OmniMarket

AI-Driven Financial Research, Quantitative Strategy Analysis and Validation Platform

Grounded in history. Based on evidence. Understanding markets with AI.

OmniMarket is an AI quantitative research platform for quantitative and fundamental researchers: it organizes long-term company history, public disclosures and market data into verifiable research evidence, helping researchers understand how companies, industries and capital behavior change — and why. OmniMarket Academy complements it with quantitative research and trading discipline education.

Unlike tools that only present the latest data, OmniMarket studies long-term history to answer “why”, keeping a verifiable evidence chain for every conclusion.

Quantitative Analysis · Three Core Research Systems · Trading Discipline Education

Explore Capabilities Explore AstraWeave

Simulated Market · Daily · Price, Volume & MASIMULATED DEMO DATA

MA10MA30Key turning points (simulated)Volume (simulated)Time axis (simulated): T-72 → T0

Three Core Research SystemsConnecting market behavior, intelligent research and financial intelligence.

Capital Behavior

Quantitative Capital Behavior Models

One proprietary model system driven by three core indicators — CEI, MRI and CBM.

AstraWeave

Intelligent Financial Research Engine

Connecting company financials, capital behavior, industry change, market data and historical events into a traceable, comparable and continuously deepening research process.

GFI + ATI

Global Financial Information and the ATI Measure

GFI gathers public financial information from major global markets; ATI measures how strongly a state deserves further research.

Market — Industry — Company — Capital Behavior · structural links (background network is illustrative)

AI Products

OmniMarket AI & OmniMarket LLM

An AI product for financial research, and the language intelligence built into it.

OmniMarket AI

Financial Intelligence for Deeper Research.

An AI product for financial-market research: natural-language access to financial information, listed-company research, industry analysis and historical comparison.

Explore OmniMarket AI

OmniMarket LLM

14B Financial Research Language Model

Specialized 14-Billion-Parameter Financial Language Model · Internal Beta

Explore OmniMarket LLM

Personalized Research Platform

Your Brand. Your Research Models.

OmniMarket is a provider of AI quantitative research tools and technology services: standardized financial research tools, plus support for highly personalized research platforms built around your own brand and methodology.

Make the Platform Your Own

OmniMarket allows users to customize the display name of their research platform. Use your company name, institutional identity, or product brand to create a personalized quantitative research environment.

This capability is already available — a standard part of the platform today.

Build Research Models with AI

OmniMarket enables users to add custom research models tailored to their analytical needs. Through natural language interaction, users can guide AI to create, refine and customize research logic, turning their own research methodologies into personalized analytical tools.

Custom research models can be built around different research goals, for example:

Company fundamentals
Industry cycles
Capital behavior
Historical backtesting
Quantitative research indicators

Note: custom research models configure and generate research logic for your needs; they do not retrain the weights of the underlying large language model.

See the Flow

OmniMarket AI

The default platform name.

Rename the platform

Name it after your company, institution or product brand.

ABC Capital Research

A research environment under your own brand (naming example).

Add your own research models

Build and refine research logic with AI in natural language.

The steps above illustrate a product capability; “ABC Capital Research” is a naming example, not an actual customer case.

Core Product Advantages

AI quantitative research tools
Financial research data and historical analysis
Professional research methods and models
Custom platform name
Custom research models

Product

What is OmniMarket?

OmniMarket is an AI-driven intelligent quantitative research platform that helps researchers understand markets through long-term history, structured evidence and artificial intelligence.

What it is

A research platform built on the long-term history of companies and industries: annual reports, public disclosures and market data organized into searchable, verifiable research evidence.

Who it serves

Quantitative researchers, fundamental researchers, financial-data professionals, and individual learners studying quantitative research and trading discipline through OmniMarket Academy.

What it solves

Scattered data, inconsistent definitions, evidence that is hard to verify, conclusions without counterexample testing — upgrading "reading the latest data" into research along history and structure.

How it differs from market-data tools

Market-data tools answer “what is happening now”; OmniMarket asks “why it became this way and whether it happened before”: comparing across long-term history, keeping evidence sources and actively testing counterexamples.

How history connects with AI: the platform first turns public historical data into structured evidence (source, date, definition, verifiable quotes); AI then retrieves, compares and tests against that evidence, and every output must trace back to the original text.

How companies and industries are compared: longitudinally over time for one company (years of operations and ownership), and laterally across companies at the same point in time (industry and value-chain relationships); both support conclusions together.

How evidence supports or refutes conclusions: every conclusion keeps its evidence sources and confidence level; the system actively seeks evidence that does not support its initial judgment (counterexamples), and revises conclusions when new evidence appears.

