GaiaEx
10 сабақтың 4-і
beginner7 minТест қосылған

AI Foundations

AI Trading Bots

Neural networks, LLMs, and machine learning for markets.

Updated 2026 ж. 21 қаз.GaiaEx Academy Editorial

Бұл сабақта

  • What an AI trading bot needs
  • How to test before going live

Негізгі тұжырымдар

  1. 1Pair any bot with strict risk management
  2. 2Backtest and paper-trade before risking capital
  3. 3No model removes market risk

Сабақ қорытындысы

An AI trading bot combines signals, automation, and execution.

Mental model

AI Trading Bots in plain terms

An AI trading bot combines signals, automation, and execution. The automation is useful only if risk limits are stricter than the model's confidence.

  • What an AI trading bot needs
  • How to test before going live

Mechanics

How to reason about AI trading bots

The bot needs data ingestion, signal generation, order execution, monitoring, and kill switches.

AI can assist with classification, summarization, or strategy selection.

The trading system still needs deterministic risk controls.

  • Pair any bot with strict risk management
  • Backtest and paper-trade before risking capital
  • No model removes market risk

Example

Seeing AI trading bots in action

A bot that increases size after bullish news should still cap exposure, reject stale data, and stop trading if spreads widen.

Есте сақтаңызDecision rule: Never let an AI bot place trades that a fixed risk engine would reject.

Common mistakes

What to unlearn about AI trading bots

Users often treat AI as an oracle. In markets, the model can be wrong exactly when volatility and leverage make mistakes expensive.

Risk notes

Staying safe around AI trading bots

Bad data, prompt injection, API failure, runaway orders, and model drift can create fast losses.

  • Define max position and daily loss.
  • Test with paper trading.
  • Add stale-data and emergency-stop checks.

Practice

Make AI trading bots stick

  • Define max position and daily loss.
  • Test with paper trading.
  • Add stale-data and emergency-stop checks.

Қайталау

Негізгі терминдер

Leverage
Borrowed capital used to amplify a position — magnifying both gains and losses.
Oracle
A service that feeds real-world data (like prices) to smart contracts on-chain.
Volatility
How sharply a price swings over time — higher volatility means higher risk and opportunity.
Machine Learning
Algorithms that learn patterns from data instead of being explicitly programmed.
Large Language Model (LLM)
An AI model trained to predict and generate text from context.

Дерек көздері

Редакциялық сілтемелер

Бұл сілтемелер осы сабақтың артындағы механизмдерді, тәуекел тексерулерін және өнім контекстін растау үшін бастапқы нүктелер болып табылады.

NISTAI Risk Management FrameworkReference for identifying, measuring, and managing AI system risk.OWASPOWASP Top 10 for LLM ApplicationsReference for prompt injection, insecure output handling, excessive agency, and other LLM risks.GaiaEx DocsGaiaEx trading API docsProduct reference for GaiaEx market data, order flow, and account-facing trading surfaces.GaiaEx DocsAPI security best practicesProduct reference for signing, keys, allowlists, and operational security.

Жалғастырмас бұрын

Мұны орындай аласыз ба?

  • Define max position and daily loss.
  • Test with paper trading.
  • Add stale-data and emergency-stop checks.

Байланысты оқу материалдары

Оқуды жалғастыру

Келесі сабақBittensor and Decentralized AIAI Unlocked: Agents and Skills course pathАлдыңғы сабақMachine Learning for FinanceAI Unlocked: Agents and Skills course pathЖолды шолуAI Unlocked: Agents and Skills10 lessonsСөздікLeverage and related terms5 terms from this lesson

Checkpoint

Бұл сабақты аяқтау

Прогресті сақтау үшін тексеруден өтіңіз, содан кейін жолды ретпен жалғастырыңыз.

Білімді тексеру

Бұл сабақты бекіту

Сабақты аяқтау үшін барлық сұрақтарға дұрыс жауап беріңіз.

1 / 2

An AI trading bot should always be paired with…

Алдыңғы сабақMachine Learning for FinanceКелесі сабақBittensor and Decentralized AI
Толық оқу бағдарламасын қарау