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# 数学代写|金融数学代写Financial Mathematics代考|TFIN101 Inline with Volume, a.k.a. POV

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## 数学代写|金融数学代写Financial Mathematics代考|Inline with Volume, a.k.a. POV

The previous paragraph hinted that one of the limitations of VWAP (and TWAP) as a market impact controlling tool in that they do not take into consideration the high degree of variability in the daily volume. If, in a particular day, the actual volume is significantly less than expected (due to lack of activity or large distortion in the volume profile) the VWAP strategy will just trade at a higher rate than originally envisioned by the trader leading to a higher total cost. Conversely, if trading a multiday order on a day where more volume is traded than expected, the trader would likely trade a smaller portion of the order than the market would have been able to absorb for the same expected impact cost.

If completing the order is an absolute hard necessity, arguably, there is little that can be done. However if there is some flexibility around completing the order then another approach can be taken. This is where the Inline strategy comes into play. The Inline or alternatively called POV (Percentage of Volume) strategy has a target trading rate as a benchmark and is not directly concerned with price. The aim of trading at a fixed rate is a way to directly control market impact. While seemingly straightforward, following a certain participation rate in real time is not an easy task and these strategies can have some severe drawbacks unless carefully implemented.

Early implementation was purely reactive, meaning observe the volume for a certain period and then trade the prescribed portion of that volume in the next iteration. Due to noise in the volume dynamics this could lead a strategy to oversize the market after a large volume spike. In particular, large block prints, if not correctly managed, can cause a strategy to severely over-trade.

Even when a volume forecast is used there is still room for error in the estimates and any shortfall needs to be correctly managed and possibly adjusted over multiple periods to avoid excessive impact.

The POV benchmark can be extremely noisy, particularly at the beginning of the order due to the granularity of trading. This may result into no trading at the beginning until enough volume is traded and then immediately chasing that volume aggressively, or may lead to falling behind the target volume.

## 数学代写|金融数学代写Financial Mathematics代考|Target Close

As previously discussed many quantitative strategies leverage time series data based on closing prices. As a result, some PM/traders favor this price point as a benchmark for the execution strategies. This is also the case for passive indexers whose fund tracking error is computed based on closing prices. This clearly places a particular importance to the closing price and thus the desire to devise strategies for minimizing the risk from large negative deviation from that price.

It is important to note that in general even Target Close is an IS strategy, as it is still trying to achieve the elusive best price possible. If the ultimate price was unimportant the strategy would be trivial: Place the whole quantity as a Market-on-Close (MOC) order into the closing auction no matter how big the order is. The closing price could be negatively affected by the excess imbalance but the order WILL achieve the closing price benchmark. Instead the objective is to limit market impact while trading at times closer to the end of the day, limiting the risk of large deviations from the close price. Most strategies attempt to forecast the amount of closing volume and size the MOC slice accordingly, thus limiting the chance of negatively affecting the close price and then trade the rest in the latter part of the continuous phase accelerating the trading rate toward the close.

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