Core Capabilities

Seven Core Capabilities, One Integrated Research System

OmniMarket integrates artificial intelligence, long-term financial history, company research, industry analysis, capital behavior and research memory into one unified platform, providing systematic analysis tools for investment research.

From long-term changes in company operations to industry competitive dynamics and to the historical behavior of capital holders, OmniMarket helps users understand the reasons behind market changes through interconnected research capabilities.

Among them, Capital Behavior, AstraWeave and GFI + ATI are OmniMarket’s three core research systems, presented in the sections below.

AI Research

Function: an AI-driven multi-step research process that organizes retrieval, comparison and testing around a research question.

Purpose: decompose research questions, retrieve historical evidence and actively test counterexamples.

User value: a verifiable research process instead of a one-shot answer.

Company Intelligence

Function: organizing operating, strategy and ownership evidence across years of company history.

Purpose: organize financial performance, strategy execution and ownership evidence across years.

User value: understand why a company became what it is today, beyond the latest statements.

Industry Intelligence

Function: studying industry cycles, competitive structure and long-term transformation.

Purpose: study industry cycles, competitive structure and long-term transformation, and trace how change transmits to companies.

User value: judge a company within its industry context, reducing isolated interpretations.

Capital Behavior

Function: characterizing disclosed capital behavior through the three core indicators CEI / MRI / CBM.

Purpose: organize disclosed holdings and capital activity history, studied against fundamentals and industry cycles.

User value: separate observable disclosure changes from actual trades, avoiding over-interpretation.

Research Memory

Function: keeping research records, evidence and hypotheses for later reuse.

Purpose: keep research records, evidence and hypotheses reusable and re-testable later.

User value: research accumulates instead of restarting from zero.

星衡经纬 Methodology

Function: a unified research methodology defining how research proceeds and is tested.

Purpose: a single methodology for all of the above — along history, across structures, tested by evidence.

User value: conclusions carry their sources and confidence, reviewable by one standard.

OmniMarket Academy

Function: a course system organizing structured learning paths.

Purpose: course catalog and learning directions for quantitative research, trading rules and trading discipline.

User value: build rule awareness and risk awareness alongside research methods.

Capital Behavior

Capital Behavior — Quantitative Capital Behavior Models

A capital behavior research system driven by three core indicators.

Capital Behavior is OmniMarket’s proprietary quantitative capital-behavior model system: based on public disclosures and market data, it computes per-stock quantitative characterizations of capital behavior, studied together with company fundamentals and industry cycles.

CEI · Capital Efficiency Index

What it studies: the efficiency state of capital deployment.

Quantitative role: produces a capital-efficiency score with its zone and direction.

Relationship: produced together with MRI and CBM by one capital-behavior computation.

User value: judge whether capital is deployed efficiently, giving research a quantitative starting point.

MRI · Market Resistance Index

What it studies: the market resistance state in price action.

Quantitative role: produces a market-resistance score with its zone and level.

Relationship: produced together with CEI and CBM by one capital-behavior computation.

User value: identify resistance, helping understand how easily prices can move.

CBM · Capital Behavior Matrix

What it studies: the overall state and multi-dimensional structure of capital behavior.

Quantitative role: produces a capital-behavior score, state and multi-dimensional structure.

Relationship: produced together with CEI and MRI by one capital-behavior computation.

User value: locate the overall state of capital behavior, cross-checking CEI and MRI.

The three indicators are produced together by one capital-behavior computation, forming a single system: efficiency, resistance and behavioral state are interconnected perspectives, not three unrelated technical indicators.

Disclosure boundary: a public shareholder list is not a complete portfolio; a shareholder leaving the top-ten list does not necessarily mean a full exit. The platform does not present incomplete disclosure data as definitive trading records.

What we study is not who bought which stock, but whether a connection between capital behavior and long-term corporate change can withstand the test of history.

Capital Leaves Traces. Research Seeks Meaning.

AstraWeave

AstraWeave — Intelligent Financial Research Engine

Connecting Evidence Across Time and Structure.

AstraWeave is OmniMarket’s intelligent financial research engine. It connects company financials, capital behavior, industry change, market data and historical events into a research process that is traceable, comparable and continuously deepening.

It does not merely aggregate information: around the research goal it conducts longitudinal historical comparison, lateral company-and-industry comparison, anomaly detection, hypothesis testing and counterexample testing, and forms evidence-based research judgments according to how reliable and complete the evidence is.

AstraWeave does not treat model-generated conclusions as facts. Through evidence verification, contradiction detection and continuous questioning, it improves the reliability of research results.

Intelligence That Questions Its Own Conclusions.

