Search Results for "market analysis system"
Sort By:
Showing 2702 open source projects for "market analysis system"
View related business solutions-
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
1
Intelligent stock analysis system
LLM-driven A/H/US stock intelligent analyzer
Intelligent stock analysis system is a Python-based smart stock analysis system that leverages large language models to automatically analyze selected equities across A-shares, Hong Kong stocks, and U.S. markets. It’s designed to produce a daily “decision dashboard” summarizing key insights such as core conclusions, precise entry/exit points, and checklists for potential trades, combining multi-dimensional technical analysis, market sentiment, chip distribution, and real-time price data. ... -
2
Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and generating trading signals based on quantitative models. ... -
3
Smart Money Concepts
Discover our Python package designed for algorithmic trading
Smart Money Concepts is a Python library that implements advanced trading indicators based on the “Smart Money Concepts” methodology, which focuses on institutional market behavior and price action analysis. It is designed for algorithmic traders and quantitative analysts who want to incorporate professional trading strategies into automated systems. The library processes structured OHLC or OHLCV market data and computes indicators such as fair value gaps, order blocks, liquidity zones, and market structure changes. ... -
4
Fincept Terminal
FinceptTerminal is a modern finance application
Fincept Terminal is an open-source financial intelligence platform aimed at bringing powerful market analysis and investment research tools to a broad audience without the prohibitive cost of proprietary terminals. The project provides both command-line and graphical interfaces that let users access real-time market data, economic indicators, and advanced analytics directly from a unified terminal environment, supporting stocks, forex, commodities, and more. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
TradingGoose Studio
Technical analysis + LLM powered trading workflows
TradingGoose Studio is an open-source AI workflow platform designed to enable advanced financial trading analysis and automation through a visual, modular interface powered by large language models. It combines traditional technical analysis with modern AI-driven decision-making by allowing users to build workflows where multiple specialized agents collaborate to interpret market signals and execute actions. The platform supports end-to-end trading pipelines, starting from ingesting real-time market data and applying custom indicators, to generating insights and triggering automated trades or alerts. ... -
6
System Prompts Leaks
Collection of extracted System Prompts from popular chatbots
...By aggregating these prompts, the repository serves as a valuable resource for understanding how widely different models are being guided in the wild, which helps with comparative analysis across architectures and service providers. It also helps raise awareness around prompt security, showing how exposed system instructions can lead to unintended behaviors or exploitation if not properly protected. -
7
ValueCell
Community-driven, multi-agent platform for financial applications
ValueCell is a community-driven multi-agent AI platform focused on financial research, analysis, and decision-making that lets users leverage multiple specialized AI agents for tasks like data retrieval, investment research, strategy execution, and market tracking. The system brings together a suite of collaborative agents—such as research agents that gather and interpret fundamentals, strategy agents that implement trading logic, and news agents that deliver personalized updates—to help users make more informed financial decisions across stocks, crypto, and other markets. ... -
8
AutoHedge
Build your autonomous hedge fund in minutes
AutoHedge is an AI-driven financial automation system designed to simulate and manage hedging strategies using intelligent agents. The project focuses on applying autonomous decision-making to financial risk management, allowing agents to analyze market conditions and adjust positions dynamically. It is built around the concept of algorithmic hedging, where strategies are executed programmatically rather than manually, enabling faster and more consistent responses to market changes. ... -
9
FinGPT
Open-Source Financial Large Language Models
FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions rather than generic knowledge alone. The platform typically includes tools for fine-tuning, context engineering, and prompt templating, enabling users to build specialized assistants for tasks like sentiment analysis, earnings summary generation, risk profiling, trading signal interpretation, and document extraction from financial reports. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
Kronos
A Foundation Model for the Language of Financial Markets
Kronos is a specialized open-source foundation model designed for analyzing and predicting financial market data using time-series representations of candlestick patterns. It is built as a decoder-only Transformer model trained specifically on K-line data, which captures open, high, low, close, and volume information across multiple global exchanges. The system introduces a novel tokenization approach that converts continuous financial data into discrete tokens, enabling the model to process market behavior similarly to language. ... -
11
BTC Trading Since 2020
Public BTC trading context since 2020
BTC-Trading-Since-2020 is a cryptocurrency trading analysis project that focuses on evaluating Bitcoin trading strategies using historical data and algorithmic approaches. The repository serves as both a research and experimentation environment, allowing users to explore how different strategies perform under varying market conditions. It includes backtesting capabilities that enable users to simulate trades over historical Bitcoin price data, helping to identify profitable patterns and risk factors. ... -
12
Flowsurface
A native desktop charting platform for crypto markets
Flowsurface is a powerful open-source desktop charting platform tailored for crypto markets, built primarily in Rust with a focus on real-time data visualization and market microstructure analysis. Instead of traditional price charts alone, Flowsurface emphasizes order flow and liquidity visualization through advanced chart types like historical DOM heatmaps, footprint charts, and depth ladder displays. This enables traders and analysts to understand actual executed trades, liquidity distribution, and tempo changes that often precede significant market movements. ... -
13
Kalshi Trading Bot CLI
AI-native CLI for trading Kalshi prediction markets
