Algorithmic Trading

    التداول الخوارزمي (Algorithmic Trading)

    The use of pre-programmed computer software to automatically execute trading orders according to predefined rules and conditions, without direct human intervention.

    Algorithmic trading is an approach that relies on computer programs to automatically execute buy and sell orders based on predefined criteria—such as price, volume, timing, and technical indicators—without the need for manual intervention on every trade.

    Algorithms are used to analyze vast amounts of data at speeds far exceeding human capabilities and to execute trades in fractions of a second, significantly reducing the impact of emotions on trading decisions.

    Common forms of algorithmic trading include:

    • Expert Advisors: Programs that run directly inside trading platforms such as MetaTrader.
    • High-Frequency Trading: Executing thousands of orders within seconds.
    • Automated Arbitrage Strategies: Exploiting price discrepancies across different markets.

    These strategies require rigorous backtesting on historical data before live deployment. A common mistake is relying on a strategy that has been overfitted to past data without verifying its performance across varying market conditions.

    Algorithmic trading operates through software connected to execution platforms like EVEST during the trading hours of the target market, whether in nearly continuous forex markets or stock markets bound by specific exchange sessions. There are no universal specifications for an algorithm, as each strategy is tailored to the developer's criteria regarding targeted assets, trade sizing, and entry and exit rules. Key advantages include ultra-fast execution speeds well beyond human capacity and absolute discipline in rule enforcement without interference from psychological factors such as fear or greed. Risks, however, involve potential programming bugs that trigger unintended trades, as well as deteriorating performance when market conditions diverge from those on which the model was built. Common pitfalls include overfitting strategies to historical data without testing them under diverse forward-looking scenarios, and running multiple algorithms simultaneously without monitoring their cumulative impact on the account. Algorithmic trading is closely tied to the forex market, which is among the most popular venues for this approach due to its deep liquidity and continuous round-the-clock price feeds suitable for developing and testing automated strategies.

    Practical Example

    An algorithm programmed to automatically buy a currency pair whenever a short-term moving average crosses above a long-term moving average, without manual intervention from the trader.

    Related Terms

    Learn the Practical Application

    EVEST Academy free courses explain these concepts step by step in Arabic.