GFI + ATI

GFI + ATI — Global Financial Information and Research Trigger Measurement

The research value of global financial information and the ATI measure.

GFI · Global Financial Information

What it studies: public financial information across major global markets.

Coverage: official disclosures and news media from China, the United States, Europe, Japan, Asia and emerging markets.

Processing: information is collected, completed and verified, then read and organized item by item by AI.

User value: bringing scattered global public information into one research view.

ATI · AstraWeave Trigger Index

What it measures: how strongly a current state deserves further research (the 星衡触发指数).

Research role: focusing research attention on the changes worth digging into.

Boundary: ATI is not a buy or sell signal and not a return expectation; it measures research priority.

User value: helping researchers allocate attention by research value.

How they work together: GFI continuously gathers global financial information and keeps its history; on that basis ATI measures the strength worth further research, so the research process follows the global changes most worth digging into.

Research Methodology

XingHeng JingWei

From scattered signals to evidence-grounded understanding.

XingHeng JingWei is OmniMarket’s goal-driven research methodology. Starting from the research question, it organizes information scattered across companies, industries, time and data systems into traceable research relationships.

The system does not try to connect all data. Through historical comparison, evidence weighting, anomaly detection, hypothesis testing and counter-evidence checks, it seeks the connections that genuinely explain the question.

Data is no longer only collected — it forms verifiable research understanding around the question.

Goal · Relevance · Evidence · Network

Visual note: a goal-driven, explainable evidence network — only relationships that are relevant to the research goal and withstand evidence testing are kept; nodes with insufficient evidence remain unconnected.

Xing | The Myriad of Signals

Spotting the signals worth studying among scattered information.

Covers: companies / financials / shareholders / capital behavior / industries / policy / markets / historical events.

Heng | The Measure of Evidence

Data volume never substitutes for evidence quality.

Covers: evidence sources / reliability / historical comparison / anomaly detection / conflict checks / counterexample testing / evidence weighting.

Jing | The Axis of Time

Placing isolated facts back into history to see how change happened.

Covers: company history / capital investment / operating change / industry cycles / shareholder-structure evolution / sequences of historical events.

Wei | The Weaving of Relationships

Building explainable, cross-subject and cross-domain relationships centered on the research goal.

Covers: companies and industries / capital and operations / policy and markets / history and the present / signals and outcomes.

How XingHeng JingWei relates to Capital Behavior, AstraWeave and GFI + ATI: it is the research methodology that runs through all three core research systems, not a separate product alongside them.

Research Applications

Built on the three core research systems, OmniMarket provides applied capabilities for concrete research tasks.

AI Research

Purpose: decompose research questions, retrieve historical evidence and actively test counterexamples.

Research scenarios: testing whether a business judgment held historically; when anomalies appear, tracing comparable periods and their context.

User value: a verifiable research process instead of a one-shot answer.

Company Intelligence

Purpose: organize financial performance, strategy execution and ownership evidence across years.

Research scenarios: tracing a company’s transformation; comparing past strategic commitments with later operating results.

User value: understand why a company became what it is today, beyond the latest statements.

Industry Intelligence

Purpose: study industry cycles, competitive structure and long-term transformation, and trace how change transmits to companies.

Research scenarios: comparing divergence among companies within the same cycle; observing how competitive advantage shifts within an industry.

User value: judge a company within its industry context, reducing isolated interpretations.

Research Memory

Purpose: keep research records, evidence and hypotheses reusable and re-testable later.

Research scenarios: tracking a topic across time, revisiting earlier judgments against new evidence.

User value: research accumulates instead of restarting from zero.

Research Should Accumulate, Not Restart.

Research Output

Research Outputs and the Evidence Structure

Every research output follows one structure: conclusions, evidence, historical comparison and counterexamples.

Conclusions

Answers the research question directly, labeled with confidence and uncertainty.

User value: you know how reliable the conclusion is, not just what it says.

Evidence Chain

Every conclusion keeps its evidence sources, dates and definitions, traceable back to the original disclosure.

User value: the research process can be reviewed step by step, instead of taking conclusions on trust.

Historical Comparison

Conclusions come with comparable historical situations and a note on the key differences.

User value: understand the historical context and the limits within which the conclusion holds.

Counterexample Record

Evidence against the conclusion is recorded proactively, with how it was handled.

User value: avoid the bias of seeing only supporting material.

All charts on this site are simulated demo data and are clearly labeled; no fabricated product screenshots or research results are shown.

Multi-Device

OmniMarket — Research Anywhere

OmniMarket is building a multi-platform research experience spanning desktop browsers, Apple devices and Android devices, so that users can use intelligent financial research tools across different scenarios.

