ABOUT QUANDORA
Quandora gives your AI the market data and quantitative tools to turn investment ideas into tested strategies. Built for AI agents. Guided by you.
THE DEVELOPER / SINGAPORE
A Singapore-based hedge fund and financial technology company, bringing systematic investment research to the AI tools you already use.
01 / BUILT FOR AI
Quandora is an MCP service ↗. MCP gives AI applications a standard way to connect to external data and tools.
Through Quandora, your AI can access market data, mine factors, build strategies, run backtests and start paper trading. The core capabilities are designed for your AI to call, directly from your conversation.
You describe a goal or a hypothesis. Your AI uses Quandora to investigate it, then brings back code, results and evidence you can review.
Your AIThe conversation stays here
QuandoraYour AI’s research tools02 / THE INVESTMENT PHILOSOPHY
Two influential approaches to investing. Quandora puts AI to work on the systematic, data-driven side.
FUNDAMENTAL / VALUE INVESTING
What is this
business worth?
Berkshire HathawayINC.
SYSTEMATIC / QUANTITATIVE INVESTING
Is there a repeatable
edge in the data?
A simplified comparison of investment philosophies. The questions are illustrative summaries, not quotations.
AI proposes the idea. Data tests it. Rules turn it into a portfolio.
We apply the data-driven philosophy associated with Jim Simons, using our own research tools and models.03 / A GLOBAL INVESTMENT UNIVERSE
Quandora is designed to research global assets and build portfolios across them. Spot markets and derivatives provide different routes to that exposure.
Companies & sectors
Indices & baskets
Metals & energy
Digital assets
Buy and hold an available asset directly through a supported venue.
Spot markets ↗Take long or short exposure through a contract linked to an underlying asset, without owning it directly.
Perpetual futures ↗Asset coverage depends on available data, supported instruments and your venue. Derivatives have their own funding, basis and liquidation risks.
04 / FROM SIGNALS TO A PORTFOLIO
Quandora uses a factor-based investment approach. Your AI turns market data into signals, tests those signals and combines them into a long–short portfolio.
THE SIGNAL
A measurable characteristic used to compare assets. Momentum, for example, asks whether recent relative price strength helps explain future performance. A model can combine several factors into a score.
Illustrative factor scores · not returns
Factor investing ↗THE PORTFOLIO
Buy assets with stronger signals and short those with weaker signals. The strategy seeks to benefit when the long basket outperforms the short basket, whether the overall market rises or falls.
Relative performance drives the idea.
Long–short investing ↗THE OBJECTIVE
Balance long and short market exposures so the portfolio relies less on the market’s overall direction. Position sizing and risk controls aim to keep that exposure near its target as markets change.
An exposure target, not a return guarantee.
Market neutrality ↗Equal long and short dollar amounts alone do not ensure market neutrality. Correlations, market sensitivity and trading costs matter, and a market-neutral portfolio can still lose money.
Mine high quality factors. Then combine the ones that work together.
Your agent hunts for new signals and grades each one across every year of data.
Your agent tests the combinations and shows you which ones hold up year after year.
Consistency is a research target, not a promise. Annual and rolling comparisons depend on available data. Backtests do not guarantee future returns.
05 / YOUR STARTING POINT
Connect Quandora to your AI, then choose how you want to explore.
NEW TO QUANDORA
Use your AI’s Goal Mode, where available, or give it a Quandora task. Let it choose from available official factors and strategies, run a backtest and check readiness for paper trading.
Use Goal Mode, if available, to build my first Quandora strategy with official factors. Aim for steadier performance across bull and bear markets, a maximum drawdown below 20% and a Sharpe ratio of at least 1.2. Backtest it, explain any unmet targets and check whether it is eligible for paper trading.
HAVE A RESEARCH IDEA?
Explore the available datasets. Describe your hypothesis to your AI, turn it into a factor and use market data to test it. Review the evidence, refine the idea and test again.
Show me the market data available in Quandora. I want to test whether strong price momentum with rising volume predicts relative outperformance. Build a factor, check data coverage and look-ahead bias, then backtest it with costs and explain where the idea fails.
Research targets are preferences, not promised outcomes. Backtests and paper trading do not guarantee future returns.
Your next investment idea starts with a conversation.
Join Quandora