Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected. George Soros

Im extremely fortunate to have the rewarding challenge of raising two boys. From an early age we have played all kinds of games to spend quality time together, and games have also served as a great medium to teach them lessons about life. In particular, we have played a lot of poker together as an effective way to gain

appreciation of probability and the complex dynamics of interactive games. If you ask either one of my boys whose cards they are playing they will immediately answer: the other guys!What my boys do not yet realize, is that understanding how people interact is something I must give a lot of thought to as an investor. After all, one of the key dynamics of markets, and in fact all of economics, is the interaction of people (economic agents) as they react to various incentives and to each others actions. One of the great contributors to understanding this

interactive dance was John Nash, who helped develop game theory and specifically the theory of non-cooperative games through his Nash equilibrium. With the recent death of Dr. Nash, I was compelled to review the core premise of game theory: end-game outcomes are often extremely difficult to predict, and often not intended by ANY of the player agents. I believe this vexing takeaway is one of the reasons markets are typically impossible to predict. However, you can derive some insight by studying how different investors actually make decisions, and thus trying to understand the different games that often drive markets in parallel.To help crystallize competing decision-making frameworks, I will use an example from Richard Thalers excellent new book on behavioral economics, Misbehaving. In the book, Thaler provides many examples of how economic theory says decisions should be made, and contrasts them with how decisions are actually made in the messy real world. In one example, two railroad tracks are laid down end to end, nailed down at the end points and meet in the middle. Each track is one mile long (5,280 feet) and expands to one mile plus one inch (5,280.08 feet) when it gets hot. Assuming the tracks maintain their linear shape, Thaler asks how high the expanded track is in the middle. The right way to answer this question is to realize that the expanded tracks form an isosceles triangle, where each half is a right triangle with a base of 5,280 feet and a hypotenuse of approximately 5,280.08 feet.

Sam Peters, CFA

Managing Director Portfolio Manager

Market Commentary

PORTFOLIO MANAGER COMMENTARY Second Quarter 2015

Fortunately, as active managers we have the luxury

and the discipline not to buy most stocks, and we are still

finding exploitable pockets of absolute value in financials,

legacy tech and in the broad power generation sector.

2MARKET COMMENTARY

You can then simply plug this into the Pythagorean Theorem: a2 + b2 = c2 where you are solving for b. The correct answer is almost 30 feet. The problem is that most peoples answer is around two inches. Whats a gap of almost 360 inches or an error of over 99% among friends?What this example, and several other fantastic examples in the book, illustrates is that we often frame the financial market as a well-ordered machine, where people converge on some concrete truth as they assess a set of objective probabilities. The reality is that people rely heavily on intuition and a subjective set of rules or heuristics when making decisions. This process is further complicated by the interplay and feedback of each decision on other competing decisions. This is why markets are a complex adaptive system, and we reflect this framing into our investment process. How so?First of all, as fiduciaries and long-term valuation investors, we are consistently trying to solve for business value using a disciplined process: typically by discounting the future free cash flows that we think a business will generate over time. This gets to the heart of our process, which is trying to find stocks where price is well below business value, and we generate returns from price-to-value convergence. In the spirit of the example, we are trying to find opportunities where other investors are pricing something at two inches, while our business-value math suggests 30 feet is the right answer. In most cases, the market gets pretty close to our illustrative 30 feet. In these cases, we have no differentiated view and we naturally dont bet. However, the market sometimes gets it wrong, at times by a large margin, and we always stand ready to take advantage of such opportunities.The key here is that doing simple valuation math is critical, but it is not enough to ensure a long-term opportunity. Ultimately, we are in the judgment business, and given the zero-sum competitive nature of stock picking, we must try and solidify what the person on the other side of a given transaction is getting wrong. Essentially, why are our expectations for a given business different than what the market has priced into the stock?To provide some rigor to our judgment and to reflect the inherent uncertainty of looking into the future, we rely on subjective probabilities of what might happen to a given business over several quarters and years. Basically, we create a probability tree that assigns different business values to a whole range of scenarios, varying from the nightmare to the best-of-all dreams. This range of potential outcomes allows us to calculate

