Balter Capital Management Hedge Fund Regional Performance Study

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Hedge Fund Regional Performance Study

A Statistical Review of Historical Performance By U.S. City

Executive Summary

This paper represents Balter Capital Management’s inaugural regional study of hedge fund manager returns.

We are not aware of any similar studies that have been done to date and we expect that there will be a number

of items that will need to be updated and improved upon as we move forward in publishing this review on an

annual basis. We have long believed there are broad based regional differentials in hedge fund manager

returns. The basis of this thinking came from the following factors:

1. Managers in the same locale often seem to traffic in a similar set of names/securities/themes.

2. The presence of social events, idea dinners and familiarity seem to lead to further concentration of ideas.

3. Manager fee structures tend to differ across locales.

4. The relationship and tolerance for risk may differ across geographical regions.

5. Hedge fund strategy sub groups (e.g., long/short technology) may have heavier concentration in some

areas versus others.

Methodology

The objective of this research paper is to identify and investigate whether there were differences in hedge fund

returns based on their geographical location within the United States. For our first study, we identified seven

cities; the criterion for the inclusion of a city was our ability to identify at least 30 hedge fund firms with valid

long term data sets for the 12 year period from January 2000 through December 2011. Our findings indicate

that many major hedge fund index providers offer indices with fewer than 30 managers, including Dow Jones

Credit Suisse and HFR. The cities we identified for this first study were Boston, Chicago, Dallas, Greenwich, Los

Angeles, New York and San Francisco. Going forward we would look to include other areas such as Denver,

Philadelphia, Miami and Minneapolis, along with the potential to add international locations such as London,

Hong Kong, and Toronto. The most important factor in delivering credible conclusions is the need to confirm

sets of data that have sufficient depth and longevity.

We used our proprietary internal database for the data set with the following evaluation methodology:

1. Only one set of returns was included from each hedge fund firm, as opposed to multiple products.

2. We selected the fund at the firm that had the longest return history.

3. When the return history was the

same for both the onshore and

offshore vehicles, we defaulted

to the onshore fund.

4. We excluded funds of funds

from our study.

5. The resulting returns compiled

are equally weighted.

6. The monthly return for each

index is a simple average of all

returns available for that month.

70

86

33

96

66

131

83

0

20

40

60

80

100

120

140

Boston Chicago Dallas Greenwich Los Angeles New York San Francisco

Managers by region

December 2012 3 of 18

As with any hedge fund index, structural weaknesses exist. There will be the typical biases that most industry participants are aware exist in almost all hedge fund studies. Furthermore, because we only included live managers in our study, these biases are likely to be more pronounced in our city composite indices. These weaknesses are mitigated to some degree, as each index contains the same biases; therefore the comparisons to each other may carry more weight than comparisons against other market or hedge fund indices. Biases include but are not limited to:

Selection bias: Not all hedge fund managers report results consistently to a database.

Survivorship bias: Hedge funds that go out of business are typically dropped from hedge fund

databases. As a result survivorship bias tends to overstate hedge fund returns.

Backfill bias: Also known as instant history bias, this occurs when a hedge fund is added into the index

and its historical returns are “backfilled” into the return history. Our city indices are entirely backfilled

given that they were created for the purpose of this study.

Performance Review

January 2000 – December 2011; 12 Year Period

Over the full twelve year period we studied from January 2000 to December 2011 annualized returns for the

various cities ranged from +9.33% to +13.64%, with Chicago at the top‐end and San Francisco at the bottom.

While Boston was the second best performing city over the aggregate period, it was outperforming Chicago by a

narrow margin through early 2007 before experiencing losses that led to material underperformance onwards.

Los Angeles, San Francisco and Greenwich were consistently the worst performing cities with New York City

remaining at the middle of the pack for the duration of the study.

1,000

2,000

3,000

4,000

5,000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Growth of $1,000Jan 2000 ‐ Dec 2011

Boston Chicago Dallas Greenwich Los Angeles New York San Francisco



During the last ten years, Chicago and Dallas were the best performing cities at +12.80% and +11.53%,

respectively, on an annualized basis. While the remaining cities were tightly clustered, the worst performers were

San Francisco and Greenwich at 8.42% and 8.83%, respectively. The most material change from the twelve year

performance record to the ten year performance record was Boston, whose return decreased ‐2.15% on an

annualized basis. The drop in performance was due to the years 2000 and 2001 rolling off the return history

which were both particularly strong years for Boston. Amongst the 70 funds that we utilized in constructing our

Boston index, there are a notable number of

long/short hedge funds that utilize a value

investment approach. Given the relative

outperformance of value stocks versus

Technology, Media, and Telecom (TMT)

stocks over this period, it comes as no

surprise that Boston saw such a precipitous

decline in the annualized return of the index

once these years were no longer included.


