Manage your Trading Risk
Global Sales Trader
Algorithmic trading (i.e. Algo Trading) is one of the many techniques widely used by institutional investors. It is popular on the professional level because the program-driven logic can execute orders and generate profits at a speed and frequency that is beyond human’s physical limit. At Saxo, we enable all our clients to trade like a sophisticated professional but with easy to understand interface. Starting this week, we go over different common algo strategies one by one, with an aim to share our knowledge with common users.
Implementation Shortfall aims to optimize the execution duration to minimize the combination of price impact and the risk of potential price movement. The optimization considers the current market price and stock-specific trading characteristics (e.g. liquidity) as well as the size of the order. The order is executed in line with the expected volume profile. Higher urgency trade faster at the beginning to maximize liquidity capture at the current price, whereas low urgency will prioritize to minimize market impact while undertaking higher execution risk.
Parameters to consider
Limit Price (Optional):
Strategy can be used both at market level or with a specified limit price
Start / End Time (Optional):
If not specified, start and end times are by default set to market open and market close, respectively. Start and end times are defined in local exchange time.
Max Participation Rate (Recommended):
Ability to place constraint on the maximum percentage of trade volume in which the order should participate. This parameter can protect the user from overly exposed in the market when order size is large compared to market level.
In Open / In Close Auction (Optional):
The user can decide whether to participate in opening and/or closing auctions. If not specified these are by default set to include auctions.
I Would Price (Optional):
Attempts to complete or trade up to the price specified. Within this price the order can be up to 100% of trade volume.
Urgency Selections offer High, Medium and Low. Based on the urgency chosen the algorithm determines the optimal trading horizon. Higher urgency trade faster at the beginning to maximize liquidity capture at the current price, whereas low urgency will prioritize to minimize market impact while undertaking higher execution risk.
One precaution for user to yield best intended performance is to avoid markets with high volatility behaviors or volume distribution is uncertain. Upon every deployment of the strategy, the algo engine will require reading into the historical trading pattern specific to the asset in focus and derive a fair and justified execution approach. This decision, while highly sophisticated, is anchored on the basis that the prevailing market is comparable to the historical behavior. If the market is going through abnormal times which deviates significantly from its prior average pattern, (e.g. after the release of surprise earnings), the effect and performance of Implementation Shortfall strategy will be discounted.