“The voyage of discovery is not in seeking new

landscapes but in having new eyes”.

Moneyball meets Manager ID

1420 18th Street

Denver Colorado 80202

email: mike@t3equity.com

303-860-7386

www.t3equity.com

PSN Top-Gun Awards t3 equity labs, llc

3rd Quarter 2012

PSN Top Gun Rankings 3rd qtr 2012

(top ten in category) Universe

# of funds in univ.

1 Star 2 Star 3 Star 4 Star 5 Star 6 Star Bull & Bear

Master

Qtr 1yr 3yr 5yr 5yr 5yr 3yr

t3 equity labs All Cap Core All Cap Core 121 #4 #4 #4 #1 #1

All-Cap 496 #3 #1

US Core 735 #4 #5

t3 equity labs All Cap Core Trigger All Cap Core 121 #6 #7

t3 equity labs Large Cap Core Large Cap Core 364 #4 #4 #10

http://www.informais.com/topguns/topguns.asp?

This document contains actual historic performance results, including assumptions, opinions and views of the Company and third part sources. Various known and unknown risks, uncertainties and other factors could cause the actual results, financial position, development or performance to differ materially from the performance presented herein. There is no guarantee, expressed or implied, that the performance presented here is free from errors nor is there any acceptance of responsibility for the present or future accuracy of the opinions expressed in this document. No representation or warranty expressed or implied is made as to, and no reliance should be placed on, any information, including projections, estimates, targets and opinions, contained herein, and no liability whatsoever arising directly or indirectly from the use of this document. In making investment decisions it is your responsibility to examine the investment and the relevant risks to such an undertaking. Past performance is not indicative of future performance. Performance is not guaranteed. This should not be considered an offer to buy or sell securities.

See how thinking “beyond” the box can help you. Call Michael Jackson at 303-952-9296, or email mike@t3equity.com

1420 18th Street

Denver Colorado 80202

email: mike@t3equity.com

www.t3equity.com

Stars are good! More Stars are Better!! Stars across all products are best (and quite rare!)

Making $ense of this is

difficult to convey in a

simple chart– what’s my

take-away? Being top 10

in a category consistently

is very difficult. But

having a variety of

products that are top 10

for a variety of different

time frames is

increasingly rare. Being

top ten with a couple of

products for the past 5

years is very humbling.

But when the added

responsibilty of doing this

on a risk adjusted basis

gets super imposed – it

becomes very difficult.

What happened to the lost decade?

Active US Large-Cap Equity Mutual Fund Managers vs. S&P 500 Market

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MKT Performance

MGR Performance

Linear (MKT Performance)

Linear (MGR Performance)

0.00

10.00

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3/1

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Pe

rce

nt

of

MG

Rs

Ou

tpe

rfo

rmin

g In

de

x

SMA Manager Outperformance Large Cap Universe

Diversification?

Average Correlation amongst all size and style 3/2005-3/2008 3/2008-3/20011

0.897 0.963

Minimizing downside loss is more important to overall performance than maximizing upside return.

Most Asset Allocation Models still work off of a 8-10% long-term rate of return for the broader markets.

Traditional Efficient Markets

conclusion.

Performance (12/1930-12/2010)

$1000 becomes

Annualized Return

Buy and Hold $74.08m 5.53%

Miss 30 Best Months

$3.47m 1.57%

Miss 30 Best & 30 Worst Months

$168.87m 6.62%

Miss 30 Worst Months

$3.60mm 10.78%

Apple begins with "why." " 'Everything we do, we believe in challenging the status quo. We believe in thinking differently. The way we challenge the status quo is by making our products beautifully designed, simple to use and user-friendly. Want to buy one?' "

The key to success is learning how to fail quickly!

Albert Einstein

An Interesting Analogy --

Quote by horse racing expert, Steven Crist:

“The issue is not which horse in the race is the more likely winner, but which horse or horses are offering odds that exceed their actual chances of victory…This may sound elementary, and many players may think they are following this principle, but few actually do…There is no such thing as “liking” a horse to win a race, only an attractive, discrepancy between his chances and his price.”

(Bet With The Best. New York Daily Racing Forum Press, 2001)

The Distinction Between Fundamentals and Expectations

Mom – •I didn’t make any money on the Derby. •What do you do?

Mom’s System – 1st Do I like the name?

2nd Have they made any money

Results – •You made more money then me. •We just do it for fun~ •I initially had Astrology

Economic Principles •Risk Reduction (both fear & greed) •Herd Mentality (how do they make the odds? •Trending •Risk vs. Reward •Peer Comparatives •Having a system •Forecasting vs. backwards looking •Sizing the bet •Regret

Picking winners vs making money!

Shackleford Wins Preakness Stakes In Nail-Biter (ran 5/21/2011)

Dad – Still studying the results (backwards looking)

$3.60

$6.80

$8.00

Betting to show = 21.% Betting to win =7%

We bet to show.