The last five years is an interesting period to analyze because it includes both the pre‐ and post‐2008 financial

crisis periods. Over this period Dallas and Chicago have been the best performing cities at +9.34% and +8.82%,

respectively, outperforming the remaining geographies by more than 200 basis points on an annualized basis.

Boston’s performance degradation continued during this period with their annualized returns falling an

additional ‐4.26% (versus trailing 10 year period), more than any other city. The worst performing city was San

Francisco, with a spread of nearly 400 basis points less than Dallas; a spread that is fairly consistent between

these two areas for a 5, 10, and 12 year period. Not surprising, poor relative performance in 2007 and 2008 was

the primary contributing factor that drove annualized returns over a 5 year stretch. As we begin to assess 1, 2,

and 3 year performance records, returns begin to materially converge which is fairly obvious in the statistical

charts that you will see over the course of this report.

Performance During Market Stress

Greenwich was consistently the best performing city during the three periods of substantial market stress that

was witnessed over the duration of the study while New York was the worst performing city in two of the three

periods. In aggregate, both San Francisco and Los Angeles captured a higher percentage of market drawdown

than the other cities. While top honors go to Chicago as the best overall performer over the 12 year period, it

only distinguished itself from a capital preservation standpoint in 2007 – 2009. Greenwich and Boston were the

best performing cities during the market correction in 2011, experiencing a drawdown of slightly more than 40%

of the broad market. New York has done the poorest job of preserving capital over time, capturing 17.9% of the

drawdown in 2000/2002 and 62.6% of the drawdown in 2011.

City 1 Year 2 Years 3 Years 5 Years 10 Years 12 Years

Boston ‐1.63 4.90% 13.08% 5.49% 9.75% 11.90%

Chicago ‐1.08 7.33% 12.62% 8.82% 12.80% 13.64%

Dallas ‐0.25 6.97% 10.62% 9.34% 11.53% 11.53%

Greenwich ‐1.28 4.96% 11.07% 6.72% 8.83% 9.89%

Los Angeles ‐2.61 5.20% 13.81% 5.01% 8.90% 9.35%

New York ‐2.48 5.15% 12.59% 6.46% 9.57% 10.49%

San Francisco ‐0.07 7.71% 12.69% 5.37% 8.42% 9.33%

ANNUALIZED PERFORMANCE (Jan 2000 ‐ Dec 2011)


8/00 ‐ 9/02 10/07 ‐ 2/09 5/11 ‐ 9/11

Boston 7.1% 39.5% 41.8%

Chicago 10.4% 26.9% 43.7%

Dallas 9.1% 29.7% 44.2%

Greenwich 3.4% 24.4% 40.9%

Los Angeles 8.4% 43.9% 51.6%

New York 17.9% 39.5% 62.6%

San Francisco 13.0% 47.0% 49.1%

HFRI Composite 14.3% 42.0% 55.2%

Drawdown Capture Percentage

We observed that, as a group, hedge funds seem to be having more difficulty protecting capital during market corrections than they did in the earlier years of the study. During the 2000 – 2002 internet bubble market correction, hedge funds (as defined by the HFRI Composite Index) were able to shield investors from most of the market correction, capturing only 14.3% of the drawdown. This metric increased to 42.0% in 2007 – 2009 and 55.2% in 2011. We attribute the worsening down market protection to rising correlations amongst asset classes globally. The 2000 – 2002 drawdown was largely driven by a selloff in technology stocks but there were areas of the market, particularly value stocks, that were up during the period. The drawdown in 2007 – 2009 and 2011 were characterized by fears of a systemic collapse with all risk assets selling off indiscriminately. No city, including the HFRI Composite Index, improved their drawdown capture from 2007 – 2009 to 2011.

Correlation to Major Asset Classes

Chicago and Dallas had the lowest correlation to global equity markets while New York and San Francisco had

the highest. Chicago had the lowest correlations with every equity oriented index and the highest correlation

with low risk assets such as the Barclays Aggregate Index (fixed income) and the Barclays U.S. Treasury Index.

We attribute this to the large number of Commodity Trading Advisor funds (CTA) in the city. Dallas had low

correlations to all market indices, which we believe is due the diversity of hedge fund strategies employed by

managers in the area. Correlations for all locations were higher for the Russell 2500 (mid‐cap equities) than they

were for the S&P 500 (large‐cap equities). We believe that this is because long/short equity hedge funds tend to

target mid‐cap equities for inclusion in their portfolios. New York had a 0.88 correlation to the Russell 2500

Index, which is extremely high and implies to us that managers in the city are actively involved in trading mid‐

cap securities, perhaps to the point where they may be influencing the behavior of the underlying index. Los

Angeles had the highest correlation to high yield bonds at 0.80, which is likely due to the concentration of large

credit managers that are based in the area. We believe their presence in the city contributes to trading in non‐


investment grade credit through both idea sharing and natural attrition of skilled analysts to start their own

firms or join smaller firms where they may have higher compensation potential. The difference in correlation

between growth (+0.85) and value (+0.74) stocks was greater in San Francisco than in any other city. The

presence of venture capital firms and technology companies in the Bay area and the San Jose peninsula likely

foster a mentality of “growth investing” in the hedge fund community.

