Market Microstructure

Bid-Ask Spreads and PIN

Daniel Sungyeon Kim

Bid-Ask spread

• The bid-ask spread can be decomposed

into what two components? • Adverse selection component

• Transaction cost component

Four-way Decomposition of the spread

• Adverse selection component• Transaction cost component can be further

decomposed into three pieces:– Inventory risk component – compensates dealers for bearing

price risk their inventory– Order processing cost component – compensates dealers for

their normal cost of doing business– Monopoly profits component – extra profits that can be

extracted by monopoly power

Four-way Decomposition of the spread

• Recent estimate by Henker and Martens:• Adverse selection = 15% of spread = 1.0 cents• Inventory risk = 17% of spread = 1.2 cents• Order processing = 65% of spread = 4.5 cents• Monopoly profits = 3% of spread = 0.2 cents

Total spread = 6.9 cents

Explanations for Adverse Selection Comp.

• What are the two explanations for adverse selection component?

• Information perspective

• Accounting perspective

Figure 14-1

• Ask0 = V0 + (1/2) Adv Selection + (1/2) Transaction Cost

• Bid0 = V0 – (1/2) Adv Selection – (1/2) Transaction Cost

• Figure directly shows information perspective:– If buy trade, value increases from – If sell trade, value decreases from

0 0BV V

0 0SV V

Figure 14-2

• Suppose there is a buy trade, value increases from• This becomes the new midpoint:• Ask1 = V1 + (1/2) Adv Selection + (1/2) Transaction Cost

• Bid1 = V1 – (1/2) Adv Selection – (1/2) Transaction Cost

• If next trade = buy, value increases from • If next trade = sell, value decreases from• Change in value = V1 –V0 = (1/2) Adv Selection

• Adverse Selection = Permanent Component of the spread• Vs. Transaction Cost=Transitory Component of the spread• That is, Ask0 - went away did not become part of

change in value• If the market is Efficient = reflects all available info,• then value changes are unpredictable = Random Walk

0 0BV V

1 0BV V

1 1BV V

1 1SV V

0BV

“Most Important Lesson in this Book for Most Readers”• Uninformed traders lose to informed trader regardless

of whether they use a limit order or market order• Example: Ask = 30.10, Bid = 30.00, informed have good

news that stock is worth 35.00

(1) Uninformed submits limit sell at 30.10

informed buys at 30.10, price rises to 35.00

uninformed sold at 30.10 & missed price rise

(2) Uninformed submits limit buy at 30.00

informed submits limit buy at 30.01 (or buys at 30.10)

price rises to 35.00

uninformed limit buy doesn’t execute & misses price rise

(3) Uninformed submits market buy or market sell

pays the spread, which is wider due to adv select comp

Easley, Keifer, O’Hara, and Paperman

• Develop a simple, classic model of adverse selection• Can estimate how much informed trading in any stock• PIN = Probability of INformed trade

= % of traders that are informed

PIN Computation

• Chance of Informed Sell =

• Chance of Informed Buy =

• Chance of Informed Trade =

• Chance of Uninformed Trade=

• PIN = % of traders that are informed

1

1

Buys+ Sells 2

Chance of Informed Trade

Chance of Informed Trade + Chance of Uninformed Trade

2

A PIN example

Day Buys Sells1 53 492 74 513 48 784 51 50

PIN Model Dynamics

• Some traders are informed and others are uninformed• Trading is anonymous• Market makers don’t know which

trader is informed vs. uninformed• Every trade causes a price reaction• Every sell causes a lower bid and ask• Every buy causes a higher bid and ask

= PIN

PIN Sampler

• Vega • PIN parameters

year-by-year

e m

a d

PIN

PIN Sampler

• Agudelo• In Indonesia,

who is more

informed:

foreigners

or locals• PIN(foreigners)

vs. PIN(locals)

PIN Sampler

• Easley,

Engle,

O’Hara,

Wu• Dynamic PIN

model• PIN estimates

for 16 stocks

PIN Sampler

• Easley,

De Prado,

O’Hara• Modified

Version of

PIN =

VPIN

during for

the 2010

Flash

Crash