Hedge Funds, Expensive Beta, Low-Cost Alpha
– Replication is Better
May 23, 2016
by Maneesh Shanbhag
Advisor Perspectives welcomes guest contributions. The views presented here do not necessarily
represent those of Advisor Perspectives.
Hedge fund returns, like most strategies, are a combination of market risk (beta) and manager specific
risk (alpha). Depending on an investor’s goals with a hedge fund investment, high risk-adjusted return
or diversification, replicating the hedge fund in order to avoid the detrimental effects of high fees is
better than a direct investment.
For investors seeking high risk-adjusted returns, or alpha, many top managers can be copied
sufficiently well. This is because one only needs to know their largest positions with some timeliness
(most managers provide more than enough of both with monthly and quarterly reporting). If one has
high confidence that a top performing hedge fund manager will repeat their outperformance in the
future, replicating the manager’s portfolio should outperform their net-of-fee return. We review a
formula that can be used to determine whether one can successfully replicate a manager.
Alternative beta exposure, for diversification, is the other common reason for investing in hedge funds.
Investors hope the beta from strategies such as trend-following and event-driven trading diversifies
their stock and bond allocations even if their returns may be in line with these traditional asset classes.
We show how to replicate many alternative betas using only a few publicly traded asset classes. This
begs the question of whether alternative betas should be diversifying to stocks and bonds in the first
place. We would argue not and, therefore, the only potential benefit of hedge fund investing in the first
place is high alpha potential, which is extremely difficult to achieve.
Mind your alphas and betas
Following the dot-com collapse in equity prices, hedge funds were pitched as the solution to market
volatility, sold as having the ability to generate high returns in any market environment and thus worthy
of their “2 & 20” fee structure. After failing to deliver on this promise of high returns, the industry has
pivoted, claiming hedge funds are a diversifier to traditional assets. This too has proven false. The
chart below shows how a passive portfolio of stocks and bonds tracked the broad index of hedge funds
with more than 80% correlation over the last decade. The hedge fund industry, with over $3 trillion
under management, has become the market.
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Hedge funds is the HFRI. Replication is 50% MSCI World, 20% Barclays US Treasury Index, 30% TBills. Source: Bloomberg. Data from Jan. 2005 to Dec. 2015.
Hedge fund returns, like all strategies, can be separated into their component drivers of return:
Total Return = Risk-Free Rate + Beta (buy and hold market risk) + Alpha (skill-based return)
From the chart above we can see that a broad index of hedge funds delivers no skill-based return –
both portfolios earned 2.9% annualized over cash since January 2006. When we dissect how much of
the hedge fund return is driven by beta risk versus alpha risk (tracking error), it is mostly beta, as
illustrated in the pie chart below. While the 21% alpha risk may seem low to some since hedge funds
are supposed to be all alpha, this number actually looks high to us.
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Tracking error is HFRI minus Greenline’s beta replication portfolio. Alpha is assumed to have 0
correlation to the beta replication in calculating the alpha risk share.
Alpha risk on its own does not equate to outperformance as we can see; rather, it is often only the
tracking error versus a selected passive benchmark. This serves as a reminder that beating markets is
very difficult and few will achieve it over the long run. Those who over-diversify while paying high fees
certainly are not likely to earn alpha and will, in turn, lag passive benchmarks by approximately their
total fee. But this does not mean hedge funds should be completely disregarded. We separately
discuss their beta and potential for alpha, and how we would go about replicating each piece more cost
effectively. First a review of the characteristics of betas and alphas.
There are two primary reasons to select an investment other than a passive index fund:
1. Higher risk-adjusted returns
2. Diversification potential
Market risk, beta, like buying a passive equity index fund, should offer moderate risk-adjusted returns
to compensate investors for taking risk, but no higher given the ease with which all investors can earn
this return. If everyone could easily earn high returns, then we would all be rich. Most betas are also
linked to similar risk factors, namely shifts in economic growth and inflation. With common risk factors,
there is limited ability for diversification among betas. This logic should apply to alternative betas, as we
will show.
