how to trade spreads

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ow to Trade Spread


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Bigger Capital LLC. ALL RIGHTS RESERVED. 6

What Is Spread Trading?

Spread trading, also known aspairs trading, is a strategy of trading one or more

securities simultaneously by buying one security or multiple securities and shorting

another security or multiple securities.

The two sides combined consist of apair. The difference between the prices of the

two sides is the spread. The termpair tradeis more commonly used than spreadtrade, and it almost always refers to statistical arbitrage (more on this later). We

usually use the term spread because we do not do all of our trades on a purely

statistical basis, and in theory, the trade could involve more than two securities on one

or both sides. We will thus use spread trading throughout this booklet.

Of course, spread traders will buy the side that they believe will outperform the short

side. For example, suppose you believe Pfizer (PFE) is cheap relative to other drug

makers and, in particular, relative to Eli Lilly (LLY). You have a few options. You canbuy PFE, but if the broad market declines, PFE might also decline. You can reduce

this risk by trading a spread: buy PFE and sell LLY, buy PFE and sell XLV (health

care exchange traded fund (ETF)), or buy PFE and sell a basket of drug-maker stocks.

In this booklet, we will discuss how to choose which spread to trade in detail.

What is Spread Trading?


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Why Trade Spreads?

At Bigger Capital, we trade spreads to generate profit while minimizing net market

exposure. When trading a spread, you are betting on relative performance rather than

on absolute performance. This allows you to express a view without taking on

unwanted risk. There are several advantages to this approach:

It maintains market neutrality, reducing exposure to the overall marketdirection.

It reduces sector and industry risk, depending on the short security chosen.

It reflects the differential economics by removing factors outside the scope of

the trade (market noise).

It improves your ability to compare and analyze.

It is self-funding because you can use the short-sale returns to buy the long

position (subject to margin requirements).

Of course, spread trading has some potential risks as well:

Reduced risk can reduce profit potential.

Further divergence between the legs can lead to a loss on both legs of the trade.

You may face increased exposure to short risk on the short leg, with the

potential for a short squeeze.

Few brokers offer spread-trading capabilities (e.g., Interactive Brokers combo

trades), making it complicated to execute and track.

And thats not all.

Because the concept of cointegration, which is central to spread trading, is a measure

of the statistical elastic force between two securities (more on that later), we can use

spread trading to implement more effectively directional or volatility trading strategies.

Why Trade Spread?


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The Art of Becoming a Better TraderWhen I traded single-stock derivatives at D. E. Shaw, observing my boss trade S&P

options fascinated me. He made money consistently, though he took little risk. He

was a trading magician. He knew his options market, especially the S&P, and he knew

how to trade spreads. He constantly traded in and out, squeezing juice out of the

lemon. The lemon never ran out of juice! It was a wonderful thinga winning trading

method.

He started his career trading options for OConnor & Associates and then worked for

Swiss Bank before joining D. E. Shaw. Both of these were great trading houses at the

time.

Most of the best traders I have met trade spreads. They spread different options,

stocks versus stocks, indices, stocks against indices, and the like. The number of

combinations is endless. Spread traders are good at identifying pockets of value

among the securities they trade, and they rotate their inventory to take advantage ofthese discrepancies with no net increase in market exposure.

The Twitter financial stream is populated with one-dimensional risk-augmenting

trading ideas. Most of these ideas are actionable in isolation, but they are not suited

for traders seeking to compound wealth by deploying capital optimally with a constant

risk profile.

The art of becoming a much better trader requires gaining exposure to spread trading.

When you start looking at the trading world from the point of view of trading one

security against another, you will:

Analyze the economics of both legs.

Hone your ability to identify value within the set.

Remove some of the market noise from the equation.

he Art of Becoming a Better Trader


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Spread Trading MechanicsWhen you trade spreads, the mechanics are not as simple as with single securities.

Suppose you think, for some reason, that ABC will outperform XYZ. So, you want to

buy the spread ABC XYZ.

Figure 1. SpreadTraderPro Scanner

If ABC is trading at $20 and XYZ is trading at $10, then you need to compensate by

trading two shares of XYZ for every one share of ABC. Another way to think about

this is that if you want $10,000 exposure on each stock, you need to buy 500 shares of

ABC and sell 1,000 shares of XYZ (ratio of 1 to 2). The concept of notional exposure

is also important for calculating profit (or loss).

Suppose you buy the spread 1 * ABC2 * XYZ at a level of 0. To get to my $10,000

exposure on each stock (or legof the spread), you buy 500 spreads, which means you

buy 500 shares of ABC and sell 1,000 shares XYZ.

pread Trading Mechanism


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Now assume you are right and ABC increases to $30 while XYZ goes up to $11. Your

spread is now trading at $8 = 1 * $302 * $11. If you close the position, your profit

is $8 per spread * 500 spreads = $4,000. You could also calculate that you made

$5,000 on your long ABC position, but you lost $1,000 on your short XYZ position

for a net profit of $4,000.

But what is your return on capital? Typically, we look at return on long (or short)

capital, which is a more conservative return number. In this case, we started with

$10,000 exposure on each leg of the trade. Total profit was $4,000. Return on long (or

short) exposure is $4,000 / $10,000 = 40%. You could also consider return on

leveraged capital, which varies depending on the margin requirements you face. If you

put up 30% margin on each leg, you will need to have $6,000 cash in the account to

do this trade, so your return is $4,000 / $6,000 = 67%.

Some brokers allow you to trade spreads easily through multi-leg orders. Interactive

Brokers, for example, has a combination order feature that allows you to trade both

legs of a spread with one order. Please see ourvideoabout Interactive Brokers combo

orders for detailed instructions. If your broker does not have this feature, you will

need to track the spread levels manually using a spreadsheet. Once the spread reaches

your desired entry (or exit) point, you enter an order for each leg of the spread.
http://www.screenr.com/ukmshttp://www.screenr.com/ukmshttp://www.screenr.com/ukmshttp://www.screenr.com/ukms


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Types of SpreadsIn this booklet, we will discuss spreads that have a linear payout, such as stocks,

baskets of stocks, or ETFs. Spreads involving derivatives and other nonlinear

securities such as options, futures, and interest rates are beyond the scope of this

booklet.

In its simplest form, the spread is defined to be dollar neutral, which means the

notional exposure on the long side will equal the notional exposure on the short side.