At the final turn, we had the top 4 horses.

Ended up with 2/3 of the winning horses.

Sizing the bet is the tough part – timing doesn’t matter.

How many names do you know?

What to look for:

“a fish swimming upstream!”

Money Managers that consistently beat their index tend to have a: • Value bias, • Run concentrated portfolio’s, • Control their turnover, • Operate geographically away from the normal market noise.

Hedge-Hunters Katherine Burton

Rich Bernstein Merrill Lynch, Chief Equity Strategist

•Risk Adverse

•Remain very humble

•Only Successful 58.5% of the time

‘Alpha’ is increasing obtained by beta, rather than manager value-added…True “alpha” has become rarer, so the [investment] manager who is indeed producing pure alpha

has become increasingly rare. Or – look for managers that operate outside the box naturally producing Alpha with-out having to leverage beta. Look for the Salmon

swimming upstream!

Michael Maubossian Legg Mason - Chief Equity Strategist

David Swensen CIO Yale University

•High Median Return •Low Correlation •Standard Deviation •Skewness •Kurtosis

In his recent open letter to investors, Robert Litterman

(Litterman 2003), Managing Director and Head of

Quantitative Resources at Goldman Sachs, defines

reliance on “the data not already fully digested by the

market” as one of the important factors to consider in

judging the investment skills of fund managers.

Intellectual Capital – Proprietary Information

“Proprietary Information - Fund Manager Use of Public Information: New Evidence of Managerial Skills”

MarcinKacperczyk and Amit Seru

Team Design Lean is Mean when it comes to a team!

Steve Johnson FT 11/6/07

In order to probe the relationship between public information and equity returns, the authors devised a measure of how aggressively and often mutual fund managers responded to analyst recommendations. They found that the more a manager did so, the worse his results. The authors concluded that “the value of a sophisticated investor derives from the private information he brings to the process.” Kacperczyk and Seru cannot possibly mean that successful fund managers are able to uncover material nonpublic raw data on a large number of companies. Rather than “private information,” I suspect what they meant was “private evaluation.” That is to say, successful manager demonstrate an ability to think for themselves. Whatever the authors’ precise meaning,, the message is clear: those who live by the buzz, die by the buzz.

“Too many cooks spoil the broth”, rather than “many hands make light work”, appears to be the apt proverb for the fund management industry. Research by Jim Hunter, a business psychologist who previously worked for the Association of Investment Trust Companies and Aberdeen Asset Management, suggests larger teams using team decision-making and managing more vehicles are more likely to underperform than small ones. He studied 54 UK fund managers from 27 companies and found that eight of the top 10 best-performing managers (measured using fund performance and independent ratings worked in teams of nine or fewer individuals. In comparison, only three of the bottom 10 worked ins such small teams. Six of the top 10 managers (and only 13 of the remaining 44) were responsible for nine or fewer vehicles, while the top two managers were both individual decision-makers, rather than relying on team approaches.

100 YearsR

2 = 0.9293

0

10

20

30

40

50

60

70

80

0 200 400 600 800 1000 1200 1400 1600

Predictive Factors --- Building a “new” Model

Interest Rates S&P 500 Earnings

An 20 year analysis of semi-annual U.S. Treasury bond yield forecasts as presented in the Wall Street Journal ………The analysis shows that the consensus estimate forecast is poor.

During this time period, 67 percent of the time the consensus estimate of the yield change is wrong in direction. The consensus estimate is only beneficial from a contrarian viewpoint.

Using a naïve forecast of the current yield results in a 25 percent reduction in the standard deviation

of forecast error.

(taken from a study by …… when asked if he’d updated the study to incl. the most recent 5 years …. Responded to me --- “why, has human nature changed?”)

Experts’ earnings predictions exhibit positive bias and disappointing accuracy. These shortcomings are usually attributed to some combination of incomplete knowledge, incompetence, and/or misrepresentation. Human desire for consensus leads to herding behavior among earnings forecasters.

Herding results in a reduction in the dispersion and an increase in the mean of the distribution of expert forecasts, creating positive bias and inaccuracy in published earnings estimates. Investors mistake reduced dispersion for reduced risk and positive bias for high future returns.

or

“A good hockey player plays where the puck is. A great hockey player plays where the puck is going to be!.”

Wayne Gretzky

Where to look --

Earnings Momentum

Traditional Earnings Surprise Triggers

Earnings Estimate Revision

Projected 5-year EPS Growth

R² = 0.0024

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1865 1885 1905 1925 1945 1965 1985 2005

R2

R2 for Quarterly Return versus Earnings

the Challenge

avoiding the …Herding behavior!

