Cálculo del área afectada por la escombrera y stock pile en un día

Using AlphaMax, a fictitious trader, we define information leak- age as follows: if other traders can reliably generate Alpha sig- nals from AlphaMax’s order executions, AlphaMax’s executions leak

information.1_{AlphaMax executions leak information if they cause}

the signal generated by other traders. This causality from AlphaMax executions to the signal generated by other traders is the defining feature of information leakage: if AlphaMax did not trade, other traders would not generate this signal. In our empirical tests, we use this causality to identify executions that may leak information. But first we must distinguish between good and bad information leakage.

In Figure 8.1, AlphaMax buys 60,000 shares XYZ in six tranches, from 10h00 to 15h00. The AlphaMax “buy” executions increase the price by 12 basis points (bp) and then the price reverts. Good infor- mation leakage occurs when AlphaMax “buy” executions prompt another trader, GoodMax, to sell. In Figure 8.1 at 15h00, GoodMax expects the price will fall and immediately sells XYZ. GoodMax sells while AlphaMax is buying. GoodMax, therefore, provides liquidity

to AlphaMax and reduces AlphaMax’s trading costs.2

Bad information leakage occurs when AlphaMax “buy” execu- tions prompt another trader, BadMax, to buy. In Figure 8.1 at 10h00,

BadMax expects the price will continue to increase and imme- diately buys XYZ along with AlphaMax, increasing AlphaMax’s trading costs. BadMax is a predator, using the Alpha signal cre- ated by AlphaMax’s executions to capture Alpha at the expense of

AlphaMax.3

Figure 8.1 also illustrates the important causality that defines information leakage. If AlphaMax did not try to buy 60,000 shares, the XYZ price would have been flat from open to close and BadMax would not have generated the signal to buy XYZ.

Our examination of information leakage focuses on BadMax and bad information leakage. AlphaMax may leak information to Bad- Max at any point in the order life cycle. Figure 8.2 traces the life cycle of an algo order beginning with the AlphaMax portfolio man- ager (PM) creating a parent order for 500,000 shares and ending with executions of 100 shares reported to the Tape.

PMs, buy-side traders, algos, smart routers, execution venues and the Tape may all leak information. PMs may leak information through headcount turnover. An AlphaMax PM, for example, moves to BadMax and replicates the AlphaMax investment strategy. Buy- side traders may leak information when they shop orders with sev- eral brokers. Algos may leak information by slicing large orders into predictable patterns. Smart routers may leak information by repeat- edly executing on the same venue. Exchanges may leak information when they display limit orders.

In Figure 8.3, we use a sample of GSET algo orders to show that the Alpha signal diminishes as orders move down the algo order

life cycle.4_{We first look at the beginning of the algo order life cycle,}

at algo parent orders. Our sample includes 15,000 large algo parent orders (more than 50,000 shares). On these large orders, the average

Alpha from arrival to same-day close is 29bp.5 _{This 29bp Alpha is}

the signal AlphaMax wants to protect and the signal BadMax wants to identify.

We next look at the end of the algo order life cycle, at the execu- tions reported to the Tape. Our sample has 15 million algo executions and the average execution size is 153 shares. The average Alpha from

execution to same-day close is−3bp.6_{These 15 million executions}

include the executions from the 15,000 large high-Alpha algo parent orders. But they also include executions from many small low-Alpha algo parent orders. Algos, by slicing large high-Alpha parent orders

Figure 8.2 Order life cycle

AlphaMax portfolio manager 500k shares

AlphaMax trading desk 500k shares

100k shares

2,000 shares

600 shares

600 shares Algorithm

Algo parent order

Smart router Smart router parent order 200 shares 100 shares Execution venues Executions Smart router child order Algo child orders Algo tranche The Tape

into small child orders and mixing them with small low-Alpha par- ent orders, eliminate the Alpha signal at the end of the order life cycle.

Figure 8.3 The Alpha signal of algo orders

0 0

Large algo parent orders All algo executions

Parent creation _{Execution time}

–3bp Same-day close

+29bp

GSET algo orders and executions, October 3–28, 2011; re-stitched parent orders including both filled and non-filled shares.

One of the questions we try to answer in this chapter is whether BadMax can identify large high-Alpha parent orders from clusters of small child order executions at the end of the order life cycle.

AlphaMax may leak information to predators in three ways. 1. AlphaMax executions may leak information to predators

through the Tape. AlphaMax, for example, may leak infor- mation by executing buy orders above the mid-quote (and sell orders below the mid). By analysing the Tape, BadMax

will observe that above-mid executions are usually followed by a price increase. AlphaMax’s above-mid buy executions,

therefore, may trigger BadMax buy orders.7 _{AlphaMax may}

also leak information through the Tape by slicing large orders into small orders and executing them in a predictable pat- tern (eg, 150 shares every 15 seconds). By analysing the Tape, BadMax may identify the pattern, anticipate AlphaMax large- order executions and trade along. In both these examples, it is the AlphaMax executions, and not the AlphaMax orders, that

leak information.8

2. AlphaMax orders may leak information to predators who ping. BadMax, for example, may use small peg mid instant or cancel (IOC) orders to ping a dark pool. Several successful BadMax “sell” pings in rapid succession may indicate the presence of a large AlphaMax non-displayed buy order and trigger BadMax buy orders.

3. AlphaMax may leak information to predators with an inside view. BadMax, for example, may have an inside view of a dark pool’s book, seeing non-displayed orders as they arrive. Or BadMax may have an inside view of an algo provider’s blot- ter, seeing the client algo parent orders as they arrive. Either a Badmax inside view is unauthorised or the venue providing BadMax with an inside view of non-displayed orders is violat- ing its obligation not to display. In both cases, an inside view is most probably illegal and the penalty likely to be severe. We next discuss how bad information leakage increases AlphaMax execution shortfall.