Other types of risk-neutral spreads include beta neutral for equities or duration neutral

for bonds.

ype of Spreads


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Choosing a SpreadThe idea behind choosing a spread is to start with a reason why the long side will

outperform the short side. Traders can use various methods to select which spreads to

trade. The method of selection will depend on the reason (or reasons) for suspected

outperformance. The sections that follow describe some common reasons that lead a

trader to believe one security will outperform another, along with methods to use to

screen securities to determine whether they meet the criteria. Some of the reasons are

mathematical or statistical in nature; as a result, the selection criteria are also

mathematical and statistical. Other reasons are intuitive in nature, and the methods are

less rigorous. Some traders use a combination of criteriasome mathematical and

others intuitiveto arrive at a trading strategy.

Regardless of the types of criteria you use, tools are available on the Web and through

our freeSpread Analyzer tooland our subscription-basedSpreadTraderProprogram.

All of these tools can assist you in discovering and analyzing good trading candidates.

hoosing a Spread
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Statistical Methods

Statistical-methods traders use mathematical approaches to first identify spreads thattrade around a mean and then find opportunities to trade when these spreads have

diverged from this historical mean. In these cases, traders must select spreads that are

likely to revert to their historical means. Identifying these spreads involves statistical

analysis. Below is a description of the theory behind statistical analysis. If you find

some of the theory challenging or confusing, dont worry. Our tools do most of the

hard work for you.

Stock prices are typically modeled as Brownian motion (random walk), where the

price in each period is a function of the price in the prior period, Y(t1); the trendrate of increase, B; and an error term that has an expected value of 0:

Y(t) = B + Y(t- 1) + e(t)

Each leg of the spread can be modeled in this way. Figures 2 and 3 show the

movement of several examples of pairs.

Figure 2. Pair 1 Figure 3. Pair 2

In both graphs, the two stocks diverge from each other at points and converge at

other points. The goal of the statistical analysis is to determine whether it is likely that

the two stocks will converge if they diverge.

-20

0

20

40

60

80

100120

-20

0

20

40

60

80

100120


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Cointegrationis the metric we use to determine this likelihood. Cointegration is a

confidence level that when two securities (long and short) deviate in relative value,

they will revert to the mean. We can think of cointegration as a metaphorical spring

mean-reversion model. When the spring is stretched (Figure 4), it tends to pull back

toward the middle (Figure 5). Similarly, when a mean-reverting spread deviates fromthe mean, a force pulls it back. As statistical arbitrage spread traders, we look for

situations where the spring is stretched so we can enter the trade, profiting from the

return to the mean level. We should not confuse this with correlation.

Again, correlation is sometimes confused with cointegration; however, the statistical

cointegration does not necessarily imply a high correlation. Correlation is a measure of

how two securities move in relation to one another. A high correlation implies that

F = -kx

Stock AStock B

Stock AStock B

Figure 4. Spring Mean-Reversion Model: Stretched

Figure 5. Spring Mean-Reversion Model: Reverting


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the two stocks move in synchrony over the short term but does not guarantee that the

two divergent stocks will revert to the mean in the long term. This distinction

between correlation and cointegration was demonstrated by Dr. Ernest P. Chan.1

Robert F. Engle and Clive W. J. Granger proposed a two-step approach to calculatingcointegration: If each individual stock price series exhibits a random walk (non-

stationary) but a linear combination of them is stationary, then they are said to be

cointegrated.2

Below we give the steps for calculating cointegration:

First step: Determine the time frame you are going to use for the analysis (more on

thislater). You may want to look at a few different time frames, such as one year, two

years, or five years. Perform ordinary least squares (OLS) regression on the chosen

time series equation below to estimate the beta. In the equation, Y(t) is the price of

one security at time t(dependent variable), andX(t) is the price of the other security at

time t(independent variable). Once you know the beta, use the known values ofY(t)

andX(t) to get the residuals (spreads).

Second step: Test the residuals for stationarity using the augmented Dickey-Fuller(ADF) unit root test.3 Mathematical programs such as MATLAB or R have

functions to calculate the ADF test statistic. The ADF test looks at the following

equation:

1 Ernest P. Chan, Cointegration Is Not the Same as Correlation,Trading Markets (blog), November

13, 2006, http://www.tradingmarkets.com/.site/stocks/commentary/quantitative_trading/

Cointegration-is-not-the-same-as-correlation.cfm.2Robert F. Engle and Clive W. J. Granger, Co-integration and Error Correction: Representation,

Estimation, and Testing,Econometrica 55(2) (1987): 251-276.3Said E. Said and David A. Dickey, Testing for Unit Roots in Autoregressive Moving Average Models

of Unknown Order,Biometrika 71 (1984): 599-607.
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The ADF looks at the mean reverting co-efficient, gamma. The test uses the null

hypothesis, gamma equal to zero, and the alternative hypothesis, gamma less than

zero. The result is a confidence level that we can reject the null hypothesis in favor of

the alternative. If the alternative hypothesis, gamma is less than zero, is deemed

appropriate, then the spread will tend to mean-revert because the change in the spreadat any given point in time is a negative function of the level of the spread. Higher

spreads will tend to decline and lower spreads will tend to increase. Individual traders

must use their own judgment to determine what degree of confidence is required.

Keep in mind that the higher you set the confidence interval, the fewer opportunities

you will find. On the other hand, if you set the confidence interval too low, you

increase the chances of finding spreads that are not really cointegrated. At Bigger

Capital, we like the cointegration confidence interval to be at least 90% using a few

different time frames.

Once you identify a spread that is likely to revert to the mean, another critical piece of

information is how long it will take to revert. A spread that you expect to revert in

three days is a much more attractive investment relative to a spread that you expect to

revert in three years. We can calculate the half-life, which is the time it takes for the

spread to revert to half its initial deviation from the mean, to determine the holding

period for a mean-reverting spread. To calculate the half-life, we first need an estimate

of the rate of mean reversion. The rate of mean reversion is the slope of the line Y=

(X), a linear regression using the daily change in the spread (current spreadprevious spread) as the dependent variable and the difference between the current

spread and the mean (current spreadmean of spread) as the independent variable.

Once we estimate the rate of mean reversion (), we can calculate the half-life using

the equation provided inOrnstein-Uhlenbecks mean-reverting equation4:

Ideally, spread traders would prefer to look at spreads with a low half-life, but again,

traders should use their judgment and their capital costs to determine what is

4Ornstein-Uhlenbeck Process,Wikipedia, last modified September 9, 2011, http://en.wikipedia.org/

wiki/Ornstein%E2%80%93Uhlenbeck_process.
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Figure 8. 10 * NFX - 17 * BRY on February 18, 2011

The following is a framework for how to look at statistical spreads based on the

concepts we discussed above.