Correlation to Hedge Fund Strategies as a Whole

With the exception of Chicago and Dallas, all cities had very high correlations with the HFRI Composite Index and

both the long/short equity and event driven strategies. New York and San Francisco had the highest correlation

to hedge funds, implying that the managers in those cities are undifferentiated and performing in‐line with the

overall hedge fund industry. New York and San Francisco’s correlation to long/short equity hedge funds was

close to 1 in both cases, which is fairly logical given the concentration of pure long/short equity hedge funds in

each city. Chicago had the highest correlation with Global Macro (+0.63) and CTA (+0.62) strategies which is not

unexpected given that there are a large number of CTA managers in the city. Greenwich also had a relatively

high correlation with Global Macro (+0.62) compared to other cities. Intuitively this makes sense to us as some

of the largest Global Macro managers in the country are based in the Greenwich area.

Market Capture Ratios

Up market capture ratios for all cities trended together during the period, starting relatively low, peaking in the

middle of 2008, and then retreating to new lows following the 2008 financial crisis. New York maintained the

highest up market capture ratio while Greenwich maintained the lowest on average during the period. As

Index Boston Chicago Dallas Greenwich Los Angeles New York San Francisco

S&P 500 0.71 0.42 0.55 0.65 0.69 0.78 0.72

Russell 2000 0.73 0.45 0.57 0.73 0.75 0.86 0.84

Russell 2500 0.77 0.48 0.60 0.75 0.78 0.88 0.85

Russell 2500 Growth 0.72 0.38 0.56 0.69 0.74 0.87 0.85

Russell 2500 Value 0.75 0.52 0.58 0.72 0.72 0.77 0.74

MSCI EAFE 0.76 0.54 0.65 0.75 0.78 0.81 0.78

MSCI World ex‐U.S. 0.77 0.55 0.67 0.77 0.79 0.82 0.79

MSCI Emerging Market 0.79 0.51 0.70 0.77 0.81 0.84 0.81

S&P GSCI 0.45 0.42 0.50 0.48 0.49 0.42 0.49

Barclays High Yield 0.72 0.40 0.52 0.63 0.80 0.72 0.68

Barclays Agg. 0.06 0.16 (0.04) 0.03 0.08 (0.04) (0.01)

Barclays U.S. Treasury (0.25) (0.01) (0.24) (0.24) (0.26) (0.33) (0.29)

Correlation to Major Asset Classes (Jan 2000 ‐ Dec 2011)

Index Boston Chicago Dallas Greenwich Los Angeles New York San Francisco

HFRI Composite 0.89 0.55 0.77 0.89 0.89 0.96 0.95

HFRI Equity Hedge 0.88 0.55 0.75 0.88 0.89 0.96 0.96

HFRI Event Driven 0.88 0.53 0.76 0.87 0.89 0.94 0.92

HFRI Macro 0.45 0.63 0.49 0.62 0.44 0.47 0.48

Barclays CTA 0.12 0.62 0.18 0.35 0.11 0.04 0.08

Correlation to Hedge Funds (Jan 2000 ‐ Dec 2011)


noted, up market capture ratios are at all time lows for each city and we believe there are a few explanations.

Most notably, equities have seen a strong resurgence following the financial crisis and hedge funds have rarely

participated fully in such market environments. Hedge funds have also been carrying lower net exposure than

they have in past periods with Morgan Stanley Prime Brokerage reporting net exposure at the end of 2011 was

~40% net long compared to ~60% net long in 2005 and a peak north of 75% in late 2007. This is certainly a

contributing factor for the general underperformance of hedge funds and likely reflects broad based concerns

that range from economic uncertainty to a lack of clarity on how the regulatory environment may change for the

asset class.

With the exception of Dallas, down market capture ratios for all cities trended in the same direction. The most

notable deviation to the general trend was in 2007 when Dallas experienced a substantial negative (positive for

investors) down market capture ratio. We believe that this is can be attributed to the short subprime trade that

various Dallas‐based managers had on at the time. This reinforces our belief that idea sharing is commonplace

in all geographies. In the period since the 2008 financial crisis, cities appear to have clustered at two different

levels. New York, San Francisco, Boston and Los Angeles currently have down market capture ratios in the 30%

to 40% range while Dallas, Greenwich and Chicago are in the low 20% range.


Rolling Correlation

In some cities, correlation to the S&P 500 Index shifted dramatically over the course of the period we studied.

The most notable shift was in Chicago which started with a rolling 48 month correlation of 0.07 and ended the

period at 0.80. Dallas had a large correlation shift of its own, starting the period at 0.60, falling to a low of 0.18

in the middle period and rising to 0.67 at the end of the period. As it stands, Dallas has the lowest rolling 48

month correlation as of December 31, 2011 while New York had the highest correlation, on average, to the S&P

500 during this period. Correlations for virtually all risk assets have been rising since the 2008 financial crisis,

which has also been the case for the various city indices we have compiled.