a probability-weighted expected value for a given stock, explicitly detailing the scenario that the market weights most highly and visualizing the magnitude of our variant perception. In many ways, our subjective probabilities reflect our knowledge of a given stock, but they also help quantify our ignorance.This probability framework also beautifully reflects the time-driven dynamic of financial markets and uncertainty: as events occur through time, different scenarios get pruned away as the cone of uncertainty ultimately narrows to a single outcome. A big part of our job is to observe these events and stay ahead of the updating process by continuing to ask the critical question: are we right or is the market? This nearly mathematical nature of markets is inherently humbling if you are paying attention, as it highlights mistakes and compels you to change your mind. Our process forces us to pay attention, and we are constantly learning and adjusting.These are the basic process rules and the probability framework we utilize as long-term investors playing a very serious game. Aside from knowing the expectations of the other players in the market and identifying which of those we are betting against, another critical factor is to understand that the financial markets have several games with different rules being played in parallel. Each of these games has an impact on price, which further influences decisions. Thus, it is impossible for an investor to operate in isolation, and it is typically a worthwhile advantage if an investor understands the different decision-making frameworks at play in competitive markets.Probably the most dramatic and long-standing divide is between active and passive investing. Active investors, like us, pick individual stocks we deem attractive, and create portfolios that are highly differentiated from an index. Passive investors simply try to mimic an index. Increasingly, and certainly during this market cycle, the tide of capital has been shifting to passive. The general argument is that stock picking is futile, making it impossible to beat an index, and now ETFs can provide passive exposure and the same liquidity as stocks.Although we welcome the continued shift to passive, as it means less competition for our active valuation strategies, the increasing influence of passive money on the price action of stocks affects both the timing of the price-value convergence of our holdings, as well as the path toward such convergence. Every investment strategy has some Achilles heels and passive is certainly no exception:

3PORTFOLIO MANAGER COMMENTARYSecond Quarter 2015

Diversity Breakdown: The whole goal of passive is to harvest the markets long-term return at a low cost. With equity indexing you are technically trying to capture an equity-risk-premium (ERP), typically with a market coefficient or beta of one, plus an underlying risk-free-rate. The key to this approach is that you assume there are enough active investors like us around to do the math and price the underlying assets efficiently, or as close to 30 feet in our Pythagorean example as possible. Essentially, passive treats stocks like a commodity, but a commodity that gets priced approximately right as supply and demand for stocks gets sorted out by a diverse set of players. The problem arises when passive overwhelms active as holder of a given stock, resulting in a nasty feedback loop where past price moves determine future price moves. In these situations, if price is going up passive managers must buy more stock, which further increases the price. Taken to extremes, this pricing diversity breakdown can push a stock a long way from its fundamental underpinnings. The most dramatic example was in the 1999 tech and U.S. mega-cap stock bubble that pushed equity valuations to absurd levels. Using the historic ERP chart below, U.S. stocks got priced to a 2% ERP (Exhibit 1), and the best strategy was simply to own anything but the index.

Herding and Liquidity Risk: Increasingly, passive is getting exploited in an expensive active wrapper, in the guise of dynamic asset allocation. The problem is that much of this activity simply amplifies an underlying bias of human nature to buy an asset class that has performed well, with resulting high realized returns but low expected returns, coupled with a simple and sexy story. The explosion of ETFs has encouraged this price-and-story activity, resulting in lots of short-term activity that consumes liquidity in often relatively illiquid underlying stocks. The underlying price distortions are growing as the industry grows, and we agree with many market observers that we risk a future bear market in liquidity that will severely test this new approach to passive investing.

In fairness, much of the asset allocation industry understands the pitfalls of the price-and-story approach, and is indexing on return-drivers or smart-beta factors other than price, such as valuation and quality. The problem is that these approaches are designed to harvest factor-driven returns over very long periods of time, and too often people are now simply chasing factors on a short-term basis. This led to a great crowding in quant strategies that broke down dramatically in the fall of 2007. In just a few weeks, the models turned upside down, and several years worth

Exhibit 1: Equity Risk Premium U.S. (Jan. 1960 June 2015)

Source: Aswath Damodoran (http://pages.stern.nyu.edu/~adamodar/), ClearBridge Investments.Equity Risk Premium: Excess return above the risk-free rate that compensates investors for taking on the relatively higher risk of investing in equities. Data calculates implied equity risk premium by using free cash flow to equity (FCFE) for the S&P 500 Index. Treasury rate used is the constant-maturity U.S. 10 year bond including coupon and price appreciation.

2.05% inDec. 1999

Credit CrisisPeak: 7.68% in

March 2009

7.64% inSept. 2011

5.74%June 1, 2015

Average

-1 Standard Deviation

+1 Standard Deviation

1%

2%

3%

4%

5%

6%

7%

8%

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Equi

ty R

isk

Prem

ium

4MARKET COMMENTARY

of returns melted away in just a few short weeks. Again, every strategy has its Achilles heel, and popularity and illiquidity are typically the culprits, as you end up with assets priced for all risk and no return.The rising popularity of passive clearly does create opportunity for us, as it is coupled with risk controls on many active managers that dont allow them to buy stocks that are going down or not sell stocks that are going up. This one-sided and pro-cyclical behavior is likely creating even bigger gaps between price-and-value. However, this also makes the risk of our strategy abundantly clear, which can be framed in a much modified version of Newtons First Law of Motion: a stock in motion will remain in motion until acted on by an outside force. That outside force is typically a valuation manager, but the crowd and emotion can take a stock a long way from fair value, and you may not have any capital left for the return trip to fair value. This is why we enforce quantified humility through our probability-driven process: we always leave room for being wrong and accordingly never bet the portfolio on a narrow set of outcomes.Despite the diminishing influence of active, this cycle has featured a dominant active stock picker in the guise of the companies themselves. In many ways, companies