Web · Browser Version

A browser-based research experience for desktops and laptops, supporting large-screen information browsing, research content reading and multi-dimensional analysis.

macOS

Status: Planned

A research client for Mac desktop devices, planned and not yet available.

Apple · iOS / iPadOS

Status: In Beta Testing

A mobile research client for iPhone and iPad, offering an AI interaction experience designed for touch.

Android

Status: In Beta Testing

A client for Android phones and tablets, currently being adapted and refined.

Simulated Trading & Strategy Testing

OmniMarket — Simulated Trading & Strategy Testing

OmniMarket AI builds on financial-market data and research analysis to help users explore trading strategies, run historical backtests and simulation-based validation, and evaluate a strategy’s behavior, risks and applicable conditions across different market environments.

Historical Backtesting & Performance Evaluation

Backtest research strategies on historical data and evaluate performance indicators such as returns, drawdown and stability across different market environments.

Simulated Portfolios with Virtual Capital

Build simulated portfolios with virtual capital and validate entry and exit rules in paper trading, observing NAV and equity curves within a research environment that never touches real accounts or positions.

Bias Audit & Forward Validation

The research workflow includes look-ahead-bias audits and forward signal validation to help identify potential bias in backtesting and simulation.

The above capabilities are research, backtesting and simulation tools. They do not include live trading execution, and backtest or simulated results do not represent future actual trading performance.

Automation Extension

Self-Developed Trading Interfaces & Automation Extension

OmniMarket AI adopts an extensible research and strategy framework. Based on their own technical capability, practical needs and the interface conditions provided by their trading service providers, users may develop and connect real trading interfaces themselves and extend or upgrade their personal strategy workflows into automated trading systems.

The development of such interfaces, system deployment, trading-permission configuration, automated execution and risk control are the user’s own responsibility. OmniMarket AI does not thereby provide discretionary trading, custodial trading or any return-guarantee service.

Statement

Risk & Responsibility Statement

OmniMarket AI provides financial data research, AI analysis and strategy research tools. It does not constitute investment advice or a guarantee of returns; historical backtest and simulated-trading results do not represent future actual trading performance.

Automated trading systems that users develop, connect or upgrade themselves — including their trading decisions, program operation, interface configuration, account authorization, trade execution and related risks — are managed by, and the responsibility of, the users themselves. OmniMarket AI makes no guarantee regarding third-party trading systems developed by users or their trading results; responsibilities are governed by applicable law and the terms of service.

OmniMarket Academy

OmniMarket Academy is OmniMarket’s education product for quantitative research and trading discipline, organizing learning paths through a course system that covers financial fundamentals, quantitative research, trading rules, risk management and trading discipline.

Course System & Divisions

Courses organized by academy divisions: quantitative research learning, trading rules education and trading discipline training.

Learning Topics

Factors and signals, backtesting and strategy evaluation, A-share trading rules, position management, trade review and error attribution.

Who It Is For

Individual researchers working on quantitative or fundamental research, finance professionals, and learners who want to build systematic awareness of trading rules and discipline.

Learning Value

Build a complete research method from data to conclusions, and bring rules and discipline into everyday decisions.

The course catalog is public (academy divisions and course titles); course content and online learning are not open yet. Existing courses are taught in Chinese.

View the Academy overview and course catalog →

Access

Accessing OmniMarket

OmniMarket is accessed through the browser. Public channels: this website (Chinese / English) and the public OmniMarket Academy course catalog; the platform itself is open to authorized users.

Public sign-up is not open yet.

Our Story

Why we built OmniMarket

In markets, the easiest thing to obtain is the price; the hardest to understand is the history behind it.

A company's transformation may take more than a decade to show in market performance; an industry may enter a long adjustment after a boom; and a judgment that looks precise may turn out entirely different over a longer horizon.

If the history of companies, industries, markets and capital behavior is connected, financial research can get closer to the essence.

OmniMarket is built around this question: grounded in long-term historical data and structured evidence, conducting verifiable research with AI, and letting research accumulate over time.

We are equally clear about the limits: financial markets are uncertain, and no method can guarantee a correct judgment. The platform therefore separates facts, inferences and hypotheses, and states the limits of evidence and the uncertainty of conclusions honestly.

OmniMarket's goal is not to predict everything, but to let AI research more seriously.

Contact Center

OmniConnect

Connect with OmniMarket

General Inquiries

General questions, partnerships and business matters

contact@omnimarket.dev

Product Support

Product support and customer service

support@omnimarket.dev

For research collaboration, academy questions or product support, please reach us through the official email addresses above.