1. Choose a time period or periods. We prefer looking at multiple time periods,

but some traders may want to focus on only the short term or only the long

term. There is no clear-cut right or wrong answer.

2. Is the spread cointegrated for the time periods you selected? This requiresselecting a confidence interval. We recommend at least 90%.

3. How far from the mean do you wish to enter into a trade? Two standard

deviations is a common entry point for many traders. While this is not a hard-

and-fast rule, we have tested entry points ranging from 1 to 3 standard

deviations. What we find is that entering at 1 standard deviation means the

spread is likely (mathematically) to continue outside of the range, because only

68% of observations are within the range -1 to +1 standard deviations from themean. If we use 3 standard deviations as the entry point, the mathematical

probability of the spread continuing outside the range is low. However, we

find that often a move to 3 standard deviations is indicative of a change in the

underlying cointegration model, where the pair will not be cointegrated going

forward.


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TheSpreadTraderProdaily scan is the most efficient tool available for statistical

spread discovery. If you are not a member of SpreadTraderPro, you can still use our

free tool,Spread Analyzer, to analyze spreads that you either think of on your own or

that you find through Twitter or other sources. The input screen for Spread Analyzer

often contains interesting, relevant spreads. See Figure 10.

Figure 10. Spread Analyzer in SpreadTraderPro

For more information on statistical methods, please see the following video:HeatMap.
http://biggercapital.squarespace.com/spread-trader-pro-bloghttp://biggercapital.squarespace.com/spread-trader-pro-bloghttp://biggercapital.squarespace.com/spread-trader-pro-bloghttp://biggercapital.squarespace.com/spread-analyzer/http://biggercapital.squarespace.com/spread-analyzer/http://biggercapital.squarespace.com/spread-analyzer/http://www.youtube.com/watch?v=JxLfitemmMI&feature=player_embeddedhttp://www.youtube.com/watch?v=JxLfitemmMI&feature=player_embeddedhttp://www.youtube.com/watch?v=JxLfitemmMI&feature=player_embeddedhttp://www.youtube.com/watch?v=JxLfitemmMI&feature=player_embeddedhttp://www.youtube.com/watch?v=JxLfitemmMI&feature=player_embeddedhttp://www.youtube.com/watch?v=JxLfitemmMI&feature=player_embeddedhttp://biggercapital.squarespace.com/spread-analyzer/http://biggercapital.squarespace.com/spread-trader-pro-blog


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2. Merger ArbitrageWhen a merger is pending and the consideration is equity in the acquiring company,

shares in the target company typically move in tandem with shares in the acquirer.

The likelihood of completion of the merger will dictate the strength of therelationship. If a merger is considered highly likely to complete, then the spread

(Target * RatioAcquirer) will be trading close to zero. When a merger is considered

less likely to complete, the spread will trade at a discount. In these cases, if the merger

does complete, the spread trader who bought the spread (Target * RatioAcquirer)

will make a profit. If the deal falls through, the trader who shorted the spread will

make money.

For example, on April 11, 2011, Level 3 Communications, Inc. (LVLT) announced itsintention to acquire Global Crossing (GLBC). Each shareholder in GLBC would get

16 shares of LVLT. If the merger were 100% certain to complete, the spread should

trade at zero. As you can see from Figure 12, the spread trades below zero but

increases toward zero as the probability of completion increases:

Figure 12. Spread Increases with Probability of Completion

If you had bought the spread in April at -2, you could sell it in September for close to

zero. The risk is that the merger does not complete, in which case the spread would

likely fall back below -8.

-10

-9

-8

-7

-6

-5

-4

-3

-2-1

0

4/1/2011 5/1/2011 6/1/2011 7/1/2011 8/1/2011 9/1/2011

Spread GLBC - 16*LVLT


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a)How to find merger arbitrage spreads

Traders can find merger arbitrage spreads by searching news articles on the Internet

or setting alerts that notify them when a merger is announced. Merger arbitrage is a

popular spread-trading strategy, so in many cases there will be articles discussing the

spread. When you trade these types of spreads, it is important to be aware of

important dates for announcements of key rulings and regulatory issues because these

can be catalysts for big moves in the spread.


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Program trading can create sharp liquidity gaps, especially when the robots go mad.

Fast traders can take advantage of these situations if they are good at recognizing what

is going on in a timely manner.


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Or you can think about it this way: the path between each cluster is a stochastic

directional vector, and the cluster is a manifestation of the cockroach theory. This

theory states that if you find a roach in the cupboard, more than one roach is usually

crawling in the same location. Using Godins example, once an animal finds food

along its random walk, the animal will rummage in the same area because thelikelihood of finding more food is elevated.

You must think this concept is crazy, right?

Here is another example of the same phenomenon. A few years ago, Twitter user

@ashrust led me to the articleSharks Hunting Strategies More Like Physics Than

Biologywritten by Brandon Keim, which considers Levy flight principles. Keims

article opens up another rich vein ripe for financial exploration: how sharks respond

to the supply of food could have interesting implications for finance.

Enough about animals: lets get back to humans.

As traders, our food is stock prices discrepancies. For trading success, it is essential to

understand what causes the price discrepancies in the marketplace.

News and other phenomena, such as the mood of market participants, for example,

influence stock prices on a daily basis. For this chapter, we will focus on news.

Ryan Holiday wrote a great book about the media business titledTrust Me, Im Lying:

Confessions of a Media Manipulator. Holiday describes how blogs control and distort the

news. This book is a must-read as it will make you aware of what goes on in spin

media, and it will help you understand the nature of the Levy flight.

By understanding the dynamics going on during a Levy flight, a trader is in a better

position to take advantage of the situation to his own advantage, especially when themedia stirs up emotions to extreme levels.

Heck, at times journalists and financial bloggers alike fabricate situations that do not

exist just to generate traffic. They create food where none exists and distort market
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prices in the process. It is our role as traders to understand these dynamics and to

implement trading strategies to take advantage of these situations.

Here is a sample of questions you can ask yourself to understand the impact of the

news on the securities that you have identified as being in play:

1.What is the relationship between the news, the volatility, and spread values?

2. How long will it take the media to migrate from this story to the next?

3.When do you expect the pressure to abate?

4.When the pressure does abate, do you think the spread will revert to the mean?

5. Can you identify a similar situation in the past that you can use as a proxy to

model how this situation will behave?