Correlation to the HFRI Composite Index has been steadily rising for all cities over the period. The most

dramatic rise can be seen in Chicago, where correlations rose from 0.14 at the start of the period to 0.90 by the

end of the period. For the aggregate period, Dallas maintained relatively low correlation while New York and

San Francisco both had correlations in the high 0.90’s. Correlations for all cities began to converge in late 2008,

which is consistent with virtually all risk assets globally. Currently Dallas and Chicago exhibit the most

differentiated behavior from the overall hedge fund industry.


Standard Deviation

The level of standard deviation (a common measure of volatility and risk) between the cities has been quite

different over the period while the overall trend has been quite similar. Chicago stands out as it initially had the

highest volatility of any city but since 2008 has fallen to the middle of the pack. Greenwich consistently had the

lowest standard deviation on average, and is currently well below any city as well as the HFRI Composite Index.

We attribute this to global macro exposure, a strategy that tends to exhibit lower levels of volatility, which is

prevalent in the city. Los Angeles had the biggest swing in volatility reaching a low of 3.5% in early 2007 and

topping all cities at 10% at the end of 2011. We suspect that this is due to credit managers shifting from the

utilization of internal pricing models to market‐based pricing models in 2007 – 2008.

Beta to the S&P 500 Index

The range of betas (a measure of market sensitivity) for the cities was quite wide. Chicago has had the greatest

variation over time ranging from near zero at the start of the period and rising to a north of 0.60 during the first

part of 2006. This does not come as a surprise to us as we’ve discussed the concentration of CTAs in Chicago

that use trend following models. These models tend to look to increase exposure to the market as it is going up

and reduce exposure as it is going down. Dallas, on average, had the lowest beta during the period. New York

had the highest beta, on average, during the period which is consistent with the city having the highest up and

down market capture ratios. Since 2008, beta for all cities has leveled off. We believe this is due to two factors;

rising correlations amongst all asset classes and deliberate intentions by hedge funds to maintain more

conservative net exposures. The betas for New York, Los Angeles and San Francisco have been virtually identical

since 2008. The HFRI Composite’s beta falls in the middle of all the cities, which is to be expected given the

broader scope of the index.


Conclusions

Our findings suggest that hedge fund performance behavior varies widely depending on the geographical

location of the firm. A major contributing factor to differences in performance is likely driven by the style and

strategy of hedge funds that are most prevalent in a particular city. We believe that cities develop areas of focus

related to the existence of large asset management firms that inevitably see talent leave to start their own firms.

Given the manner in which they are trained, each newly established firm in a given area is likely to have similar

portfolio exposures, intentionally or not. We have seen multiple incidences of shared trades in a given city,

most notably the short subprime trade witnessed in Dallas in 2007. While various measures of risk and return

produced distinct results across our sample set, most cities experienced similar trends.

Boston: Boston was the second best performing city during the period, returning +11.90% annualized. Despite

its overall standing, performance trailed off materially after 2001, when value stocks outperformed growth

oriented equities. Boston had the highest correlation to the Russell 2500 Value Index which implies that

managers in the city are actively investing in value stocks and that is consistent with the fact that there are

numerous high profile value oriented hedge funds in Boston. With the exception of 2008 – 2009, Boston did a

better job than most cities preserving capital during market corrections. Correlation to the broad market and

hedge fund indices was generally in the middle of the group. Similarly, market capture ratios, beta and standard

deviation trended with the overall group and were undistinguished.

Chicago: Chicago was the best performing city in the study, returning +13.64% on an annualized basis, and

outpaced its closest competitors by more than 1.5% per year. Chicago performed well during periods of market

stress and was the second best performing city during the 2008 financial crisis. The prevalence of CTAs may

explain the performance difference, which is consistent given the meaningful correlation to the CTA Index at

0.62. Correlation to the HFRI Global Macro Index was also high at 0.63. Chicago also had the lowest correlation

to the broad market and to the HFRI Composite Index during the period. On the other hand, we also note that

Chicago had the highest standard deviation, which reduces their risk adjusted returns as illustrated by their

Sharpe Ratio of 1.26, the median of the group.

Dallas: Dallas was the 3rd best performing city during the entire period, producing annualized returns of

+11.53%, while having the best performance over the last 5 years. The superior performance could be partially

impacted by the fact that funds in Dallas have lower compensation structures than funds in other parts of the


country. Dallas was amongst the best at preserving capital during periods of market stress and exhibited lower

correlation with the broad market and hedge fund indices than any other city, with the exception of Chicago.