A single investment with both desirable characteristics, high return and diversification, can only be
driven by skill, which we call true alpha. True alpha is determined by the skill, insight and disciplined
process of a manager. By definition, skill is rare because markets are a zero sum game (and negative
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sum after fees). True alpha can have much higher risk-adjusted returns than beta because of its rarity
and also more diversification potential if it is driven by unique manager skill. Below we analyze how to
separately replicate the alphas and betas embedded in hedge fund.
Hedge fund alpha replication: A formulaic approach
We have already explained why alpha is hard to earn and especially over long periods of time.
Therefore, the word “replication,” implying “easy” or “low cost,” should not be consistent with the
definition of “alpha.” Take this as fair warning as to the difficulty in outperforming by simply copying
others. This being said, we should be able to create a logical framework for what strategies and
managers we can copy and expect to increase the odds of earning higher risk-adjusted returns.
The expectation with replicating a manager is simple: if they are good and we can copy them
accurately, we should earn even higher returns than a direct investment with the manager by
avoiding their high fees. In order to replicate a manager, we need transparency into their positions
delivered in a timely manner. If we cannot get full transparency into a manager’s holdings in real
time, this does not mean we cannot closely replicate their performance. As long as one can
replicate a large enough portion of their holdings so as to overcome the fee hurdle, then replication
should be superior to investing directly with the manager.
Through a thought experiment, we develop a logical framework that managers should be able to
replicate successfully. We think there should be a trade-off between:
1. Fraction of portfolio that is transparent and fees paid as percentage of expected return
For a manager earning 10% per year and charging a 2% management fee plus 20% on
performance, their net of fees expected return is 6.4% (10% – 2% management fee – 20% x 8%
of the remaining return = 6.4%). In this case, the investor keeps 64% of the gross return, which
will vary with fee structure and expected return.
If we cannot replicate a manager’s entire portfolio, then how much is sufficient to at least match
their net of fee alpha? If we assume all positions equally contribute to return, then we should only
need to replicate enough of their portfolio to outperform their net of fee returns. If net of fees
return is 64% of their gross return as in our example above, then we should have to replicate at
least 64% of the portfolio. In practice, all positions are not equally weighted nor contribute equally
to portfolio return. Furthermore a manager’s highest conviction ideas get the largest weights and
are also expected to earn proportionally more than the smaller positions. Mathematically, using the
Herfindahl index, we can show that a 50 stock portfolio with half its weight in the largest 10 names
is similar in diversification to a portfolio of 25 equally weighted stocks. Therefore we should be able
to replicate less than 64% of the portfolio by at least a factor of 2 if most of our replication is of
their highest conviction positions in this 50-stock portfolio example.
Mathematically, we can say that, over time, replication should earn more than investing with the
manager if:
% of portfolio not replicated < % of return paid in fees
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Furthermore, we can divide the ‘% of portfolio not replicated’ by 2 for many managers given the
likely concentration in their top ideas.
2. Time lag of position reporting divided by average holding period and fees paid as a percentage of
expected return
Since we cannot get immediately transparency into positions when a manager places a trade, how
much lag in reporting positions still allows for successful replication? Said another way, with a
given time lag when position data is reported relative to when a manager puts on their position,
what is the maximum turnover a manager can have to allow for successful replication? To
understand this, we show a thought experiment illustrating the trading of the perfect manager to
arrive at an upper bound for turnover.
The chart below shows what happens to the returns of a portfolio before, during and after the
perfect manager holds it. The perfect manager initiates a position just as it begins making money
and exits at the top. To further simplify, let’s assume the portfolio makes its expected return at a
linear rate over its holding period. This way, we can estimate the lost return from entering the
same positions at a later time than the perfect manager.
