If you’ve been following around with our Algo 101 series, you’ve already gotten a taste of parts 1 and 2 with our TWAP and VWAP posts; and if you haven’t read those, we recommend taking 5 mins after this to get a quick refresher.

So, this is the third post in this series helping those interested in algorithmic execution understand how different types of algorithms work and the execution objectives they’re intended to solve.

Strategy Name: POV

POV stands for Percentage of Volume, and is classified as a participation based algorithmic execution strategy.

The POV algo is reactive in nature and attempts to execute at a consistent participation rate. POV participates in-line with volume traded in the market at a trader’s desired percentage participation rate.  A trader may opt to use POV when they would like to participate along with the market but do not have a specific view on how to optimally achieve their trading objective. POV may also be useful in certain illiquid products where lack of data proves challenging from a modelling perspective, or during periods where markets are exhibiting abnormal trading conditions with respect to their normal behavior. POV inherently runs the risk that the market does not trade in enough quantity to allow full order completion in certain scenarios.

For example, a trader who is looking to execute 1,000 10-Year Futures contracts with a focus towards minimizing impact may trade alongside the market by setting a target of 5% of volume. The parent order for 1,000 contracts will be sliced by the algo into smaller child size orders. The POV algo will react to volume traded in the market. If 100 contracts trade, the algo would look to have completed 5 contacts. In order to complete this entire order, the algo would expect that a total of 20,000 contracts would have to be traded before the original parent order was fully completed.

How does RCM-X handle a POV?
The general concept remains the same as the algo targets to participate alongside the traders POV target. As a premium provider of algo execution strategies, RCM-X utilizes short-term signals to dynamically place passive orders in the market in order to collect the spread rather than simply reacting to traded volume by instantly crossing. By utilizing real-time market conditions such as bid/offer spreads and orderbook dynamics, along with various other metrics, the algo decides when to place passive orders and and when to be aggressive – all while seeking to minimize the execution cost for the trader. RCM-X POV also includes a “Block Limit” parameter so that clients may selectively ignore trades in the market data relating to their POV objective. This feature provides protection from chasing large trade prints in the market that could cause a simple POV to execute more than a trader would otherwise intend. Like other RCM-X Algos, the RCM-X POV algo takes into account economic releases, seasonality effects, and uses anti-gaming logic in seeking to improve execution performance for clients.