We attribute this partly to a diverse group of underlying strategies within the city. In the 2007 time period,

Dallas exhibited much lower down market capture and beta than all of the other cities, which we believe is due

to the short subprime trade that some high profile managers had on at the time. Dallas also had the smallest

sample size of any of the cities in our study which could also be a contributing factor to their performance

characteristics.

Greenwich: A middle of the pack performer during the period, returning +9.89% on an annualized basis, trailing

the median performer (New York) by 60 basis points annually. That said, Greenwich was the city that performed

the best during every period of market stress we studied. Greenwich also had amongst the lowest beta and

standard deviation of any of the cities, resulting in strong risk adjusted returns which can be seen in their Sharpe

Ratio of 1.32. This is only marginally lower than Dallas and Boston at 1.34 and 1.33, respectively. Greenwich

had lower correlation with broad market indices than most other cities trailing only Chicago and Dallas, while

correlation with the hedge fund indices was in the middle of the pack. Greenwich had high correlation with the

HFRI Global Macro Index which makes sense given some of the high profile global macro hedge funds based in

the city.

Los Angeles: Los Angeles was the second worst performing city during the period at +9.35% on an annualized

basis, outpacing San Francisco by just 2 basis points. They were also amongst the worst cities in protecting

capital during periods of market stress. Los Angeles had the lowest up market capture and the highest down

market capture ratio of all the cities in our study. Correlations to major market and hedge fund indices were

relatively high for Los Angeles. LA had the highest correlation to high yield bonds which we attribute to the

existence of several large credit focused firms within city limits. Los Angeles had the largest shift in standard

deviation of any city in our study. In our opinion, this change was due to credit managers shifting their portfolio

pricing practices from internal pricing to external pricing, likely driven by the demands of investors following the

2008 credit crisis.

New York: New York was the median performing city during the period at +10.49% annualized. New York did

not protect capital well on a relative basis as it was the worst performing city during two out of the three

periods of market stress we studied (2000 – 2002 and 2011) and had the highest correlation with market and

hedge fund indices. Correlation to the Russell 2500 Index was 0.88 which implies that funds in the city are

actively trading mid‐cap equities. Correlation was also very high (+0.87) to the Russell 2500 Growth Index which

may imply that New York based managers actively trade technology stocks. The poor relative drawdown in 2000

– 2002 also points to this as technology stocks performed poorly during that period. Furthermore, our

experience has shown that New York funds trade in technology names because they tend to offer outsized

return potential over shorter periods of time. New York was also consistently amongst the highest when it came

to up and down market capture ratios, beta and standard deviation which all imply hedge funds in the city are

managing their portfolios in an aggressive manner.

San Francisco: San Francisco was the worst performing city during the period at +9.33% annualized and was a

particularly poor performer during periods of market stress. San Francisco was the worst performing city in

2007 – 2009, the second worst performer in 2000 – 2002, and the third worst performer in 2011. San Francisco

had the second highest correlation to market indices of all the cities we studied. Similar to New York, they had

very high correlation with the Russell 2500 Growth Index (+0.85) which implies they are trading technology


stocks. This could be due to the presence of venture capital firms and technology companies in the region which

may be influencing manager behavior. They were also the city with the second highest correlation to the HFRI

Composite Index. San Francisco was also amongst the highest ranking cities in up and down market capture

ratios, beta and standard deviation. This is implying that hedge funds in the city are managing their portfolios

aggressively, with outsized exposure to technology as a whole.

Next Steps

We intend to increase the size and the scope of this study next year, updating and re‐evaluating the

performance history and characteristics of each region in 2012. In addition to potentially adding new cities, we

will look to report on the number of underlying strategies in each city and compile assets under management

and average fee structure.

About Balter Capital Management

Formed in 2006, Balter Capital Management, LLC is a registered investment advisor focusing purely on hedge

fund research and investing. We believe our dedicated focus on hedge fund investing provides us with the

highest level of insight and differentiation by applying our rigorous approach to sourcing, analyzing, monitoring

and interacting with hedge funds. We utilize both established funds as well as continuously sourcing “non‐brand

name” managers that have not yet been identified by the broader investment community.

Please contact Ben Deschaine via email at [email protected] with questions or comments.

Balter Capital Management, LLC


Glossary

Beta: Calculated using regression analysis, and measures the tendency of a security's returns to respond to

swings in the market. A beta of 1 indicates that the security's price will move with the market. A beta of less

than 1 means that the security will be less volatile than the market. A beta of greater than 1 indicates that the

security's price will be more volatile than the market. For example, if a stock's beta is 1.2, it's theoretically 20%

more volatile than the market.

Correlation: A statistical measure of how two securities move in relation to each other. Results range between

‐1 and +1. A correlation of +1 means that the two securities are perfectly positively correlated and move in

lockstep. A correlation of ‐1 means that the two securities are perfectly negatively correlated and move in

opposite direction of each other. A correlation of 0 means that two securities move independent of each other.

