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006

Case 006Execution and market microstructureCore

A broker must buy Rs 50 crore of a stock through the day, and the volume profile is U-shaped: 30% in the first hour, 20% in the last. Build TWAP and VWAP schedules and compare their tracking risk against the day's VWAP.

1The situation

Samyuktam Brokers has a client order to buy Rs 50 crore of a liquid stock over one session, benchmarked to the day's volume-weighted average price. The stock trades about Rs 500 crore a day, so the order is 10% of the day's volume, and its daily volatility is 2%.

Split the session into six hourly buckets. The historical volume profile by bucket is 30%, 14%, 10%, 9%, 17% and 20%: busy at the open, quiet at midday, busy again into the close.

2Your task

Build a TWAP schedule and a VWAP schedule, and compare how far each is likely to land from the day's VWAP.

Quick check

Which schedule tracks the day's VWAP more closely, and why?

Worked solution

Try it on paper, then open one step at a time.

30-second answerThe answer to give first

VWAP buys 15, 7, 5, 4.5, 8.5 and 10 crore by hour; TWAP buys 8.33 crore every hour. VWAP keeps participation at a steady 10% and tracks the benchmark except for errors in the volume forecast, about 5 bps on a plausible miss. TWAP's weights differ from the market's, so any intraday drift moves it off the benchmark: about 15 bps, or Rs 7.4 lakh, one standard deviation. It also trades 18.5% of volume at midday.

Step 1How do you build each schedule?

TWAP is the simple one: Rs 50 crore over six hours is Rs 8.33 crore an hour, whatever the market is doing. VWAP buys each hour's share of the day's volume: 30% of Rs 50 crore in the first hour is Rs 15 crore, then 7, 5, 4.5, 8.5 and 10. Because the order is 10% of the day's volume, the VWAP schedule is always 10% of whatever trades in that hour, while TWAP's participation swings from 5.6% at the open to 18.5% at midday. Think of two people filling buckets from a tap that runs fast, then slow, then fast: one takes a fixed cupful every minute, the other takes a fixed share of whatever is flowing.

Rs crore bought each hour: VWAP follows the volume, TWAP ignores it5101515.06%9:1530% of vol7.012%10:1514% of vol5.017%11:1510% of vol4.519%12:159% of vol8.510%13:1517% of vol10.08%14:1520% of volVWAP, croreTWAP, label = participation10% of the hour's market volumeHour starting; profile as a share of the day's volume
The VWAP schedule buys 15, 7, 5, 4.5, 8.5 and 10 crore by hour, exactly 10% of each hour's volume, while TWAP buys 8.33 crore every hour and so trades only 5.6% of the open's volume but 18.5% of the quiet midday hour.
Step 2Where does tracking risk come from?

The VWAP benchmarkThe average price of the day weighted by the volume traded at each price. An order that buys in the same proportions through the day pays the same average. is the day's prices weighted by the day's volume. If your weights match the market's, your average price equals the benchmark whatever the path. If your weights differ, what matters is how much of the order is still unbought when the price moves. After the first hour TWAP has bought 16.7% against the market's 30%, so 13.3% of the order is exposed to every move from there on; that exposure shrinks through the day and turns slightly negative after 13:15.

The relationship
sd(Pˉyou−VWAP)=σh∑kDk2=0.82%×0.0332≈14.9 bps\text{sd}(\bar P_{\text{you}} - \text{VWAP}) = \sigma_h \sqrt{\sum_k D_k^2} = 0.82\% \times \sqrt{0.0332} \approx 14.9\text{ bps}
\sigma_hhourly volatility, 2% over the square root of six hours, about 0.82%
D_kyour share of the order still to buy minus the market's share of volume still to come, at the start of hour k: 0.133, 0.107, 0.040, -0.037, -0.033 for TWAP
What it says in wordsTracking error is each hour's price move times the gap between your remaining schedule and the market's remaining volume, added up in variance.
ScheduleTracking sd, bpsRs lakh on 50 crorePeak participation
TWAP14.97.418.5%
VWAP, profile exactly right0.00.010.0%
VWAP, day comes in 26, 15, 11, 10, 16, 224.82.4about 11.5%
On a stock with 2% daily volatility, TWAP lands about 14.9 bps, Rs 7.4 lakh, from the day's VWAP on a one standard deviation day; a VWAP schedule whose volume forecast misses by a few points lands about 4.8 bps away.
Step 3Is VWAP simply better, then?

For this benchmark, mostly yes, with two limits. A VWAP schedule is only as good as its volume forecast: if the day's volume comes in at 26, 15, 11, 10, 16 and 22 instead of the historical profile, the schedule still drifts about 4.8 bps from the benchmark. And VWAP concentrates buying at the open, when spreads are often widest and the price is still finding its level. The cost side modestly favours VWAP too: with impact rising with the square root of participation, TWAP's uneven participation costs roughly 7% more impact than a flat 10%.

Close by tying the choice to the client. A client measured against the day's VWAP wants the VWAP schedule, updated during the day as actual volume arrives. A client who wants the order done quickly, or has information that the price will rise, should not be benchmarked to VWAP at all, because the benchmark rewards patience. The schedule follows from the benchmark, not the other way round.

Where candidates lose it

Candidates often say TWAP is safer because it is evenly spread. Evenness in time is not evenness against the benchmark; the risk that matters is the gap between your weights and the market's, and TWAP's gap is largest at the open.

The other miss is forgetting participation. Rs 8.33 crore in an hour that trades Rs 45 crore is 18.5% of the market, enough to move the price on its own.

What the interviewer asks next

  • At 11:15 volume is running 40% above forecast. How do you adjust the rest of the schedule?
  • The client wants to finish by 13:15. What benchmark would you propose instead?
  • How would you estimate the U-shaped profile for a stock that listed three months ago?
← Case 005A backtest shows 18% gross return at 9% volatility, turning the book over 60 times a year at an assumed 5 bps a side. Live, costs are 14 bps a side and only 70% of signals fill. Reconcile the backtest Sharpe with a live Sharpe near zero and decide what to fix first.Case 007 →A fund holds Rs 40 crore of a 2-year government bond (duration 1.9), Rs 35 crore of a 5-year (4.4) and Rs 25 crore of a 10-year (7.6). Compute portfolio duration and DV01, show two ways to raise duration to 5.5, and the P&L of a 50 bp fall in yields.

Company names and figures are illustrative.

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