6.What is the reaction of traders and investors? If they amplify the news, will the

situation stabilize once they get bored and move on to another story?

7. Can you find other candidates that could be influenced by this situation that

have sold off and are punished unduly (Cockroach theory)?

8.Which type of trade do you implement to exploit this situation?

When the next Vioxx crisis erupts, I will remember that the media will eventually

walk away and let it go. The news will subside, as it always does. As Benjamin Graham

once said, This too shall pass.

Since I wrote the original post, weve used this mental model to sell volatility on

Goldman Sachs when the fraud scandal erupted in April 2010. You can read more

about it here:Levy flight, Truffle Diggers, and Goldman Sachs.The trade washighly

profitable, and we unwound this trade in early July 2010 after the truffle diggers got

bored and moved on to another story. The Gulf of Mexico became a much more

powerful story to coverthen the North African crisis, the Japan crisis, and so forth.

b)Trading the cockroach theory

Here is how we applied the cockroach theory to the trading of Select Comfort

Corporation (SCSS) and Tempur-Pedic International (TPX).

On Thursday, April 7, 2011, after the market close, TPX said it expected to report

strong first-quarter results and increased its full-year guidance. In the past two
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reporting periods, TPX announced earnings prior to SCSS. In each case, a solid

earnings report from TPX was followed by a solid earnings report from SCSS. We

took TPXs announcement as a strong indicator that SCSS would also report robust

results in late April. The 5 * SCSS1 * TPX spread had been trading around $10

since the prior quarters results. It closed at $10.76 on April 7, so when it dippedbelow $8 in after-hours trading, we bought it. We bought some more on the morning

of April 8, also slightly below $8. As it turned out, we could have waited a little longer

because the spread at one point dipped below $5 and closed Friday at about $5.60.

Nevertheless, based on the cockroach theory, we were confident it would return to

the $10+ level.

On Thursday, April 21, we provided the following update to our SCSSTPX trades

on April 7 and April 8. On both dates, we bought five SCSS and sold one TPX on the

back of a rally in TPX after the firm said it expected strong first-quarter results. In the

prior two reporting periods, SCSSs results mimicked TPXs results, and we were

betting the same would happen this time. Sure enough, SCSS significantly beat

expectations when it reported earnings. The stock went up 28%. We unwound the

spread the day after the report for an approximate 13% return.

This is how the cockroach theory can help you identify juicy situations.

A good way to find candidates for the cockroach theory is to look for big daily movesin stocks. When you see one stock move higher (lower) due to earnings, think about

other similar companies that might also report good (bad) earnings. If one stock is the

target of an acquisition, look for competitors who might also be potential targets. For

a hedge, use the company with the original price move (in our example above, TPX).

You can also use a sector ETF or the broad market.

c)Trading crisis-related spreads

Spread traders should always be alert to crises, which present significant

opportunities. As an example, the triple whammy earthquaketsunaminuclear event

in Japan in early 2011 presented a great opportunity, as the Nikkei collapsed 20%

while the S&P 500 dove 6%. There were plenty of opportunities to trade spreads in

both markets and make a good chop.


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During that episode, you could also have traded the relationship between gold ETF

and the miners.

As Warren Buffett says, Be fearful when others are greedy and greedy when others

are fearful.

i. How to find crisis-related spreads

Go where the crisis is, young man! Typically, a crisis is easy to find. It is top news on

every TV channel and news site on the Internet. The hardest part is buying in this

case. Buffetts quote should inspire you to buy when others are selling in crises. The

buy side of the spread is always the target of the crisis, whether it is Japan (EWJ),

nuclear stocks, Steve Jobss resignation as CEO of Apple, or even U.S. indices. The

hedge side of the spread can be a sector ETF or another broad market index.

d)Trading event-related spreads

When a stock experiences a big move due to news such as an earnings announcement,

trading spreads means you can trade the move in stock price while reducing or

eliminating market or sector risk. Depending on your view, you can either buy or sell

on the news.

For example, on March 25, 2011, Accenture (ACN) reported good earnings. The

spread 5 * ACN2 * SPY had closed at -1.8 the previous day and was trading as high

as +21.15 pre-market. After the open, it traded down to +11 by 10:30 a.m. and closed

the day at +8.85.

The market reacts differently to big events at different times. Making money with this

method requires traders to be in tune with these reactions.

i. How to find event-related spreads

Some events are known in advance (e.g., earnings announcements). You can get a

calendar of upcoming earnings announcements fromCNBCor fromYahoo! Finance.

The siteFinvizallows you to screen for stocks reporting earnings in any number of
http://cnbc/http://cnbc/http://cnbc/http://www.finance.yahoo.com/http://www.finance.yahoo.com/http://www.finance.yahoo.com/http://www.finviz.com/http://www.finviz.com/http://www.finviz.com/http://www.finviz.com/http://www.finance.yahoo.com/http://cnbc/


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time frames, including today, after the close, and tomorrow before the open. You can

research the stocks in advance so you know what earnings number is expected. If

there is a surprise and a big move when the event occurs, you can trade the spread

using a competitor, sector ETF, or the broad market as a hedge.

ii. Trading a positive catalyst event

Here is an example of how you can trade the positive news about a company. We

traded this spread at the end of June 2012.

With the introduction of its Nexus tablets and its glasses, Google (GOOG) will have

an abundance of fresh news in the next few months, which will create trading

opportunities.

This situation is appealing to us because the stock is statistically cheap against the

Technology Select SPDR (XLK), as you can see on the Spread Analyzer image

displayed below. GOOG is also cheap against Intel (INTC) and the triple Qs (QQQ),

but we like the $spread better against the XLK given the volatility of the spread. This

vehicle will move quite a bit on fresh news and traders can take advantage of this by

leaning on GOOGs cheapness. You can look at the $spread within the analyzer

here for more clarity. You can play around with the time frame or run GOOG against

any others stocks of your choosing. At the time of this writing (9/4/2012), we arelong GOOG against INTC, QQQ, and XLK.
http://biggercapital.squarespace.com/spread-analyzer/http://goo.gl/Nwbwwhttp://goo.gl/Nwbwwhttp://biggercapital.squarespace.com/spread-analyzer/


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Figure 15. GOOG XLK Spread
http://biggercapital.squarespace.com/storage/pictures/goog%20xlk%206%2028%202012.png


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e)How I exploited a Lvy flight with spreads

Lvy flight situations are easy to find. When the media is all wrapped up in stirring up

emotions and a stock price is moving wildly as a consequence, you know that the

story is a Lvy flight. Examples of this are BP and the Gulf Crisis, Goldman and thefraud scandal, and so forth.

