Algorithmic Trading (Algo-Trading) Definition

Algorithmic trading uses computer programs to execute buy and sell orders for assets such as equities or cryptocurrency according to predefined rules. Once configured, the software reviews price movements, trade volumes, and time-based patterns in real-time and places orders far faster than a human trader.

Key capabilities

• Continuous operation
  The code monitors markets around the clock, applies its logic without interruption, and reacts to news events within milliseconds.
• Precision execution
  Algorithms capture available prices immediately, which reduces slippage—the difference between the intended price and the final fill.
• Emotion-free decisions
  Because instructions remain fixed, the program avoids fear-driven selling and impulse buying, helping traders adhere to a plan.
• Portfolio scale
  High-frequency logic can manage large baskets of instruments across multiple venues simultaneously, a task impractical to perform manually.
• Improved liquidity
  Rapid order flow increases market depth and fosters tighter bid-ask spreads, contributing to more stable pricing.

Practical example

A trader programs the system to buy Bitcoin after a five percent hourly decline and to exit once the price recovers three percent. The algorithm tracks the threshold, submits orders immediately when conditions match, and closes the position as soon as the rebound occurs.

Common strategies

• Arbitrage—exploiting price differences across exchanges
• Trend following—entering positions when momentum indicators turn positive and exiting on reversal signals
• Market making—quoting simultaneous bids and asks to earn the spread while supplying liquidity

Although many platforms offer plug-in tools, developing or selecting a robust algorithm still requires technical skills, thorough testing, and ongoing oversight.