is an automated cryptocurrency trading bot that generates buy and sell signals by running technical analysis on market data from multiple exchanges. The system is built around a config-driven signal pipeline that routes price data through a user-defined chain of indicators and thresholds, with analysis cycles triggered on a fixed schedule for continuous, hands-off monitoring. The project distinguishes itself through its modular, plugin-based indicator engine that allows technical analysis indicators to be added or removed without core changes, and its exchange-agnostic data laye
Python - jerbouma/financetoolkit
JerBouma/FinanceToolkit
4,449View on GitHubThe FinanceToolkit is an open-source Python library for quantitative finance that provides a unified framework for financial analysis, asset valuation, and risk management. It serves as a comprehensive platform for computing over 200 financial metrics and ratios, with capabilities spanning financial ratio analysis, fixed income analytics, macroeconomic data aggregation, options pricing, and portfolio risk management. The toolkit distinguishes itself through a modular architecture that separates data retrieval from computation, with stateless engines for financial models like Black-Scholes, GA
Pythoncommoditieseconomicsequities - jerbouma/fundamentalanalysis
JerBouma/FundamentalAnalysis
4,974View on GitHubFundamentalAnalysis is a comprehensive financial analysis library, quantitative finance framework, and macroeconomic data integrator. It provides tools for computing financial ratios, executing corporate health metrics, and pricing derivatives and bonds using mathematical models. The project integrates diverse data streams, including global economic indicators, real-time market quotes, and standardized corporate financial statements. It features a technical analysis engine for generating momentum and volatility indicators, as well as a portfolio performance analyzer for tracking risk-adjusted
Python