Ideally, a stock should have moved 20% or more (most of the best opportunities

happen when the news is negative and the stock moves down sharply).

Figure 16. COH After Earnings Release in August 2012

For example, in early August 2012, Coach (COH) reported earnings, and the stock

gapped down more than 20% on the news. When a situation like this arises, the first

thing I look for is potential pairs using our Scan All feature.


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Figure 17. Potential Pairs for COH

I decided to investigate the XLYCOH spread further, since I had already rated this

one in the past and was familiar with it. I had been monitoring it for quite some time.

For my style of trading, I did not want to enter the trade right away while the news

was still fresh. Often, big gaps down like these will be followed by more weakness. Iwanted to buy COH and sell XLY beta neutral on some strength.


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Figure 19. Setting Alert on XLYCOH

On August 3, the system alerted me that the spread had reached the set level, so I sold

the spread at 74.81. On August 8, I bought back the spread at 46.07 for a profit of

almost $30 per spread. It was a great situation.


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Figure 20. Results of Spread Trade, XLYCOH

a. How Jennifer Galperin exploited the same situation on a much shorter time scale

Here is a video about how Jennifer Galperin traded COH earnings on the same day.

She chose a different spread, and she talks about this in her video, which you can findhere:COH Earnings Daytrade.
http://biggercapital.squarespace.com/biggercapital-algorithm/2012/8/3/day-trade-coach-earnings.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/8/3/day-trade-coach-earnings.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/8/3/day-trade-coach-earnings.html


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sense for that type of viewpoint). Use our Scan All feature to find spreads that

contain your in-play stock.

b)A word about day trading and risk management

Many day traders do not use spreads. They view intraday risks as minimal, and they

need to act fast. In a bull market, this strategy can work well. But in times of crisis, we

are reminded of the most important rule of risk management: dont lose money.

When we see big intraday moves down in the markets, correlation among stocks

increases dramatically. If you buy ABC stock on good earnings news, only to see the

market down 5% on the day, chances are you will lose money. If you buy the spread

ABCSPY, you may come out on top. Knowing this will allow you to sleep at night

and keep your capital intact.

c) Intraday spread trading example

Check out the trade we did at 8:30 a.m. on September 2, 2011 as the employment data

news hit the tape.

We bought the spread 8 * $SPY13 * IWM at a level of $33.94, which was about $10

below the level it was trading just before the release: we are talking about a fraction of

a second.

Our ability to make money in this situation depended on the following three

components:

1. Major news that can move the market big time.

2. Fast technology to capture a short-term liquidity gap that was almost invisible

to the naked eye. Fast computers are great. Embrace them.

3.The appropriate low delta spread. You wouldnt want to trade this with an

open delta.

We wish we could have done more of this trade, but it just happened too fast.


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7. PatternsBy taking the market out of the equation when looking at the relative pricing of two

securities, you will be in a better position to identify patterns at different time scales

and trade around them. Look for patterns related to volume, percentage moves, oranything else you can think of. Start your search for profitable patterns by following

your favorite spreads (just a few to keep the task manageable) on a daily basis and pay

attention to what is going with them at different time scales, especially intraday. To

start, you may want to look for spreads between ETFs that track important economic

indicators, such as SPDR S&P 500 ETF Trust (SPY), iShares Barclays 20+ Year

Treasury Bond (TLT), iShares Russell 2000 Index (IWM), SPDR Dow Jones

Industrial Average (DIA), SPDR Gold Trust (GLD), and others.


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Combining Different MethodsOf course, traders can always combine different methods when spread trading. They

can start with a fundamental view about two different securities and use statistical

techniques to choose entry and exit points. They can use statistical techniques to find

pairs and then either select or eliminate pairs based on some fundamental or macro

view. Or, traders can give equal weight to both methods, selecting pairs that meet a

strict set of criteria based on fundamental and statistical tests. Another strategy might

be to locate candidates that have events coming up and find a hedge using statistical

methods. You should experiment with different combinations of strategies, because

combining two different methods can dramatically improve the profitability of your

trading strategy. Please watch our webinar for more about this:My Little Tricks

Webinar.

Sometimes, one spread trade might lead to another spread trade. For example, you

may trade one spread in response to an event catalyst and find a competitor to tradeas a cockroach theory trade. Or maybe you successfully locate one statistical spread

and you decide to further investigate spreads in the same industry. Once you start

thinking like a spread trader, you will find endless possibilities.

ombining Different Methods
http://biggercapital.squarespace.com/biggercapital-algorithm/2012/9/7/my-little-tricks-for-profitable-spread-trading-webinar.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/9/7/my-little-tricks-for-profitable-spread-trading-webinar.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/9/7/my-little-tricks-for-profitable-spread-trading-webinar.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/9/7/my-little-tricks-for-profitable-spread-trading-webinar.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/9/7/my-little-tricks-for-profitable-spread-trading-webinar.html


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Extensive and cutting-edge application programming interface (API)

technologies; for traders with little or no programming experience, we

recommend going with a broker that offers a simple DDE for Excel platform,

as Excel offers a familiar and user-friendly interface

Breadth of products in both type (stocks, bonds, futures, commodities,currencies, options, etc.) and geography (global)

Powerful algorithms you can use to make money right out of the gate

Continuing education via webinars

Strong credit and well capitalized

Reliable and fast mobile platform

Portfolio margin capability; margin based on risk, not regulation T

Once you have selected your broker, you will probably want to keep track of the greatspreads youve found. You may even want to be alerted when these spreads get to

levels where you want to enter or exit a position. The best software we have found for

this type of tracking isSpreadTraderPro. Our augmentedSpread Analyzerfeatures

allow you to keep track of past queries, rank spreads based on certain criteria, and set

alerts for when spreads reach desired levels. Plus, you can enter your trades and a

separate tab will calculate your P&L by spread position each day, month, and year.
http://biggercapital.squarespace.com/spreadtraderprohttp://biggercapital.squarespace.com/spreadtraderprohttp://biggercapital.squarespace.com/spreadtraderprohttp://biggercapital.squarespace.com/spread-analyzer/http://biggercapital.squarespace.com/spread-analyzer/http://biggercapital.squarespace.com/spread-analyzer/http://biggercapital.squarespace.com/spread-analyzer/http://biggercapital.squarespace.com/spreadtraderpro


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Risk ManagementThe key spread-trading risks to pay attention to are the following:

Unlimited risk on short side

Correlation risk

Cointegration risk

Concentration risk M&A risk

Short squeeze risk

Opportunity cost risk

Specific risk

Market risk

Political risk

Execution risk (if legging into spread)

The unexpected Adverse momentum

The spread-trading business is statistical, which means high volume and small size.

