Another key component of algorithmic trading is quickly and efficiently managing orders based on signals in order to gain an edge over the competition. It is important to react to changing market data, changing signal values in a fast but intelligent manner. Oftentimes, speed and sophistication are two competing goals, and good execution logic will try to balance the two objectives in an optimal manner. It is also extremely important to disguise our intentions/intelligence from other market participants so that we get the best executions possible.

Remember that other market competitors can observe what orders are sent to the exchange and assess the potential impact it might have, so this component needs to be intelligent enough to not make it obvious what our trading strategy is doing. Slippage and fees are also very important factors as far as execution logic design is concerned.

Slippage is defined as the difference in the expected price of a trade and the price at which the trade is actually executed. This can happen for predominantly two reasons:

• If the order reaches the exchange later than expected (latency), then it might end up either not executing at all, or executing at a worse price than you might expect.
• If the order is very large such that it executes at multiple prices, then the VWAP of the entire execution may be significantly different from the market price observed when the order was sent. 

Slippage obviously causes losses that might not have been correctly factored in, in addition to difficulty liquidating positions. As the position sizes for trading algorithms scale up, slippage becomes a larger problem.

Fees are another issue with executing orders efficiently. Typically, there are exchange fees and broker fees proportional to the size of the orders and the total volume traded.

Again, as the position sizes for trading algorithms scale up, trading volumes typically increase and fees increase along with it. Oftentimes, a good trading strategy can end up being non-profitable because it trades too much and accumulates a lot of trading fees. Again, a good execution logic seeks to minimize the fees paid.