Execution Insights Through Transaction Cost Analysis (TCA): Benchmarks and Slippage

What's the right benchmark?

What exactly makes a benchmark suitable for your trading strategy? Each benchmark offers a distinct lens through which trading performance can be evaluated, and understanding these differences is key to enhancing your execution quality. In this article, we explore the definitions of key price benchmarks, provide quantitative rationale behind each choice, and conclude with an illustrative example demonstrating how to interpret slippage relative to these benchmarks and other relevant metrics.

Arrival price: a fundamental benchmark

The arrival price is the simplest and most important benchmark, and a good place to start. Arrival price is typically defined as the price seen in the market at the start of the order – the moment the order is submitted by a trader. 

For example, let’s say you’re selling USDT to buy BTC (BTC/USDT) by placing a market or duration-based algo (e.g., Time Weighted Average Price - TWAP) order. When the order was submitted, the price was $100 (the arrival price). At the moment the trade was completed, the price was $105.

But, how were the $100 and $105 prices calculated? Was it the last trade price, some average across some time period, or something else?

Arrival price definition

A fair way to determine the arrival price is to look at all publicly available sources of liquidity and take a statistically stable measure of the mid-quote ([ask+bid]/2) over a short duration. A short and stable duration, according to our research, is a 1-second interval. 

Figure 1 below shows the distribution of our top-of-book consolidated (across all public exchanges we connect to) BTC-USDT spread in 1-second intervals in 2024 (adjusting for outlier events). 

The distribution is sufficiently stable with a clear peak, which supports our determination that a 1-second interval is a sensible choice to use when calculating arrival price.  Therefore, we define arrival price as the median 1-second mid-point top-of-book quoted price at the parent order submission time (t0).

Note that we call this price Arrival Price (Parent) given that some of our algorithms may slice a parent order into child orders over time. For example, a TWAP or VWAP order can span minutes to hours to days, while a limit order may sweep the market at the time of submission for immediate execution.

Average execution price

With the definition of arrival price established, we proceed to define the average execution price of an order. We define Average Execution Price (Parent) as the average execution price of a given parent order, inclusive of trading fees (e.g., exchange maker-taker fees).

Where: 

• p_t^fee denotes the execution price that includes marker or taker fee
• T represents the execution horizon of a given parent order

Including exchange fees  provides a normalised view of the execution prices across exchanges and market makers, where the fee is typically baked in the execution price (more about that in another article).

The importance of arrival price and slippage

With arrival price and execution price defined, we can measure the slippage from arrival as the difference between the arrival price and the execution price in bps, where a positive (negative) number represents how much the trade execution underperformed (overperformed) versus the arrival price.

Arrival price and arrival slippage are important to different types of trading styles.  In the case of non-systematic event trading, the arrival price may represent the theoretical price (among other factors) that incentivized the origination of the order. For example, an event trader observes a post on social media that reinforces their conviction to buy. The trader looks at the price (and other factors) at that point in time to conclude it is the right time to trade, with the expectation that  the price will go up (at which point the position can be unwound). Because the trader is making a buying decision “now” based on the price “now”, the arrival slippage becomes the most important benchmark to assess their trading  performance.

In systematic trading (where bots execute trades based on signals), the arrival price is commonly used as a benchmark for measuring slippage. This is because strategies are backtested under the assumption that trades are executed at the price exactly when the trading signal is generated. Because arrival price best reflects the theoretical entry point used in backtests, systematic traders aim to minimize slippage relative to this benchmark, aligning actual trading performance more closely with the strategy’s projected results.

How to analyze arrival slippage 

The arrival slippage, in conjunction with other factors, provides our clients with insights into when a trading strategy seems to be working (i.e., when performance is beating arrival price, negative slippage displayed in green) and when it can be improved (i.e., positive  slippage displayed in red), so that they can make changes to their strategies and parameters to reduce slippage further.

The Talos Analytics dashboard decomposes slippage and other relevant metrics such as volumes and participation rates distribution by strategy. 

Parent level analysis: marketable vs. limited orders

The Parent Order Stats table provides an overview of slippage in aggregation, by strategy and marketability – orders are classified as Marketable or Limited:

• Marketable. This classification indicates that the parent order executed was marketable for its entire duration, and at no point did a limit price, if provided, prohibit the algorithm from taking liquidity. 
• Limited. This classification indicates that the parent order was “limited” at some point during the execution duration, where a limit price prohibited the algorithm from taking liquidity. If a limit price did not prohibit the algo from fetching liquidity at any point, the parent order would be classified as marketable.

Note that an algorithmic strategy may choose to not trade due to other constraints, but these classifications only consider whether a limit price was an execution constraint.