There are diseconomies of scale in financial markets. Diseconomies of scale means as

you increase the size of your position, the expected P&L declines. Spread traders are

exposed to the short leg, and that is one of the reasons spread traders should keep

their positions small relative to the size of the portfolio. Start small!

Example:The Gold Spread Moves Sharply Against Us(5-15-2011)

The spread that occupied most of our attention this week

was $GLD-$GDX, and we didnt even trade it this week.

We have been short $GLD-$GDX since late April, and the

spread recently moved sharply against us. The spread is

sk Management
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currently trading at its highest level since late 2008. Of

course, its always a good idea to re-evaluate a position that

has made such a large move. Weve decided to leave it on

for now because we dont believe there has been any

fundamental change in market conditions to justify thecurrent level. We feel the move is attributable to the recent

sell off in silver (and other commodities). We think this sell

off spooked some holders of $GDX even though gold

itself has held up rather well compared to other

commodities. Also, our position is relatively small

compared to the size of our portfolio. We try not to have

many positions that are so big that we cant take a little pain

once in a while.

Table 1 shows some of the risk you have with the corresponding pairs structure:

Table 1. Risks with Pairs Structure

Leg 1 Leg 2 Sector/Industry Risk

Stock A Stock A Same No risk

Stock A Stock B Same Specific,

cointegration, shortStock A Stock B Different Specific,

cointegration,

industry, short

Index A Stock B Same Specific, basis risk,

short

Broad Market Stock B Different Specific, short,

industry


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Figure 23. Alerts in Spread Analyzer


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Creating SignalsIn the prior chapter, we explored using spreads to form a directional opinion. If

you find a spread that has predictive values, you can use the spread or a weighted

basket of spreads to create your own proprietary buy or sell signal.

You can create signals by using a few spreads that you think have predictive value

and assign a weight to each spreads daily percentage sign to create your own

predictive index.

Over the last few years, we have discovered a number of spreads with predictive

value. We have called these spreadspredictivebecause they are cyclical in nature.

They can go to an extreme level, but, over time, they will revert to the mean.

Market Versus Predictive Spread 1We use this spread to gauge risk aversion and risk appetite. When capital is

flowing into large caps more than small caps, we can say that the market is risk

averse. Alternatively, when capital outflow in large caps is less than small caps, we

can also say this is a form of risk aversion.

Figure 26 shows Spread 1 (blue, left vertical axis) compared to the S&P 500.


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DividendsDont forget to factor in dividends when calculating the price of a spread on the day

that one of the stocks trades ex-dividend. This is best illustrated with an example.

Suppose you are long one share of Stock A at $55 and short one share of Stock B at

$50. In other words, you paid $5 for the spread. Suppose Stock B pays a $1 dividend,

and on the ex-date, the price of Stock B drops to $49. Dont rush to unwind the

spread because you think you just made $1. Dont forget that you owe a $1 dividend

on the stock you borrowed.

Keep this in mind for statistical analysis as well. Some data sources will adjust for

dividends and stock splits, and others leave that up to you. It is important to knowwhat your data source does in these cases.


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Carry CostsIn calculating the profit and loss of a spread trade, dont forget to take into account

carry costs. You will pay interest on your long position and collect interest on your

short position. The rate you pay on your long position will be higher than the rate youreceive on your short position. For short-term positions, the carry cost wont have a

significant impact, but if you hold long-term positions, you need to take carry costs

into account. This may also affect your choice of spreads (targeting a shorter half-life

when carry costs are high) or your entry/exit decisions.


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Trading OptionsIn the chapter titled Choosing a Spread, we discussed cointegration as a

metaphorical spring mean-reversion model. Options traders can incorporate this

concept of a spring in their decision making to find spread patterns to exploit usingoptions. The linkage between two securities can tip the advantage in the favor of

astute traders who learn how to read what a spread tells them.

Options strategies are numerous, and it is not our intention to go deeply into options

trading. Our goal is to make you aware of the possibilities that spreads represent for

options traders. There is no better way to do this than to give you one example of

how we implemented an options trade using a cointegrated spread with positive

momentum.

On August 29, 2012, Bob Love (@boblove) and I posted the following tweets:

I replied that at the five-year time frame, the spread was cointegrated. You can view

the spread in our analyzer at this link:http://goo.gl/5MqQqor in Figure 32.
http://goo.gl/5MqQqhttp://goo.gl/5MqQqhttp://goo.gl/5MqQqhttp://goo.gl/5MqQq


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upswing. I decided to sell a short-term put on HES. As I mentioned in this tweet, I

wanted to use this trade as an example for this manual.

Figure 33. Cointegration of VLOHES Spread


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Figure 34. Short-Term Put Option on HES

A week after I initiated this trade, I was able to unwind it for a $0.34 profit per option.

The reason I made money on this trade might have nothing to do with the structure

of this spread. There are unlimited factors as to what justifies options prices.

However, I do believe that if a trade pattern is statistically advantaged, the chance of a

positive outcome is greatly enhanced.


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Creating a PlaybookSpread trading is a broad category encompassing everything that involves buying one

security and selling another as a hedge. Within spread trading, there are many different

strategies. You may stick to one strategy, or you may wind up trading a few differentstrategies. You might, within equity spread trading, allocate some of your capital to

these strategies I have listed or any number of other strategies.

Think of each strategy as a play in a football playbook. Sometimes you do a passing

play and other times a running play; you need to mix it up to win the game. In certain

market conditions, you use one strategy more and another strategy in other

conditions, but it is helpful to have a mix of good strategies available to you. But

before you can have multiple strategies, you need to develop one good strategy.

There are many ways to develop a winning strategy. First, you start with an idea. Any

one of the methods discussed in this booklet can be a starting point for your trading

strategy.

I keep a document where I start with my idea and add on over time as I refine my

strategy. In my document, I lay out the universe of stocks (or spreads) that I will

consider: for example, what countries I include, market cap limitations, liquidity

limitations, sectors, and anything else I think is important. You may even specify a list

of specific stocks or spreads you want to trade, if your strategy calls for that. I then

write how I narrow down that universe of spreads to the ones I plan to trade on any

given day. Those instructions will depend on what type of strategy you are developing.

