One word commonly appearing in algorithmic trading landscape is "POV" – Percentage of Volume. Understanding the POV is crucial for traders seeking efficient execution strategies that depend on the shifting market conditions. In this blog post, we will discuss the concept of POV and how it works and provide examples.
Overview of POV
The POV is an order execution trading strategy that allows traders to execute the desired percentage of the total market volume called participation rate over a specified period. It's an adaptive strategy designed to adjust the order size dynamically based on prevailing or forecasted market volume in real-time.
Unlike TWAP / VWAP, which follows a fixed schedule, the POV algorithm changes its trading in real-time to ensure a consistent participation rate. The POV, however, has an intuition of the VWAP algorithm, but in real-time. The VWAP algorithm trades more when the volume is historically high and less when the volume is historically low. The POV algorithm trades more when the market trades more and less when the market trades less.
How POV Works
Assume a trader intends to execute 5% of total market volume during an hour using a POV algorithm. The algorithm will seek to trade 500 shares for every 10,000 shares that trade in the following hour. The algorithm will attempt to submit an order for 50 shares for every 1000 shares, e.g., if 950 shares trade in 1 minute, the algorithm will send a limit order or market order (for more aggressive execution) for 50 shares (total volume traded would be 950+50 = 1000). And if another 1000 shares trades in the market during the following 30 minutes, the algo will have traded only 100 shares in 31 mins (1+30 mins). Generally, for the POV algorithm, the schedule is updated on a tick-by-tick basis, and it waits for trading to occur and then participates only afterward.
Market Impact and Considerations for the POV
Since the POV algorithm must trade more aggressively to avoid falling behind schedule, it often uses market orders rather than limit orders, placing orders only after the trading volume has happened. Spread expenses increase as a result. The POV is volume-responsive and ultimately becomes a liquidity taker rather than a liquidity generator. It trades immediately following the volume surge, responds to the previous volume, and has the potential to significantly affect the price if another trader has made a similar move. Another increase in volume would result from this, which would encourage trading by additional parties. The POV would trade more aggressively to maintain the target rate due to this feedback cycle at the expense of higher market impact costs.
Inability to Guarantee Completion
POV algorithms cannot guarantee that an order will be executed within the specified time frame. Market conditions, particularly low liquidity, may result in partial fills or the inability to complete the order within the desired period.
Not Suitable for All Securities
Illiquid stocks have short and isolated bursts of activity than more liquid stocks. The POV would respond to such spikes quickly and would have more spread and market impact cost. Intuitively, the POV should be more effective than TWAP / VWAP with the higher volume. However, it ends up being reactive and suboptimal.
Implementation Challenges
POV algorithm implementation and maintenance can be challenging and need careful calibration. Traders must constantly evaluate and modify parameters; they must pay attention to order sizes, the number of open orders, the intervals between orders, the nature of market dynamics, order book sizes, and hidden liquidity. Additional risk management and real-time monitoring are crucial to navigate the complexities introduced by the interaction of Iceberg Orders.
Conclusion
While the POV has several advantages over other algorithms, such as TWAP and VWAP, it also has limitations and challenges. Nevertheless, with careful calibration and monitoring, POV can be a powerful tool for traders seeking to navigate the complexities of algorithmic trading. Traders must pay attention to its implementation details and can use its concept along with other algorithms, such as VWAP, to design custom execution trading algorithms.
