FAQ
What is AI native algorithmic trading?
AI native algorithmic trading is an approach where AI sits at the core of the trading system rather than being added to a traditional rule-based platform. Unlike conventional algorithmic trading, which follows fixed pre-programmed rules, AI native systems learn from data and continuously adapt their quantitative trading strategies in real time.
What is algorithmic trading?
Algorithmic trading is the use of computer programs to make and/or execute trading decisions according to predefined, rules-based logic. It operates across two layers: the signal/strategy layer — the logic that decides what to buy or sell and when (e.g., stat arb, momentum, mean reversion, market making) — and the execution layer — the logic that decides how to fill that decision in the market once made (e.g., order slicing, smart order routing, minimizing slippage). Together, these remove manual discretion in favor of speed, consistency, and precision.
What is quantitative trading?
Quantitative trading is a strategy approach. It uses mathematical and statistical models to find trading opportunities — analyzing price history, volume, correlations, and other data to decide what to buy or sell and when. The emphasis is on the research and modeling side: building the signal that says "this is a good trade." Most modern systems are both — a quantitative model generates the signal, and an algorithm executes it automatically.
Is AI native algorithmic trading suitable for beginners?
Yes. Because AI native algorithmic trading platforms handle the modeling and execution automatically, beginners can access sophisticated quantitative trading strategies without writing code or building models from scratch. A solid understanding of the underlying risks is essential.