I lHE EASY WAY lO GEl STARTEO I
Everything You Need lo Know, Including:
• The internal configuration of a high-frequency
trading systelll
• COlllparisons of benefits and drawbacks,
as we" as analyscs of inhcrcnt risks
• Who profits frOIll high-frcqucncy trading
and how they do it
MICHAEL DURBIN
All About
HIGH-FREQUENCY
TRADING
MICHAEL DURBIN
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C O N T E N T S
Preface v
Acknowledgments xiii
Chapter 1
Busted 1
Chapter 2
Trading 101 9
Chapter 3
Trading Strategies 43
Chapter 4
Achieving Speed 95
Chapter 5
Under the Hood 131
Chapter 6
The High-Frequency Trading Debate 173
Now What? 195
Glossary 197
Bibliography 215
Index 219
iii
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P R E F A C E
Customer: How much are these?
Merchant: A buck fifty.
Customer: I’ll take some.
Merchant: They’re a buck fifty-one.
Customer: Um, you said a buck fifty.
Merchant: That was before I knew you wanted some.
Customer: You can’t do that.
Merchant: It’s my shop.
Customer: But I need to buy a hundred!
Merchant: A hundred? Then it’s a buck fifty-two.
Customer: You’re ripping me off.
Merchant: Supply and demand, pal. You want ’em or not?
What is high- frequency trading? Great question! And it’s
about time for an answer, because everyone seems to be talk-
ing about it—and forming strong opinions about it—and
when that happens, it’s usually a good thing to know just
what it is. Does high- frequency trading relate only to stock
trading? Or does it include automated trading of stock deriva-
tives such as options? Does it encompass any type of auto-
mated trading, where computers make the decisions humans
once did? Or does it pertain only to the dubious practices of
the sharks sophisticated trading firms who, like the merchant
above, move markets in their favor just because they can get
away with it? Well, since nobody can quite answer these ques-
tions, let’s just make our own definition and get on with it.
In general, high- frequency trading (HFT) refers to the buy-
ing or selling of securities wherein success depends on how
v
vi
Preface
quickly you act, where a delay of a few thousandths of a sec-
ond, or milliseconds,1 can mean the difference between profit
and loss. HFT happens not only in the stock markets but in the
markets for stock options and futures as well. Naturally, not
every reason for trading requires speedy execution. Certainly
not, say, buying stock because you think the company will do
well over the coming years or cashing out your 401(k) to buy
the Harley you’ve had your eye on since you were sixteen.
But plenty of trading strategies do indeed depend on how
quickly you can spot a profitable trading opportunity in the
market—and how quickly you respond with a trade order
to seize that opportunity before somebody else does. We’ll
describe a number of such strategies later on.
The high- frequency trader evolved from the ranks of the
traditional market-maker, or specialist, whose primary source
of profit was the spread between the prices at which he bought
and sold. Unlike the traditional market-maker, however, and
owing to developments like decimalization2 and advances in
technology, the high- frequency trader must settle for much
narrower spreads—razor-thin margins of a penny or less.
As such, high- frequency traders operate in massive scales.
Indeed, the larger high- frequency trading firms now glide
through the markets scooping up vast mouthfuls of trades
like a whale does krill.
Signs of the likely effects of high- frequency trading, and
the growth of the number of firms practicing it, are not hard to
find. Figure 1 shows the Security and Exchange Commission’s
(SEC) calculation of the nearly threefold increase in daily
1 Increasingly, and perhaps by the time you read this book, microseconds—or
millionths of a second—also matter. And it’s only a matter of time before
we’re talking about nanoseconds, or billionths of a second.
2 Decimalization refers to the shift, in the early 2000s, from trading stocks
in fractions of dollars to doing so in pennies, dramatically reducing the
potential spread between the prices at which one can buy and sell a stock.
Preface
vii
F I G U R E 1
NYSE Trading Statistics
8
! .6
• , .
L
ID
o
25
~ 20
~ 15 ,
j 10
~ 5
o
800
.: 600
~ ! 400
i 200 • o
NYSE-Listed Consolidated
Average Daily Volume
2.1
.2005 . 2009
NYSE-Listed Consolidated
Average DailyTrades
22.1
2.9
11 2005 • 2009
NYSE-Listed Consolidated
Average Trade Size
,,.
268
.2005 . 2009