Rolling Statistics: We chose to evaluate certain performance and risk statistics on 48 month rolling periods. This

approach looks at statistics on a 48 month period and the rolls forward dropping the last month and adding the

next month. This allows us to evaluate risk and return over a longer period of time while smoothing out of some

noise in the data.

Standard Deviation: A statistical measure of the volatility (a measure of risk) of the historic returns of a security.

A volatile or risky security will have a high standard deviation compared to a conservative security that will have

a lower standard deviation.

Index Definitions

Barclays Capital U.S. Aggregate Bond Index: A broad‐based benchmark that measures the investment grade,

U.S. dollar‐denominated, fixed‐rate taxable bond market, including Treasuries, government‐related and

corporate securities, MBS (agency fixed‐rate and hybrid ARM pass‐through’s), ABS, and CMBS. The U.S.

Aggregate rolls up into other Barclays flagship indices, such as the multi‐currency Global aggregate Index and

the U.S. Universal Index, which includes high yield and emerging markets debt. The U.S. Aggregate Index was

created in 1986 with index history backfilled to January 1, 1976.

Barclays Capital U.S. High Yield Index: Measures the market of USD‐denominated, non‐investment grade,

fixed‐rate, taxable corporate bonds. Securities are classified as high yield if the middle rating of Moody’s, Fitch,

and S&P is Ba1/BB+/BB+ or below, excluding emerging market debt. The U.S. Corporate High‐Yield Index was

created in 1986 with history backfilled to July 1, 1983, and rolls up into the Barclays U.S. Universal and Global

High‐Yield Indices.

Barclays U.S. Treasury Index: The U.S. Treasury Index includes public obligations of the U.S. Treasury. Treasury

bills are excluded by the maturity constraint but are part of a separate Short Treasury Index. In addition, certain

special issues, such as state and local government series bonds (SLGs), as well as U.S. Treasury TIPS, are

excluded. STRIPS are excluded from the index because their inclusion would result in double‐counting.

Securities in the index roll up to the U.S. Aggregate, U.S. Universal, and Global Aggregate Indices. The U.S.

Treasury Index was launched on January 1, 1973.


MSCI EAFE Index: A free float‐adjusted market capitalization index that is designed to measure the equity

market performance of developed markets, excluding the US & Canada. The MSCI EAFE Index consists of the

following 22 developed market country indices: Australia, Austria, Belgium, Denmark, Finland, France, Germany,

Greece, Hong Kong, Ireland, Israel, Italy, Japan, the Netherlands, New Zealand, Norway, Portugal, Singapore,

Spain, Sweden, Switzerland, and the United Kingdom.

MSCI EM Index: A free float‐adjusted market capitalization index that is designed to measure equity market

performance of emerging markets. The MSCI Emerging Markets Index consists of the following 21 emerging

market country indices: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Korea,

Malaysia, Mexico, Morocco, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand, and Turkey.

MSCI World Index ex‐USA: A free float‐adjusted market capitalization weighted index that is designed to

measure the equity market performance of developed markets. The MSCI World Index consists of the following

24 developed market country indices: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany,

Greece, Hong Kong, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain,

Sweden, Switzerland, and the United Kingdom.

Russell 2000 Index: Measures the performance of the small‐cap segment of the U.S. equity universe. The

Russell 2000 is a subset of the Russell 3000® Index representing approximately 10% of the total market

capitalization of that index. It includes approximately 2000 of the smallest securities based on a combination of

their market cap and current index membership.

Russell 2500 Index: Measures the performance of the small to mid‐cap segment of the U.S. equity universe,

commonly referred to as "smid" cap. The Russell 2500 is a subset of the Russell 3000® Index. It includes

approximately 2500 of the smallest securities based on a combination of their market cap and current index

membership.

Russell 2500 Growth Index: Measures the performance of the small to mid‐cap growth segment of the U.S.

equity universe. It includes those Russell 2500 Index companies with higher price‐to‐book ratios and higher

forecasted growth values.

Russell 2500 Value Index: Measures the performance of the small to mid‐cap value segment of the U.S. equity

universe. It includes those Russell 2500 Index companies with lower price‐to‐book ratios and lower forecasted

growth values.

S&P 500 Index: Regarded as the single best gauge of the U.S. equities market, this index includes 500 leading

companies in leading industries of the U.S. economy. Although the S&P 500® focuses on the large cap segment

of the market, with approximately 75% coverage of U.S. equities, it is also an ideal proxy for the total market.

S&P 500 is part of a series of S&P U.S. indices that can be used as building blocks for portfolio construction. S&P

500 is maintained by the Index Committee, a team of S&P Dow Jones Indices economists and index analysts,

who meet on a regular basis. The goal of the Index Committee is to ensure that the S&P 500 remains a leading

indicator of U.S. equities, reflecting the risk and return characteristics of the broader large cap universe on an

on‐going basis.