For example, this playbook is for statistical spreads, so I look for statistical arbitrage

candidates trading around two standard deviations from the mean. Depending on

your strategy, you might look at all stocks reporting earnings and find spread pairs to

trade with the in-play names. You might look at a list of 30 stocks or spreads that you

know well and look for trading opportunities there. I lay out my notional size pertrade (which should be somewhat consistent or at least weighted by some guidelines).

I then describe each trades entry strategy, exit strategy, and stop-loss strategy. Each

strategy will typically start with an experiment, and I make a note of the parameters I

want to experiment with. For example, a play might say that if a statistical arbitrage


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spread gets to -2 z-scores, then I buy it, targeting an exit at -1 z-scores. I might

experiment with buying spreads at 1.5 z-scores or waiting until they get to 2.5 z-

scores. You can experiment by trading the strategy to see how it performs, or you can

design a back-testing program to tell you how your strategy would have performed

over certain periods. Back-testing programs depend on rigorous entry signals, sodepending on your strategy, this may or may not be possible.

Once you have a basic idea with some parameters to experiment with, you are ready

to start with a few small trades. Start small at first until you are comfortable because

you want to save capital for additional opportunities that will likely come your way.

Test your first trading strategy with a few trades, and build a small portfolio of trades.

Remember to diversify your entry points. To do this, think of your time frame for

investment. Do you plan to hold each position a few days, a few weeks, or longer?

Spread out your entry points across your holding period. If you plan to hold each

trade for a month and you want 20 positions, then you should do approximately one

new trade per day. Dont put on 10 trades on the first day, because you will soon run

out of capital. Depending on your time frame, you may be able to build a small

portfolio within a few days, or you may need several weeks.

As you put on new trades and close old ones, experiment with the entry and exit

strategies until you find what makes money consistently. Think of your playbook as a

living document, where you update as you adapt strategies or as you discover whatworks and what doesnt. You may adapt to changing market conditions and come

back to old strategies in the next market cycle. You can also add other factors: for

example, what to do if a stock has just reported earnings or is about to report or

whether to include or exclude M&A stocks. When I first started my spread-trading

framework, it was a few paragraphs. Over time, I have grown it to many pages by

adding successful trades, taking note of unsuccessful strategies, and tweaking my

plays. When I have a very successful (or unsuccessful) trade, I add a chart of the trade

and note my entry and exit points. If you are able to describe your strategynumerically, you may even be able to design an algorithmic trading program to trade it

using an API. Or, you might keep the actual trading decisions up to you.

For more information about building a spread-trading playbook, please watch our

webinarhere.
http://biggercapital.squarespace.com/biggercapital-algorithm/2012/4/20/how-to-build-a-spread-trading-playbook.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/4/20/how-to-build-a-spread-trading-playbook.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/4/20/how-to-build-a-spread-trading-playbook.htmlhttp://biggercapital.squarespace.com/biggercapital-algorithm/2012/4/20/how-to-build-a-spread-trading-playbook.html


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ConclusionWe will conclude with a list of some things we ve learned, some of which apply to

all spread strategies, and some of which are strategy specific.

Be able to clearly identify and articulate your rationale for the trade, whether

its statistical, fundamental, a liquidity gap, etc.

Always choose an entry and exit point based on price and time.

Know and understand the various risks involved in your trading strategy ingeneral and in each trade you do.

Continue to experiment and refine your strategy all the time. Maybe the

market will change, in which case you will need to evolve to succeed. Or

maybe your strategy is good but could be better with a slight tweak in

parameters. To do this:

o Keep track of the P&L of each trade and your entire portfolios. What

types of trades are most and least profitable? Under what market

conditions are you most profitable? Can you identify any patterns

about which types of trades are more profitable in different market

conditions?

o Track the P&L of each spread after you unwind it. Perhaps you are

unwinding too soon or not soon enough.

o Track the P&L of each leg of the spread. Where are you making

moneyon the long side or the short side?

Keep track of general observations. Here are some that we have found. Think

about whether you agree or disagree with these, and try to come up with

observations of your own.

o In our statistical book, we have found that it is not necessary to

choose two stocks from the same industry.

o For our statistical book, profits increased with increased volatility in

the market. In times of low volatility, profits tend to be lower.

o We have found that it is best to set your target profit and stop-loss so

that they are symmetrical.

onclusion


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Additional Materialdditional Material


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Join the One PercentI recently went to dinner with several friends who are traders at large investment

banks. All of them are smart, successful people with many years of trading experience.

I was explaining to them some of the statistical techniques we use at Bigger Capital.None of them was familiar with any of the basic statistical measures used in statistical

arbitrage.

Ive encountered the same thing when talking to other traders on different occasions.

Ninety-nine percent dont have any idea of the basic concepts of statistical trading.

And yet, none of these measures is new. Statistical arbitrage has been used as a

successful strategy since the 1980s.

So what are the basic measures that we use? We briefly define the primary ones below.

They are the same statistical values we provide subscribers to our SpreadTraderPro

tool. You can use these measures as a stand-alone strategy or combine them with

other methods to enhance your returns. They are as follows:

1. Cointegrationmeasures the degree of confidence that a stock pair that has

diverged from its mean value will revert to that mean.

2.The z-scoremeasures the distance the spread is from its mean value in

standard deviations.

3.Thehalf-lifeis the expected time it will take for the spread to revert halfway to

its mean.

4.Thezero crossing rateis the number of times the spread can be expected to

cross the zero value for the defined period. A higher number implies a shorter

holding period and a greater likelihood that the spread will not continue totrend.

5. Thesum of least squaresis the squared distance over the selected period. The

lower this number, the tighter the spread is and the better the chance that the

price of leg one will not wander far from the price of leg two.


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The Big Spread DebateAt Bigger Capital, we have different views on a critical issue regarding statistical

spreads. The question is whether the two companies need to be similar (in the same

sector or industry).

The basic pillar of spread trading is that the two stocks are tied together with some

sort of force, and a deviation from historical levels is an opportunity to bet on a

return to those levels. Without such a force, the spread may not ever return to past

levels.

My view is that all stocks are subject to the Law of One Price (LOP); this is the force

uniting all securities.Ingersoll (1987) defines the LOP as the propositionthat twoinvestments with the same payoff in every state of nature must have the same current

value,9 regardless of whether the two companies are in the same or different

businesses. The profit generated by the arbitrage is compensation for enforcing the

LOP.

