About SmartQuant
We are a content and research platform for AI quant. Our scope is narrow: break institutional-grade quant methods into steps an individual can execute, and state the limits of every step just as clearly.
What We Do
- Strategy research — annualized return, max drawdown, win rate and Sharpe published under one unified backtest standard
- Signal reviews — entry, take profit, stop loss and the trigger logic published, with stopped-out trades kept on record too
- Quant education — 20 long-form articles, from basics to backtesting methods and risk management
- Airdrop research — treating airdrops as a business with costs, not as a rush to get on board
What We Do Not Do
This section matters more than the one above.
- No discretionary money management — we accept no custody of funds in any form
- No management fees — no cut based on assets under management or profits
- No buy or sell recommendations — we will not tell you which coin to buy or when to buy it
- No promises of returns — every figure is a historical backtest, not a guarantee about the future
Why We Stress the Limits
Crypto content has no shortage of profit screenshots and sales talk. We do the opposite: every strategy publishes its max drawdown, every tutorial spells out where the method fails, and all backtest data is labelled as including fees and slippage.
The cost is that the content looks less enticing. The benefit is that trusting us will not lose you money you should not have lost.
How the Content Is Produced
The backtest standard, fill-price rules and cost model are all published on the methodology page. Anyone can reproduce our numbers under the same standard — that is the only form of trust we are willing to accept.
Tools to Come
We are building AI quant tools (strategies, backtesting, signal alerts) and will keep a free tier after launch. The tools provide analysis only; trading decisions and their consequences always remain yours.