S&P GSCI: Provides investors with a reliable and publicly available benchmark for investment performance in the

commodity markets. The index is designed to be tradable, readily accessible to market participants, and cost

efficient to implement. The S&P GSCI is the first major investable commodity index. It is one of the most widely

recognized benchmarks that is broad‐based and production weighted to represent the global commodity market

beta. The S&P GSCI is calculated primarily on a world production weighted basis and is comprised of the

principal physical commodities that are the subject of active, liquid futures markets.

Hedge Fund Index Definitions

HFRI Monthly Indices (HFRI): Equally weighted performance benchmarks, HFRI indices are broken down into 4

main strategies, each with multiple sub‐strategies. All single‐manager HFRI Index constituents are included in

the HFRI Fund Weighted Composite, which accounts for over 2200 funds listed on the internal HFR Database.

Due to mutual agreements with the hedge fund managers listed in the HFR Database, we are not at liberty to

disclose the particular funds behind any index to non‐database subscribers. Funds included in the HFRI Monthly

Indices must, report monthly returns, report net of all fees returns, report assets in $USD, and have at least $50

Million under management or have been actively trading for at least twelve (12) months

Equity Hedge: Funds who maintain positions both long and short in primarily equity and equity derivative

securities. A wide variety of investment processes can be employed to arrive at an investment decision,

including both quantitative and fundamental techniques; strategies can be broadly diversified or narrowly

focused on specific sectors and can range broadly in terms of levels of net exposure, leverage employed, holding

period, concentrations of market capitalizations and valuation ranges of typical portfolios. Equity Hedge

managers would typically maintain at least 50% exposure to, and may in some cases be entirely invested in,

equities ‐ both long and short.

Event Driven: Funds who maintain positions in companies currently or prospectively involved in corporate

transactions of a wide variety including but not limited to mergers, restructurings, financial distress, tender

offers, shareholder buybacks, debt exchanges, or security issuance. Security types can range from most senior

in the capital structure to most junior or subordinated, and frequently involve additional derivative securities.

Event Driven exposure includes a combination of sensitivities to equity markets, credit markets and

idiosyncratic, company specific developments. Investment theses are typically predicated on fundamental

characteristics, with the realization of the thesis predicated on a specific development exogenous to the existing

capital structure.

Macro: Funds who trade a broad range of strategies in which the investment process is predicated on

movements in underlying economic variables and the impact these have on equity, fixed income, hard currency

and commodity markets. Managers employ a variety of techniques, both discretionary and systematic analysis,

combinations of top down and bottom up theses, quantitative and fundamental approaches and long and short

term holding periods. Although some strategies employ RV techniques, Macro strategies are distinct from RV

strategies in that the primary investment thesis is predicated on predicted or future movements in the

underlying instruments, rather than realization of a valuation discrepancy between securities.

Barclay CTA Index: A leading industry benchmark of representative performance of commodity trading advisors.

There are currently 602 programs included in the calculation of the Barclay CTA Index for the year 2012, which is

unweighted and rebalanced at the beginning of each year. To qualify for inclusion in the CTA Index, an advisor


must have four years of prior performance history. Additional programs introduced by qualified advisors are not

added to the Index until after their second year. These restrictions, which offset the high turnover rates of

trading advisors as well as their artificially high short‐term performance records, ensure the accuracy and

reliability of the Barclay CTA Index.


Additional Charts and Tables

Boston Chicago Dallas Greenwich Los Angeles New York San Francisco S&P 500

MSCI World

ex‐U.S. HFRI Comp

Ann. Compound Return 11.90% 13.64% 11.53% 9.89% 9.35% 10.49% 9.33% 0.55% 0.98% 5.69%

Cumulative Return 285.24% 363.88% 270.45% 210.08% 192.19% 230.95% 191.59% 6.80% 12.38% 94.27%

Standard Deviation 6.77% 8.38% 6.48% 5.48% 7.02% 8.09% 7.80% 16.32% 18.39% 6.88%

Best Monthly Return 5.97% 11.56% 5.66% 4.98% 6.10% 7.78% 8.97% 10.93% 12.90% 6.16%

Worst Monthly Return ‐7.49% ‐4.94% ‐7.45% ‐4.92% ‐9.96% ‐7.37% ‐8.67% ‐16.80% ‐20.80% ‐6.84%

Max Drawdown ‐20.10% ‐13.73% ‐15.11% ‐12.41% ‐22.36% ‐20.11% ‐23.94% ‐50.95% ‐56.63% ‐21.42%

Sharpe Ratio Geom. (tbill) 1.33 1.26 1.34 1.32 0.96 0.96 0.86 ‐0.10 ‐0.07 0.48

Sortino Ratio (5.00%) 1.49 1.81 1.45 1.36 0.81 0.97 0.77 ‐0.34 ‐0.28 0.13

Gain Deviation 4.31% 6.21% 3.95% 3.61% 3.91% 5.01% 4.79% 9.38% 9.77% 3.93%

Loss Deviation 5.57% 4.40% 5.21% 3.66% 6.66% 5.76% 5.86% 11.61% 13.29% 4.83%

Downside Deviation (5.00%) 4.29% 4.40% 4.19% 3.35% 5.06% 5.29% 5.26% 12.60% 14.18% 5.08%