Kalshi Trading Bot CLI is an AI-driven command-line tool designed to automate trading strategies on Kalshi prediction markets by combining quantitative modeling with real-time market data. It operates by conducting deep research on events, generating independent probability estimates, and comparing those estimates against current market prices to identify trading opportunities. The system incorporates advanced decision-making logic, including Kelly criterion-based position sizing and a structured multi-step risk evaluation process before executing trades. ... -
14
KIS Open API
Korea Investment & Securities Open API Github
The open-trading-api repository from Korea Investment & Securities provides sample code and developer resources for interacting with the KIS Developers Open Trading API, which enables programmatic access to financial market data and automated trading functionality. The project is designed primarily for Python developers and AI automation environments that want to build investment applications, algorithmic trading systems, or financial analytics tools using the brokerage’s infrastructure. It... -
15
ta4j
A Java library for technical analysis
Ta4j is an open-source Java library for technical analysis. It provides the basic components for the creation, evaluation, and execution of trading strategies. Ta4j is available on Maven Central. You can also download example code from the maven central repository. The wiki is the best place to start learning about ta4j. For more detailed questions, please use the issues tracker. We can calculate indicators over this bar series, in order to forecast the direction of prices through the study of past market data. ... -
16
Pants Build System
The Pants Build System
Pants 2 is a fast, scalable, user-friendly build system for codebases of all sizes. It's currently focused on Python, Go, Java, Scala, Kotlin, Shell, and Docker, with support for other languages and frameworks coming soon. A lot of effort has gone into making Pants easy to adopt, easy to use and easy to extend. We're super excited to bring Pants' distinctive features to Go, Java, Python, Scala, Kotlin, and Shell users. -
17
zvt
Modular quant framework
...Once you are familiar with the core concepts of the system, you can apply it to any target in the market. -
18
PowerTrader_AI
Fully automated crypto trading powered by a custom price prediction AI
PowerTrader_AI is a fully open-source, automated cryptocurrency trading bot that combines a custom price prediction AI with a structured and tiered dollar-cost averaging (DCA) strategy to make real trading decisions on behalf of users. It continuously analyzes market data to forecast high and low price levels across multiple timeframes, using those predictions to determine when to open, scale into, or close positions automatically, which aims to take emotion out of trading and enforce... -
19
Finance
150+ quantitative finance Python programs
Finance is a repository that compiles structured notes and educational material related to financial analysis, markets, and quantitative finance concepts. The project focuses on explaining key principles used in finance and investment analysis, including topics such as financial statements, valuation models, portfolio theory, and financial markets. The repository is designed as a study reference for students and professionals who want to understand financial systems and the analytical... -
20
NOFX
Open source AI trading OS for autonomous multi-model trading systems
NOFX is an open source AI-powered trading operating system designed to automate financial trading workflows using autonomous AI agents. It acts as an infrastructure layer that transforms market data into AI-driven trade decisions and execution. Instead of requiring users to manually configure machine learning models, data sources, and API integrations, the system allows AI components to perceive market conditions, select models, and perform trading actions automatically. ... -
21
EventStoreDB
The stream database optimised for event sourcing
...EventStoreDB is an open-source database technology that stores your critical data in streams of immutable events. It was built from the ground up for Event Sourcing, we believe that makes it the best solution in the market for building event-sourced systems. Event Sourcing offers some great benefits over state-oriented systems; the key ones are explained below. An event-sourced system stores your data as a series of immutable events over time, providing one of the strongest audit log options available. All state changes are kept, so it is possible to move systems backward and forwards in time which is extremely valuable for debugging and “what if” analysis. -
22
TradingAgents
Chinese Financial Trading Framework Based on Multi-Agent LLM
TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline. The project is oriented toward practical usage, including a stack that can be run in a modern development environment and commonly paired with containerized backends, configuration files, and service components. ... -
23
QuantDinger
AI-driven, local-first quantitative trading platform for research
QuantDinger is a local-first, open-source quantitative trading platform designed to bring AI-assisted analysis, strategy development, backtesting, and live execution into a self-hosted workspace where data and API credentials remain under your control. Unlike cloud-locked quant services, it lets users run the entire trading workflow on their own infrastructure using Docker, with a PostgreSQL database backend, a Python backend API, and a web frontend UI that supports visualization and strategy management. ... -
24
MiroFish
A Simple and Universal Swarm Intelligence Engine
MiroFish is a next-generation artificial intelligence prediction engine that leverages multi-agent technology and swarm-intelligence simulation to model, simulate, and forecast complex real-world scenarios. The system extracts “seed” information from sources such as breaking news, policy documents, and market signals to construct a high-fidelity digital parallel world populated by thousands of virtual agents with independent memory and behavior rules. Users can inject variables or conditions into this simulated environment from a “god’s eye view,” enabling iterative prediction of future trends under different assumptions, which can be useful for decision support, scenario planning, or creative exploration. ... -
25
Polymarket Data
Polymarket Data Retriever that fetches, processes, and structures data
Polymarket Data is a comprehensive data engineering pipeline designed to collect, process, and structure trading activity from the Polymarket prediction market ecosystem into analyzable datasets. The system operates as a multi-stage pipeline that integrates data from both off-chain APIs and on-chain event sources, enabling users to reconstruct full trading activity including markets, order events, and executed trades. It begins by fetching market metadata such as questions, outcomes, and trading volumes, then proceeds to scrape order-filled events from a GraphQL-based subgraph, and finally transforms these raw events into structured trade-level records with calculated prices and directions. ...
