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FX hedge execution: algorithmic trading considerations


While traditional phone and platform trading is still the most common approach for corporates hedging FX risk, interest in algorithmic execution has grown significantly in recent years. In this article, we’ll examine the fundamentals of algorithmic trading and assess the advantages and disadvantages of using algos to achieve efficient execution on FX hedging products.

Key takeaways

  • Trading algorithms can offer distinct advantages over traditional phone/platform trading because they can work faster than humans under strictly defined parameters.
  • The increase in trading speed and efficiency can reduce execution costs for banks, leading to tighter pricing for end-users.
  • Algo trading also introduces risks, which depend largely on the type of algorithm and the trading objective.


At the most basic level, an algorithm is a set of instructions that guide the completion of a particular task. Over the past few decades, algorithms emerged as a popular execution tool, both for speculative traders and those focused on mitigating risk. Speculative traders often use algorithms to take advantage of arbitrage opportunities that pass too quickly for human traders, along with a variety of other applications. For those more focused on risk mitigation, algos can present a path towards pricing efficiency when parameters are clear and speed is a priority. In either case, speed is a key feature of algorithmic trading, as it allows users to enter and exit positions faster than they could by using human traders.

Types of "algos"

Over time, banks have developed a variety of trading algorithms to support FX execution objectives. Each has its own set of parameters and places emphasis on different aspects of the trading process. Would you like to get out of the market as quickly as possible, or are you comfortable using time to your advantage? Do you want to lock-in at a specific level or try to outperform the market average over a period of time?

Fortunately, banks offer marketing materials that provide detailed information on the pros and cons of each algorithm, so you can identify which is best for you. At a high level, the algorithms offered tend to range from “aggressive” to “passive.” The most aggressive algorithms will offer slightly skewed pricing on available platforms, drawing in market participants and utilizing available liquidity to support rapid execution. Passive algorithms, by contrast, may make use of limit orders and offer no guarantees that an order will be filled within a given time period. Somewhere in the middle are TWAP (Time Weighted Average Price) algorithms, which make an effort to capture spread but also fill orders by the end of a specified window.

These are the basic “types” when it comes to FX algorithmic trading, but there is a good deal of flexibility within each category. For example, you could employ a passive algorithm but be relatively aggressive in how you use limit orders (i.e., post at or near mid-market).

Benefits of algorithmic trading

The specific benefits of algorithmic trading can vary significantly depending on the particular algorithm and parameters involved. But relative to traditional phone or platform trading, a few things stand out. The flexibility mentioned above means that you can customize the algorithm to match your objectives. The greater speed of algorithms also means that you can employ sophisticated logic around limit orders and timing that you wouldn’t be able to access through human traders. Finally, algorithmic trading is a reliable way to minimize trading costs associated with process management and liquidity premiums, particularly for very large trades (e.g., over $1.5B in total notional) that would otherwise be executed in tranches and may be difficult to manage operationally within a company’s treasury team.

Risks and downsides

One key downside of algorithmic trading is that it puts market risk in the hands of the client, rather than the bank, as the executed rate is not fixed from the outset. Under traditional risk transfer trading (i.e., platform or phone), the bank assumes market risk immediately upon execution. But when an algorithm is in play, the bank passes this risk to the client, who must carry the risk until the whole trade has been executed. Many companies that are utilizing derivatives for hedging activity will choose to retain a higher level of certainty over risk transfer timing.

Another downside to using trading algorithms is that you must sacrifice some control over the execution process. Corporates who turn to algos for hedge execution must be willing to let final trading decisions happen without the benefit of human judgment. And while it’s beneficial to rule out human error, human traders do have the ability to react to black swan events and other curveballs with a level of nuance that can be difficult to mimic through limit orders and other logic. For example, algos that operate over a given time interval may continue to execute in the moments following a market-shifting headline, leading to suboptimal results. Human traders will continue to hold an edge in some unpredictable scenarios, at least until algos develop beyond today's capabilities.

Corporates trading large positions will typically also want to maximize their ability to leverage and reward banking relationships while balancing credit capacity, pricing efficiency, ancillary trading activity, and even nuances across ISDA or CSA terms with different counterparties. These types of considerations can sometimes be more challenging to apply a rules-based framework to, and can lead companies to retain a more engaged and hands-on trading approach.


While algos offer some definite upsides, corporates tend to use traditional phone/platform trading for the large majority of their FX hedge execution needs. Especially for trades in liquid currencies with manageable notional amounts, traditional trading maintains some distinct advantages over algos, including visibility into the exact pricing you will be able to achieve in the moments leading up to execution. If your banking partners are actively pushing algorithmic trading, keep in mind that they may prefer this approach to execution, and therefore promote it. This is because algos allow the bank to transition from "risk-taker" to "risk broker." They receive a spread for executing but are not required to take any market risk.

If you are faced with the decision between algorithmic and traditional trading, consider partnering with an independent advisor to ensure you achieve the best results. Even if you decide to go the algo route, the associated fees are typically negotiable, and an experienced advisor can help ensure you get competitive quotes. If a more traditional execution approach better suits your needs, you can also enlist an execution partner to ensure you have the appropriate level of operational support to manage market appetite and competing internal priorities.

Chatham Financial corporate treasury advisory

Chatham Financial partners with corporate treasury teams to develop and execute financial risk management strategies that align with organizational objectives. Our full range of services includes risk management strategy development, risk quantification, exposure management (interest rate, currency, and commodity), outsourced execution, technology solutions, and hedge accounting. We work with treasury teams to develop, evaluate, and enhance their risk management programs and to articulate the costs and benefits of strategic decisions.

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Chatham Hedging Advisors, LLC (CHA) is a subsidiary of Chatham Financial Corp. and provides hedge advisory, accounting and execution services related to swap transactions in the United States. CHA is registered with the Commodity Futures Trading Commission (CFTC) as a commodity trading advisor and is a member of the National Futures Association (NFA); however, neither the CFTC nor the NFA have passed upon the merits of participating in any advisory services offered by CHA. For further information, please visit