AI-Trader
An AI-assisted trading workspace for crypto, forex, and equities—research, monitor, and automate in one place.
The product is currently in closed beta.
Markets we cover
One product to watch markets, explore ideas, and automate parts of your workflow.
Crypto
Digital assets and volatile markets.
Forex
Currency pairs and macro-driven regimes.
Stocks
Equities and systematic approaches.
Closed beta
We're rolling out access gradually and sharing updates as the product grows. If AI trading interests you, leave your email below.
Latest from the blog
Product notes, engineering updates, and news.
Main types of trading strategies in algorithmic trading
Algorithmic trading does not start with the question "where should I buy?" or with choosing an indicator. It starts with a hypothesis about why the market sometimes behaves non-randomly: it continues a move, reverts to an average, temporarily diverges between related instruments, pays for liquidity provision, or rewards the allocation of risk across assets.
5/5/2026
Backtesting: how to test trading strategies properly
Backtesting often looks like the most convincing stage of trading strategy development: load historical data, run the entry and exit rules, get an equity curve, calculate return and drawdown. If the chart rises, it is tempting to think the strategy has been proven.
4/25/2026
Data in trading: what data is used and where to get it
In algorithmic trading, the question "where do we get the data?" usually comes up too late. First comes the idea, then the search for quotes, then the backtest, and only after that does it become clear that the strategy in reality depends on data that was not actually present in the research setup. The result is a system that can look convincing on a chart and still be unusable in live execution.
4/19/2026