The distinction between Marketable and Limited parent orders is important when evaluating slippage. Consider 2 parent TWAP orders for crypto pair A, one with a $100 limit and one without a limit, for a duration of 5 hours. Say that for the first 4.5 hours, the price of A was always above $100, and completely equal or under $100 for the remaining 30 minutes. In this case, the marketable parent order will be able to trade for the entire duration, whereas the limit parent order can only trade during the last 30 minutes. This may yield completely different trading outcomes, and hence slippage for the 2 orders, and aggregating those into one measure would be an “apples vs. oranges” situation.

Note: Some Talos algos, when in a “limited” state (e.g., during a TWAP algo execution accessing public exchanges), a portion of the order may be posted to rest at or below the limit price to take advantage of passive (maker) fills when the market price comes in the direction of the limit, which helps to minimize slippage on the order.

TWAP and VWAP: important benchmarks

Finally, we measure slippage against 2 other important price benchmarks for additional insights: the market TWAP and the market VWAP, which we define as follows. 

• Talos Market TWAP -- the interval TWAP (Time Weighted Average Price) across the client parent order time duration, based on the Talos consolidated book.

• Talos Market VWAP -- the interval VWAP (Volume Weighted Average Price) across the client parent order time duration, based on the Talos consolidated book.

Note that TWAP and VWAP are computed based on trades within the parent lifecycle, as opposed to quotes. In the case where there’s a limit price given, the Talos interval VWAP and TWAP would be computed based only on the public trades (the Talos consolidated book) that were in-limit. 

For example, if a parent order to buy with a limit of $100 was traded over a minute, with 10 trades at or below $100 and 5 trades greater than $100, the interval VWAP and TWAP would be computed only based on the 10 trades that occurred at or below the $100 limit.

It is important to make sure the price computation aligns with the range of liquidity opportunities when there is a limit price, so that slippage is based on a fairly calculated benchmark price.

Putting it all together: Execution insights

Looking at slippage versus TWAP and VWAP, as well as arrival price, provides important insights into trading performance. 

Consider the following slippage outcomes for 1000+ parent orders representing $1B in notional, executed through a TWAP strategy.

Observations from TWAP strategy performance:

• Paid nearly 13 bps from arrival but (mildly) beats the market TWAP and VWAP, an indication that, even if 13 bps might seem high, trading outcomes were aligned with the market, even beating the “general” trend indicated by the TWAP and VWAP slippages..
• The market moved up by 42 bps on average and the TWAP strategy was a strong buyer (85% of the notional), an indication that the arrival slippage, while seemingly high, is in line with the market trend: 13 bps is less than half the  average market move of 42 bps
• The maker rate was 75% while the market was trending up in conjunction with our positioning (85% buying), an indication that the algo is making its best attempt to post passively and gain maker (typically cheaper) fills, taking advantage of the likely volatility on the way to completion. This is also a strong indication that the discretion bands around the TWAP target are appropriately calibrated to the trade pattern.

Potential actions to improve slippage

• Shorten the duration. The average duration of an order was 100 minutes. If the assets traded are relatively liquid, then shortening the duration might help reduce the arrival slippage. If a trader tends to buy (sell) when the market goes up (down), trend following, the “time risk” (the risk of missing the arrival price) is exacerbated by prolonging the trade duration.
  
  • Note that shortening the trade horizon may result in reduction of the maker rate, given the algo has a statistically smaller chance at passively accumulating liquidity. However, for a liquid pair with a tight spread, taking liquidity more often may result in a better execution slippage vs. arrival when trend following.

• Consider switching to a more aggressive strategy when trend following, like a POV (percent of volume) strategy. Assuming the average participation rate of the TWAP strategy is 5% in this instance, increasing the target participation rate to 8% or 9% under a POV strategy would be a good alternative. You may see a reduction in the maker rate, but you can look at the outcomes in conjunction with arrival slippage to calibrate.

Talos algo researchers have the ability to dive deeper into the data to derive a “contributions to slippage” analysis which identifies the factors driving arrival slippage. This is typically done using machine-learning approaches (e.g., Random Forest). This analysis could serve as the foundation for building an “algo wheel” that systematically switches between algos under certain conditions or used as a guide.

Conclusion

The metrics we’ve covered above are really just “scratching the surface” of understanding your execution performance and improving slippage against your preferred benchmark. Talos provides many tools for you to dive deeper into slippage, and we’re constantly adding new measures and models to help you find ways to reduce it.

We’ll let you worry about what to trade, while we focus on optimizing how to trade.

^{Disclaimer: Talos Global, Inc., together with its affiliates (collectively, “Talos”), is not an investment advisor or broker/dealer. No Talos product or service constitutes an offer to buy or sell, or a promotion or recommendation of, any digital asset, security, derivative, commodity, financial instrument or product or trading strategy. Further, No Talos product or service is intended to constitute investment advice or a recommendation to make (or refrain from making) any kind of investment decision and may not be relied on as such. Talos offers software as a service products that provide connectivity tools for institutional clients. Services may not be available in all jurisdictions.}