Chapter 1 Discussion

7/29/2019 Chapter 1 Discussion

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Paper Overview

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An Empirical Analysis of the Limit Order Bookin the SGX Equities Market

Chapter 1: Order Aggressiveness

Author: Tze Hua Loh1

Discussant: Alex Nikolsko-Rzhevskyy2

1Department of FinanceUniversity of New South Wales

2Department of EconomicsUniversity of Memphis

September 20, 2011

Nikolsko-Rzhevskyy Order Aggressiveness

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Paper Overview

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Summary

Main findings

Summary

The paper contributes to the literature by testing whether

placing of multiple simultaneous buy and sell orders is

used by traders

It utilized a new SGX-ST dataset, which is exceptionally

rich & allows answering many interesting questions

Dataset includes info on all executed and placed orders,

clients ID, clients types, etc., on a second-by-second basis

Due to confidentiality reasons, only 5 stocks over 5

different weeks are studied


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Summary

Main findings

Main findings

The results indicate that traders do seem to place multiple

orders at multiple prices

There is evidence that sometimes, trades are placed onboth sides of the LOB (limit order book)

Order sizes and aggressiveness vary by trader types

Some of the conclusions, however, appear somewhat

unjustified, and terminology – not fully developed

Now will discuss the potential problems with this paper in detail

starting with the major “conceptual” issues


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Paper Overview

Major points

Minor points

Summary

Main findings

Main findings

The results indicate that traders do seem to place multiple

orders at multiple prices

There is evidence that sometimes, trades are placed onboth sides of the LOB (limit order book)

Order sizes and aggressiveness vary by trader types

Some of the conclusions, however, appear somewhat

unjustified, and terminology – not fully developed

Now will discuss the potential problems with this paper in detail

starting with the major “conceptual” issues


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Paper Overview

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Conceptual

Unjustified conclusions

Econometrics/Statistics

Major points1/3 Conceptual

Why only 1 stock is used when there is data on 4 more similar

stocks?

Yes, their samples (and hence market trends) are different,

but these findings are presented as general , so it shouldn’tmatter

Will help to remove time-specific and stock-specific effects

Many results (Proposition #4 in particular) are quite

different for different stocksSome results are currently statistically insignificant; maybe

increasing the sample in 5-fold will help


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More details on Handa and Schwartz (1996) theory would

benefit the paper

Placing multiple buy and sell orders should:1 reduce entry price searching costs ...2 ... but increase transaction costs

I personally am curious to see under which marketconditions this strategy is helpful. My guess would be:

1 Flat non-volatile market (I’ve checked STI – indeed flat)2 Placing multiple buy or sell orders: trending market



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benefit the paper






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Why are Aitken, Almeida, Harris, and McInish’s (2007 JFM)

results so different?

Author’s explanation:1 Their data is on institutional traders only2 The data consists of snapshots and thus doesn’t contain

info on market orders

But this shouldn’t matter for 2 reasons:1 Most traders (including Institutions) use Limit, not Market

(≈ 15% only), orders (Table 4.2)2 Placing multiple-price simultaneous buy and sell orders (the

focus of this paper) could only be done with limit orders

So in their data, we should expect to observe similar effects

(unless the market was trending – see my previous point)



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Major points1/3 Unjustified conclusions

Message on p.51: “Fact: Investors place multiple buy/sell

orders. Investors are smart, hence the strategy is profitable &

should be used” (one of the main results of the paper!)

Generally agree with the observation, but not with the

conclusion

This statement needs to be either made weaker or formally

tested

Testing should be very easy, as client ID is readily available


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When testing Proposition #4, the author finds that “Institutions”

place relatively small orders. Hence she concludes that

Institutions “have sliced orders into small parcels to reduceprice impact”

To justify, need to look at the number of orders in addition

to volume

Table 4.4 shows that Institutions usually use only 1 price

level when placing orders




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to volume






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When testing Proposition #5, the author concludes that the

MKT/LMT order ratio is higher for “Trade Reps” than “Retail”

investors (difference significant at 5%)

However, this is 1 out of 30 cases ( 3%), and the rest 29

differences are insignificant.

Hence, this is just a statistical artifact and it doesn’t justify

the conclusion

We expect to see 1-2 out of 30 cases (which is 5%) appearsignificant at 5% even when the effect is not there




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Major points1/1 Econometrics/Statistics

Investor Mean PIM Institution TrdRep Retail

Type (Aggressiveness) t -statistics

Proprietary 0.5667 -2.68* -7.12** -11.26**

Institution 0.9434 1.0 -8.34** -16.97**

TrdRep 1.6318 1.0 -6.32**

Retail 2.1992 1.0Notes: * 5%, ** 1% significance

Was autocorrelation taken into account?

PIM it = α+ β Institution i + it (1)

If PIM it correlates with PIM it −h or PIM depends on market

trend, it would be correlated; need NW adjustment

Why “-2.68” significant at 5, not 1 percent?

“1”s at the main diagonal are confusing



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Proprietary 0.5667 -2.68* -7.12** -11.26**

Institution 0.9434 1.0 -8.34** -16.97**

TrdRep 1.6318 1.0 -6.32**










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Proprietary 0.5667 -2.68* -7.12** -11.26**

Institution 0.9434 1.0 -8.34** -16.97**

TrdRep 1.6318 1.0 -6.32**










Minor points

Terminology

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Minor points

Minor points1/1 Terminology

When calculating the “MKT/LMT ratios,” the author actually

computes the share of MKT orders in total orders

I would recommend either changing the name or changing

the formula

In Table 4.9: One of the columns is called “Ranking of limit

order placement sizes, most (1) to least (4)”

“most” and “least” sound confusing as in that table,

(1)(“most”) corresponds to the smallest, and (4)(“least”) – highest rank



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Chapter 1 Discussion

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