A limit order is an instruction to buy or sell a financial instrument at a specified price or better. Unlike a market order, which prioritizes speed of execution, a limit order prioritizes price. A limit buy order will only execute at the limit price or lower, and a limit sell order will only execute at the limit price or higher. If the market never reaches the limit price, the order remains unfilled.
How limit orders work
When a trader submits a limit buy order at $50.00, the order is placed on the exchange's order book at that price level. The order will only fill if a seller is willing to trade at $50.00 or less. If the stock is currently trading at $50.50, the limit order waits until the price drops to $50.00. If the price never reaches $50.00, the order expires unfilled.
Limit orders are subject to price-time priority on most exchanges. At any given price level, orders that arrived first are filled first. This means a limit order placed at a popular price level may need to wait behind other orders at the same price, even after the market reaches that level. The order might not fill even though the price touched the limit level if there was insufficient volume to reach all queued orders.
Advantages and disadvantages
The primary advantage of limit orders is price control. The trader knows the worst price at which the order will execute, which eliminates the slippage risk associated with market orders. This is particularly valuable in volatile or illiquid markets where market orders might fill at significantly worse prices than expected.
The disadvantage is execution uncertainty. A limit order might never fill, causing the trader to miss a profitable opportunity. For momentum strategies that need to enter positions quickly as the price moves, limit orders can result in missed entries because the price moves away before the order is filled.
Limit orders in backtesting
Accurately modeling limit orders in backtesting is challenging. A naive approach fills a limit buy order whenever the market price touches or drops below the limit price. This overstates fill rates because it ignores the queue position problem: the market price might briefly touch the limit level without enough volume to fill all orders at that price.
Realistic limit order modeling considers the volume traded at or below the limit price and estimates the probability of fill based on the order's queue position. This is particularly important for strategies that rely on limit orders for entries, as overstating the fill rate directly inflates backtest performance.
Practical example
A mean reversion strategy places limit buy orders 0.5% below the current mid price, expecting to capture short-term dips. In a naive backtest that fills whenever price touches the limit, the strategy shows a 65% fill rate and strong returns. In a realistic backtest that considers volume and queue position, the fill rate drops to 30% because many of the price touches did not generate enough volume to reach the order in the queue. The reduced fill rate significantly changes the strategy's overall performance.
How Tektii helps
Tektii models limit order execution against actual historical tick data, accounting for available volume at each price level and the realistic probability of fills. The platform does not assume that touching the limit price guarantees a fill, which prevents the overly optimistic results that plague simpler backtesting engines. This gives traders accurate expectations for limit-order-based strategies before they deploy real capital.