Search Results for "technical indicators"

FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. ...

...The interface blends real-time or near-real-time market data with personalized analytics, so users can assess portfolio health, diversification, and risk exposure with intuitive charts and tables. Beyond tracking, the platform offers educational insights and indicators (like technical or fundamental signals) that can inform investment decisions and help users recognize patterns or opportunities. Portfolios can be synced across devices, and users can set alerts for threshold events such as price moves or allocation shifts.

fastquant is a Python library designed to simplify quantitative financial analysis and algorithmic trading strategy development. The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common...

...The system analyzes historical stock price and volume data to detect anomalies that could indicate potential trading opportunities. By applying machine learning techniques to market indicators, the tool attempts to identify patterns in trading behavior that deviate significantly from normal market activity. These anomalies are interpreted as signals that a stock may soon experience a major upward or downward move. The framework includes modules for retrieving market data, computing technical indicators, and applying anomaly detection algorithms to identify unusual patterns. ...