have acted as managers of single-stock portfolios and in aggregate have aggressively bought back $1.7 trillion of their own stock since 2009. As animal spirits have risen, boards have become increasingly comfortable with an uncertain future and have started to acquire other companies. The financial engineering logic behind these deals speaks for itself, given the ability to buy existing cash flow streams with cheap debt, and remarkably roughly 2/3 of buying companies are seeing their stocks increase along with the selling companies. Nothing like 2 + 2 = 5 corporate alchemy can fan the flames of deal activity, and we are not surprisingly seeing historically high deal activity at historically high valuation levels (Exhibit 2).Increasingly, deal activity is coming to dominate the returns in U.S. stocks, especially against the backdrop of flattish equity returns year-to-date. We have benefitted directly from deal activity, both as owners of acquiring companies that went up a lot, such as NXP Semiconductors (NXPI) and Expedia (EXPE), but also as owners of targeted companies Perrigo (PRGO) and Broadcom (BRCM). In the case of the two targets, the offer price was very close to our assessment of business value, which suggests good valuation work on our part and provided a welcome catalyst for price-and-value convergence.

Exhibit 2: U.S. M&A Volume and Median Total Value/EBITDA Valuation (H1 Data Only From 1996 2015)

Source: Bloomberg Finance, L.P., ClearBridge Investments.Data includes M&A deals involving private and public U.S. target companies with deal value above $50M.Data set includes completed, pending and proposed M&A deals as of June 30, 2015.

7x

8x

9x

10x

11x

12x

13x

14x

15x

16x

17x

$0

$200

$400

$600

$800

$1,000

$1,200

H1 1996

H1 1997

H1 1998

H1 1999

H1 2000

H1 2001

H1 2002

H1 2003

H1 2004

H1 2005

H1 2006

H1 2007

H1 2008

H1 2009

H1 2010

H1 2011

H1 2012

H1 2013

H1 2014

H1 2015

Total Value (TV

)/EBITDAD

eal V

olum

e ($

Bill

ions

)

Deal Volume (Left Axis) Median TV/EBITDA (Right Axis)

5PORTFOLIO MANAGER COMMENTARYSecond Quarter 2015

The challenge for long-term investors is that if stocks got pushed to 2 inches during the great financial crisis, deals are now pushing price towards fair value at 30 feet and beyond. Not surprisingly, at this point, we find many U.S. stocks broadly uninteresting, and yet we expect pro-cyclical deal activity to likely push price well above business value for many stocks. Besides this rising valuation risk, we also expect that many deals will fail to meet current investor and boardroom expectations, and some of the popular current roll-up companies will inevitably blow up on poorly executed integration and mismanaged complexity. As in all market cycles, as the perception of future uncertainty fades, valuation and risk rise, and our jobs as valuation managers gets tougher.Fortunately, as active managers we have the luxury and the discipline not to buy most stocks, and we are still finding exploitable pockets of absolute value in financials, legacy tech and in the broad power generation sector.Our financial stocks have recently performed well as interest rates have moved up, and indeed some of our holdings are closing in on fair value. However, the majority of our financial holdings are still just climbing out of the valuation basement of the housing crisis, persistently low interest rates and crushing regulatory costs. As a result, our core financial holdings, including Citigroup (C) and American International Group (AIG), are currently enjoy improving fundamentals and capital return profiles, which we think are still not fully reflected in price.

The legacy tech names we own, such as Microsoft (MSFT) and Cisco Systems (CSCO), continue to generate massive free-cash-flow (FCF) streams, which are valued at narrowing, but still substantial discounts from the overall market. The valuation discount of legacy tech reflects the ever-present risk of disruption, especially from the accelerating and dramatic transition to the cloud. Our goal is to find tech stocks that reflect the disruption risk of cloud, but have durable cash flow streams that will allow them to transition and in some cases thrive in a cloud-based world.