Experts’ earnings predictions exhibit positive bias and disappointing accuracy. These shortcomings are usually attributed to some combination of incomplete knowledge, incompetence, and/or misrepresentation. Human desire for consensus leads to herding behavior among earnings forecasters.

Herding results in a reduction in the dispersion and an increase in the mean of the distribution of expert forecasts, creating positive bias and inaccuracy in published earnings estimates. Investors mistake reduced dispersion for reduced risk and positive bias for high future returns.

Predicting – where to begin the search!

t3 Risk manager Equity Market Noise Level Indicator

Irrational Exuberance

Chicken Little (the sky is falling)

Which one is it?

Measuring Disagreement

A Variant Perspective: An opinion about something that rightly differs from the common wisdom!

- Michael Steinhardt

If you’re foolish enough to forecast – forecast often! Jamie Dimon CEO JP Morgan

Sector Rotation

30%

25%

20%

15%

10%

5%

-5%

-10%

-15%

-20%

-25%

-30%

IndustrialsConsumer

StaplesTelecom

Consumer

DiscretionaryHealthcare Energy Materials Financials Utilities

Information

Technology

30%

25%

20%

15%

10%

5%

-5%

-10%

-15%

-20%

-25%

-30%

Telecom IndustrialsConsumer

Staples

Consumer

DiscretionaryMaterials Healthcare Financials Utilities Energy

Information

Technology

Russell 3000

Sector Weighting Changes

S&P 500

Sector Weighting Changes

Increasing Chance of a

Negative Earnings surprise

Increasing Chance of a

Positive Earnings surprise

Example of Monthly Shift in Sector Emphasis

Telecom

Industrials

Energy

Materials

Consumer

Stapler

Healthcare

Consumer

Discretionary

Utilities

Financials

Info. Tech

“Our research continues to show that the rewards from accurately forecasting earnings surprises are much greater in the weeks before the earnings report than they are in the

weeks after the earnings report. Furthermore, the most significant rewards are obtained by correctly forecasting surprises from two to five weeks before the earnings report to

the week of the report.

Keith Miller – Citigroup Global Markets

Analysts move estimates up after the beginning of earnings seasons and

following the move up by the market.

Market starts to move Market move begins upward climb in advance of the beginning of the

earnings season.

Analysts move earnings estimates

up following the beginning of the

earnings season and after the market’s 1st

move

15.873% move

2..083% move

Analysts earnings revision based

models missed this move and caught

this one..

30

•Anticipate earnings surprises using a

quantitative macro- model w/fundamental

micro inputs and a technical overlay.

•Increase exposure to

upside surprises

•Decrease exposure to downside surprises.

Individual Security Model

Negative Earnings surprise

Positive Earnings surprise

Notice Volume lead/lag

Entry Points

Fundamental Inputs & Technical Overlay

Earnings Surprise viewed through a different lens.

Example of a tie (dell vs payx)

Technology Sector

+6.4%

Energy Sector Comparison of low score vs. high score in selected sector

(eqt vs vlo)

+20.59%

New names going into the

LCC model 6/11/2011

Active Share = .90

Quantitative Factor (1)

Fundamental Factors (6)

Technical Factors (2)

“What we are really trying to do is to think about thinking … Understanding how groups behave is central to understanding how complex adaptive systems – such as the stock market --- work.” Bill Miller, CFA

Legg Mason Capital Management

“Systematic outperformance requires variant perception: one must believe something different from what the market believes, and one must be right. This usually involves weighting publicly available information differently from the market, either as to its magnitude or it’s duration.”

“… In markets, everyone tends to see the same things, read the same newspapers and get the same data feeds. The only way to arrive at a different answer from everybody else is to organize the data in different ways or bring to the analytical process things that are not typically present ..”

“At t3 equity labs, llc, the market is viewed as a discounting mechanism. People buy and sell based on their expectations about the future. The key question in markets is always what is being discounted. Investors earn excess returns when expectations are different from what occurs, driven by heterogeneous time horizons or diversity breakdowns.

In an open letter to investors, Robert Litterman (Litterman 2003), Managing Director and Head of Quantitative Resources at Goldman Sachs, defines reliance on “the data not already fully digested by the market” as one of the important factors to consider in judging the investment skills of fund managers.

“The issue is not which stock in the race is the more likely winner, but which stock or stocks are offering odds that exceed their actual chances of victory … This may sound elementary and many investors may think they are following this principle, but not many do. There is no such thing as

“liking” a stock to win, only an attractive discrepancy between it's chances and it's price.” (adapted the Kelly Criterion to the equity markets)

“In Markets, competitive advantages are three: informational, analytical and behavioral … Behavioral advantages are the most interesting because they are the most durable…” Bill Miller, CFA

When ? Why ?

What ?

1420 18th Street, Denver, Co 80202 303.860.7386 (office) www.t3equity.com mike@t3equity.com

Downside risk management is significantly more

important than upside capture!!