Jennifers view is that the current price is the expectation of future cash flows, which

are affected by many outside forces. Companies that have similar businesses will be

affected similarly by small changes to inputs like interest rates, commodities prices, or

consumer sentiment. A deviation in the price of a bank versus an oil company may be

an anomaly, or it may be due to fluctuations in inputs that could take a long time to

correct. For similar companies, it is more likely to be an anomaly that we can exploit

in the short to medium term. Given a relatively short time horizon, it is essential that

the two companies have similar businesses.

This is an important issue because requiring the pair to be similar companies means

fewer potential trading candidates and therefore less diversification across positions.

However, if we open up to pairs of different companies, we may introduce more data

mining errors.

9 Evan Gatev, William N. Goetzmann, and K. Geert Rouwenhorst, Pairs Trading: Performance of aRelative-Value Arbitrage Rule, available at http://www.google.com/url?sa=t&rct=j&q=&esrc=s&frm=1&source=web&cd=3&ved=0CCwQFjAC&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc

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What do you think? Do you think statistical spreads need to be pairs of similar

companies, or can you make money trading statistical spreads with companies in

different industries?

Jennifer Galperin

Comment on this text:

Several months ago, I would have agreed with Jennifer, but I have since changed my mind.

Ultimately, you are trading future cash flows, so it doesnt matter which industry generates

those cash flows. It is almost impossible to gauge how the various factors you mention affect

short-term price fluctuations, even within the same industry, so you let the stats tell you the

likelihood of those fluctuations being noise or real.

Norm Winer


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Figure 37. Spread Analyzer XLKVMW


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Figure 38. Spread Analyzer for SPY IWM


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Figure 39. Spread Analysis SPYIWM

If you want to become a professional trader, there is a lot to learn. When you are first

starting out, SPYIWM is a great product because it is liquid, is easy to understand,

can be traded on a short (but not instant) time frame, and provides lots of

opportunities to make money. It will help you learn some of the subtle yet important

aspects of trading, such as:

Setting probabilistic and symmetrical stop-losses

Understanding emotion and its impact on the market

Interpreting liquidity gaps and spikes Finding pricing lags in one security versus another

Recognizing changes in the market environment, and how to adapt your

strategy

Comprehending intraday time windows

What is your favorite trading vehicle?
http://biggercapital.squarespace.com/storage/pictures/spy%20iwm%204%2030%202012.png


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Darwin the TraderCharles Darwin is widely known as the man behind the theory of evolution. He

theorized that through evolution, a species could adapt to different environmental

conditions. Those individuals who did not adapt would not survive to pass along theirgenes.

A friend said to me the other day, It is the markets fault I lost money trading last

month.

I could have agreed with my friends opinion since I have spent the last two years

building my quantitative strategy, and I have had plenty of setbacks along the way. But

now, in the current low-volatility environment, I am making money trading my

strategy at a short time scale, choosing my entry points wisely, and capitalizing onmany small gains.

At various points in my journey so far, I have had to cut limbs to survive. I had to

admit I did not know much about quant strategies when I started. I made mistakes,

and I took steps back to think. I iterated, retested, and moved forward.

What has worked for me is to adapt to different market conditions all the time. Like a

football team, I started by building a book of plays that will work at different times,

against different opponents, and in different market environments. I learned that whatworked last week may not work this week or next week. I need to understand my

opponent by recognizing trends, inflection points, and themes in the market, all of

which can change on a dime. I use my growing playbook to exploit this situation. If

you build a good playbook, you will have the trades set to make money in any market

conditions by adapting and evolving.

A playbook is the tool I have built to adapt.

So how do we adapt? For quantitative traders, this can be one of the hardest things todo. Computers dont learn and adapt; they just crunch numbers. Humans need to

think carefully about the inputs. Maybe that means we ask the computer to look at

performance of the strategy in bull and in bear markets, in low- and high-volatility

environments, or in times when oil prices are low and highwhatever we think might

affect our strategy. Maybe we find that when certain market conditions are in effect,


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we need to tweak our strategy (or radically change it). Then, experiment with the

change. Try one or two small trades to see how they perform. But dont get too

comfortable, because the next change in the market is just around the corner.


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Learn To Trade Like a Math GeekIn March 2012, we held a webinar titled Learn to Trade Like a Math Geek. We

discussed some of the key math terms involved in statistical arbitrage spread trading.

Many of the questions were specifically about calculations and how they are done.

It is important not to get too bogged down with the math. Cointegration tells you that

the two stocks have a history of reverting to a mean level, like a spring. When you

design your statistical arbitrage trading framework, you want to build a portfolio of

these spreads. You should see that most of them behave nicely, while a few continue

on their trend away from the mean. Youll develop your own recipes for determining

when spreads will behave well and when they will not. You may even develop some

recipes for trading spreads that are different, like the earnings strategy we discussed atthe end.

The beauty of statistical arbitrage spread trading is that you can design your own

strategy in whatever way you find works best.Here is the replay of our webinar.
http://www.interactivebrokers.com/en/software/twsDisclaimer.phphttp://www.interactivebrokers.com/en/software/twsDisclaimer.phphttp://www.interactivebrokers.com/en/software/twsDisclaimer.phphttp://www.interactivebrokers.com/en/software/twsDisclaimer.php


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Spread Trading and TakeoversOne morning I came in short Taleo (TLEO) at about $39.50 as part of a spread I

initiated the previous day. Oracle announced that morning that it was buying TLEO

for $46 per share. Bad news!

How do you prevent something like this from happening? The short answer is that

you cant. But there are a couple of things you should be doing to lessen the pain and

decrease the frequency of such events. First, you should create a diversified portfolio

that can withstand such a move. TLEO represented less than 2% of the portfolio.

Second, you should be certain that your process is not getting you into situations like

this on a regular basis. If it is, you might want to rethink your strategy. In our case, it

hasnt. Sometimes weve been on the winning side of these events.

If your process is sound and your portfolio is diverse, events like this will occasionally

occur, but they shouldnt prevent you from being profitable over the long run.


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TaxesReaders are advised not to act upon this information without seeking the service of a

professional tax and/or financial planner. Spread trading can create complicated tax

issues, and spread traders should review their spread-trading tax implications withtheir professional tax advisers at least once a year.

At BiggerCapital we trade spreads in a Section 475 election trading vehicle. You can

learn more about thisright here. Please discuss this and any other tax issue with a

professional who understands your specific situation
http://www.taxesfortraders.com/sec475.htmhttp://www.taxesfortraders.com/sec475.htmhttp://www.taxesfortraders.com/sec475.htmhttp://www.taxesfortraders.com/sec475.htm

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