The power generation, natural gas and coal sectors are all in various states of recession to depression. Power prices are depressed from weak demand, natural gas

remains over-supplied thanks to massive productivity gains from shale drilling, and the coal industry needs to cut supply by almost 40% to balance the market. Supply and demand fundamentals will improve with time, but we expect a rash of coal bankruptcies, further gas supply cuts and the retirement of many coal-fired power generation plants in the meantime. Fortunately, the lack of any current fundamental tailwinds and the time required to improve these fundamentals over the next several quarters is allowing us to buy trough fundamentals at trough valuation levels. In particular, AES (AES) and Calpine (CPN) continue to generate very strong free-cash-flow streams, are valued at double-digit FCF yields, and will benefit from any improvements in power pricing. In the even more depressed gas and coal sector, CONSOL Energy (CNX) is one of the few well-capitalized coal and natural gas companies, with low-cost production assets in both segments. Fortunately, CNX saw the writing on the wall for coal during the China-induced coal boom of last decade, and wisely diversified into gas. CNX is now proactively separating its coal and gas assets, and we think we are getting very cheap high-quality gas assets due to the coal overhang.Even with the continued convergence of price and value in most U.S. stocks, our focus on absolute value has allowed us to maintain attractive potential risk-adjusted upside in the portfolio. We track this potential on a daily basis, and the current potential return profile of the portfolio is similar to levels achieved during the deflationary-driven correction that occurred last October. This upside potential is not at the homerun levels we enjoyed a few years ago, but it is still absolutely attractive, and extremely attractive relative to most fixed-income alternatives.

In closing, we are in the judgment business, and our job is to execute an investment process that exploits expectation-driven gaps between price and underlying business value. Our judgment of these valuation opportunities is constantly evaluated by a probability-driven framework, which reinforces humility and constant learning. We could not execute this process without the long-term culture of ClearBridge that encourages investors to truly invest, and more importantly, without the quality and long-term orientation of our shareholders.

6MARKET COMMENTARY

Past performance is no guarantee of future results. Copyright 2015 ClearBridge Investments.All opinions and data included in this commentary are as of June 30, 2015 and are subject to change. The opinions and views expressed herein are of Sam Peters and may

differ from other managers, or the firm as a whole, and are not intended to be a forecast of future events, a guarantee of future results or investment advice. This information should not be used as the sole basis to make any investment decision. The statistics have been

obtained from sources believed to be reliable, but the accuracy and completeness of this information cannot be guaranteed. Neither ClearBridge Investments nor its information providers are responsible for any damages or losses arising from any use of this information.

ClearBridge Investments100 International Drive, Baltimore, MD 21202 | 800 691 6960

ClearBridge.com

Retu

rns

Year To Date

Index Name June QTD YTD

S&P 500 Index -1.9% 0.3% 1.2%

Dow Industrials -2.1% -0.3% 0.0%

Nasdaq Composite Index -1.6% 2.1% 6.0%

S&P 100 Index -1.8% 1.3% 1.1%

Russell 1000 Index -1.9% 0.1% 1.7%

S&P Mid-Cap 400 Index -1.3% -1.1% 4.2%

Russell 2000 Index 0.7% 0.4% 4.8%

Russell 1000 Growth Index -1.8% 0.1% 4.0%

Russell 1000 Value Index -2.0% 0.1% -0.6%

Broad U.S. Market Indices

Index Name June QTD YTD

FTSE 100 Index (UK) -3.6% 3.1% 2.4%

DAX Index (Germany) -2.5% -4.9% 2.4%

CAC 40 Index (France) -2.2% 1.2% 6.0%

MICEX Index (Russia) -2.0% 8.2% 20.7%

NIKKEI 225 (Japan) 0.1% 3.6% 14.4%

Hang Seng Index (Hong Kong) -3.0% 7.2% 13.7%

Kospi Index (South Korea) -2.3% 0.8% 6.2%

Shanghai SE Composite (China) -7.0% 14.8% 33.1%

BSE Sensex 30 Index (India) 0.4% -2.1% 1.2%

Brazil Bovespa Index 3.0% 7.0% -9.5%

Broad Foreign Market Indices (USD)

Index Name June QTD YTD

S&P 500 Consumer Discretionary 0.6% 1.9% 6.8%

S&P 500 Consumer Staples -1.8% -1.7% -0.8%

S&P 500 Energy -3.4% -1.9% -4.7%

S&P 500 Financials -0.3% 1.7% -0.4%

S&P 500 Health Care -0.3% 2.8% 9.6%

S&P 500 Industrials -2.5% -2.2% -3.1%

S&P 500 Information Technology -4.3% 0.2% 0.8%

S&P 500 Materials -3.9% -0.5% 0.5%

S&P 500 Telecomm Services -2.3% 1.6% 3.2%

S&P 500 Utilities -6.0% -5.8% -10.7%

Source: Bloomberg (through June 30, 2015).Past performance is no guarantee of future results.All returns are in U.S. dollars.

S&P 500 Sector Indices

-4%

-2%

0%

2%

4%

6%

8%

10%

January 2015 March 2015 May 2015 July 2015

S&P 500 IndexDow Jones Industrial AverageNasdaq Composite Index