Wall Street has it wrong!

Short-term capital gains vs. Long-term Buy and hold

t3 equity labs, llc All-Cap Core model

Period beg bal return end. val dividends cap gains div taxes cap gain tx ending balance Inv Mgt fees Tax Proc

$ annual % $ 2% $ 15% 35% $ (pre-tax)

2007 100000 23.13 125746 2000 23746 -300 -8311.1 117134.9 1128.73 200

2008 117135 -26.79 89028 2342.7 -30449.598 -351.4 0 88676.5953 1030.81 200

2009 88676.6 28.94 117411 1773.53 26960.8728 -266.03 0 117144.9702 1030.44 200

2010 117145 19.42 141605 2342.9 22117.1304 -351.43 -2790 138463.5651 1293.75 200

2011 138464 7.82 149183 2769.27 7950.16361 -415.39 -2782.5573 145985.052 1438.23 200

2012 145985 7.82 157044 2919.7 8139.24692 -437.96 -2848.7364 153757.3084 1515.15 200

10.0567 -2122.2 -16732.394

72611.9174 -18854.609 7437.11 1200

Long-term Buy & Hold Russell 3000

Period beg bal return end. val dividends cap gains div taxes cap gain tx ending balance Inv Mgt fees Tax Proc

$ annual % $ 2% $ 15% 15% $ (pre-tax)

2007 100000 5.14 105265 2000 3265 -300 104965 100

2008 104965 -37.31 71577 2099.3 -35487.3 -314.9 71262.105 100

2009 71262.1 28.34 93747 1425.24 21059.6529 -213.79 93533.21369 100

2010 93533.2 16.93 110329 1870.66 14925.122 -280.6 110048.4004 100

2011 110048 3 113011 2200.97 761.631634 -330.15 112680.8548 100

2012 112681 16.13 131748 2253.62 16813.5281 -338.04 -4978.1139 126431.8435 100

5.37167 33187.4262 -1777.5 600

-6755.5826

Michael C. Jackson

Michael Jackson founded t3 Equity Labs, LLC in April of 2006. He currently serves as manager-member and is responsible for designing and implementing all equity strategies. Mr. Jackson brings 25 years of experience in the areas of asset allocation and investment management. He began a successful career with Merrill Lynch, Private Client Group in 1989. While at Merrill’s Denver office, he held positions including Wealth Management Advisor and Certified Financial Manager, as well as being appointed the position of Portfolio Manager within the Personal Investment Advisory Program. He also earned the title of Certified Investment Analyst (CIMA), through the Investment Management Consultants Association, IMCA. While at Merrill Lynch he was responsible for assisting high net worth individuals, small and middle market institutions and selected non-profits with the management of their investment asset. He focused on managing risk through the design and implementation of a formalized investment policy statement, strategic long-term asset allocation strategy, professional manager search and professional portfolio performance review. Mr. Jackson currently serves on the board of his own foundation, the t3 Alpha Project. In the past, Mr. Jackson has served on the Finance Committee for the Archdiocese of Denver and the Development Committee of Mt. St. Vincent's School. He has served on the Board of Directors of The University of Notre Dame Club of Denver, Denver Athletic Club, The Denver Athletic Club Scholarship Fund, The University of Notre Dame Scholarship Fund, the Board of The Applied Research and Development Association, and on the Development Committee of The Seeds of Hope. Mr. Jackson holds a BBA degree in Business Management from the University of Notre Dame. He is currently studying for an MA in Economics at The University of Denver and is a thesis candidate.

(taken from Google’s IPO Offering Circular)

Google is not a conventional company, we do not intend to become one!”

Disclosure

Past performance is no guarantee of future results. All Investments carry a certain amount of risk. This material is being provided for informational purposes only and nothing herein constitutes investment, legal, accounting or tax advice, or a recommendation to buy, sell or hold a security. No recommendation or advice is being given as to whether any investment or strategy is suitable for a particular investor. It should not be assumed that any investments in securities, companies, sectors or markets identified and described were or will be profitable. All information is current as of the date of herein and is subject to change without notice. Any views or opinions expressed may not reflect those of the firm as a whole. Sector, capitalization and style weightings reflect the weightings as of 9/30/2012 based on the aggregate dollar value for a representative account; however, the preceding chart represents the actual performance of the representative account. All information is provided for informational purposes only and should not be deemed as a recommendation to buy or sell any security. The historical sector allocations identified and described do not represent all of the securities purchased, sold or recommended in the Rank Strategy. Past performance is no guarantee of future results. There is no assurance that a separately managed account will achieve its investment objective. Separately managed accounts are subject to market risk, which is the possibility that the market values of securities owned will decline and that the value of the securities may therefore be less than what you paid for them. Accordingly, you can lose money investing in a separately managed account.