Skewness ‐0.79 0.48 ‐0.87 ‐0.38 ‐1.49 ‐0.49 ‐0.58 ‐0.43 ‐0.60 ‐0.57

Kurtosis 2.98 1.99 2.42 1.13 6.40 1.32 3.03 0.65 1.29 1.31

Number of Periods 144 144 144 144 144 144 144 144 144 144

Negative Periods (%) 26.39% 35.42% 25.00% 29.17% 29.17% 31.25% 32.64% 41.67% 44.44% 34.03%

Positive Periods (%) 73.61% 64.58% 75.00% 70.83% 70.83% 68.75% 67.36% 58.33% 55.56% 65.97%

Statistics (Jan 2000 ‐ Dec 2011)

Year Boston Chicago Dallas Greenwich Los Angeles New York San Francisco S&P 500

MSCI World

ex‐U.S.

HFRI

Composite

2011 ‐1.63% ‐1.08% ‐0.25% ‐1.28% ‐2.61% ‐2.48% ‐0.07% 2.11% ‐12.18% ‐5.25%

2010 11.87% 16.46% 14.72% 11.61% 13.65% 13.39% 16.09% 15.06% 8.94% 10.25%

2009 31.40% 23.99% 18.27% 24.37% 33.21% 29.07% 23.35% 26.45% 33.66% 19.98%

2008 ‐17.15% ‐4.88% ‐10.26% ‐10.27% ‐20.61% ‐17.57% ‐22.15% ‐37.00% ‐43.56% ‐19.03%

2007 9.03% 12.33% 28.65% 12.57% 9.12% 16.23% 16.63% 5.45% 12.44% 9.96%

2006 15.51% 13.21% 19.71% 12.92% 13.32% 15.90% 10.91% 15.81% 25.71% 12.89%

2005 12.59% 12.62% 11.93% 10.41% 7.28% 9.97% 10.48% 4.90% 14.47% 9.30%

2004 11.79% 11.06% 11.22% 9.69% 11.10% 13.38% 11.05% 10.88% 20.38% 9.03%

2003 22.33% 29.29% 22.87% 18.76% 23.88% 28.17% 22.60% 28.68% 39.42% 19.55%

2002 9.12% 19.32% 4.08% 3.64% 9.74% ‐1.53% 3.57% ‐22.10% ‐15.80% ‐1.45%

2001 21.66% 10.20% 11.49% 11.43% 10.37% 14.85% 10.94% ‐11.88% ‐21.40% 4.62%

2000 24.92% 26.27% 11.59% 19.44% 12.89% 15.54% 17.09% ‐9.11% ‐13.37% 4.98%

Calendar Year Performance

Year Boston Chicago Dallas Greenwich Los Angeles New York San Francisco S&P 500

MSCI World

ex‐U.S.

HFRI

Composite

1 Year ‐1.63% ‐1.08% ‐0.25% ‐1.28% ‐2.61% ‐2.48% ‐0.07% 2.11% ‐12.18% ‐5.25%

2 Year 4.90% 7.33% 6.97% 4.96% 5.20% 5.15% 7.71% 8.39% ‐2.19% 2.20%

3 Year 13.08% 12.62% 10.62% 11.07% 13.81% 12.59% 12.69% 14.10% 8.54% 7.82%

4 Year 4.62% 7.96% 4.98% 5.30% 4.01% 4.15% 2.73% ‐1.64% ‐7.83% 0.37%

5 Year 5.49% 8.82% 9.34% 6.72% 5.01% 6.46% 5.37% ‐0.26% ‐4.09% 2.22%

6 Year 7.10% 9.54% 11.00% 7.73% 6.36% 7.98% 6.28% 2.25% 0.33% 3.92%

7 Year 7.86% 9.98% 11.13% 8.11% 6.49% 8.26% 6.87% 2.63% 2.24% 4.68%

8 Year 8.35% 10.11% 11.14% 8.30% 7.05% 8.89% 7.38% 3.62% 4.35% 5.21%

9 Year 9.82% 12.09% 12.39% 9.42% 8.80% 10.88% 8.98% 6.15% 7.76% 6.71%

10 Year 9.75% 12.80% 11.53% 8.83% 8.90% 9.57% 8.42% 2.91% 5.14% 5.87%

11 Year 10.78% 12.56% 11.53% 9.06% 9.03% 10.04% 8.65% 1.47% 2.39% 5.75%

12 Year 11.90% 13.64% 11.53% 9.89% 9.35% 10.49% 9.33% 0.54% 0.98% 5.69%

Annualized Performnace (Jan 2000 ‐ Dec 2011)

Balter Capital Management Hedge Fund Regional Performance Study

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