In this stylized example, we can see how much return is lost by implementing the manager’s
portfolio with a time lag. Assuming, again, the standard 2 & 20 fee for a manager earning 10% per
year, as long as the time lag between the manager initiating a position and it being reported (and
copied) is less than 36% (% of return paid in fees in the example above) of the manager’s average
holding period, then replication should outperform the net of fee returns. Said another way, if this
manager had an average holding period of 12 months, as long as we can implement this portfolio
less than 131 days of the manager doing so, then replication should outperform. In practice, we
get transparency more frequently. With equity managers, they must report their positioning to the
SEC within 45 days of each quarter-end. Managers of other strategies often give sufficient
transparency into their top holdings in monthly reports and quarterly letters to also facilitate
replication.
Mathematically, with lag, we can say that replication should be successful when:
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Reporting lag / Holding Period < % of return paid in fees
Similarly as with the fraction of the portfolio we replicate, we can divide by a factor of 2 the
‘Reporting lag / Holding Period’ to remove some conservatism because markets do not behave
linearly nor do managers consistently catch the tops and bottoms of trades. We can now combine
the fraction of portfolio factor and reporting lag factor to estimate whether replication for a given
manager should be successful or not with the following formula:
[ % of portfolio not replicated + Reporting lag / Holding Period ] / 2 < % of return paid in fees
Next, we look at a few examples of actual managers we have replicated and how our formula applies in
each case. We do not disclose the individual manager names, but the studies are based on real
managers and their actual returns and holdings information.
Hedge fund alpha replication: Manager replication examples
We start with a large, well-known activist investor, whom we will call Manager 1 because this style of
investing generally translates into concentrated portfolios of a few positions with long holding periods.
From their 13F fillings, Manager 1 usually holds 10-20 positions with typically 80% of their capital in
their top 10 holdings. Furthermore, as activists they tend to have long holding periods of at least 3
years. Let us assume that all of their holdings are in U.S. companies, which are reported in SEC 13F
filings with a 45 day lag after the end of each quarter. For a portfolio like this, we should be able to
replicate 100% of their portfolio with a short lag relative to their average holding period. For our
example, we assume their fee is 2 & 20 with an expected return of 15%. Applying our formula:
% of portfolio not replicated = 0%
Reporting lag / Holding Period = 45 days / 3 years or 1095 days = 4.1%
% of return paid in fees = 2% management fee + [20% x (15%-2% mgmt fee)] = 2.6%
performance fee
= 4.6% / 15% = 30.7%
0%/2 + 4.1%/2 = 2.1% < 30.7% → YES, replication should outperform
Our formula suggests we should be able to handily outperform Manager 1’s net of fee returns through
replication. The chart below compares our replication results to their gross and net of fee returns over
the last 5 years. Our replication strategy is to exactly copy their 13F filings on the day they are released
(45 day lag). As expected for a manager with long holding periods, our replication strategy would have
roughly matched their gross returns and saved the investor over 5% in fees per annum.
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Activist funds are well suited for replication since they are primarily long-only and long term holders of
equities. Below we analyze another manager who has been successful over the past decade using a
different approach. Manager 2 is large long/short manager for whom their largest position until mid
2015 was Valeant Pharmaceuticals. Manager 2 also offers a long-only fund, which is what we attempt
to replicate. This manager has a growth and quality bias, some international exposure (we assume
20% on average) and nearly 100% annual turnover in their portfolio. For the sake of example, we
assume their fee structure is lower than for the average hedge fund, at 1% + 20% of returns above the
S&P 500. We assume their expected outperformance is 5% annually. Applying our formula for
Manager 2 gives:Source: Bloomberg, Greenline Partners analysis. Data from Nov 2010 to Aug 2015.
There is a potential for loss, as well as gain that is not reflected in the hypothetical information
portrayed. The hypothetical performance results shown do not represent the results of actual trading
using client assets but were achieved by means of the retroactive application of a model designed
with the benefit of hindsight. Investors should carefully review the additional information presented by
Greenline Partners as part of any hypothetical comparison.
% of portfolio not replicated = 20% (non US positions not reported to SEC)
Reporting lag / Holding Period = 45 days / 365 days = 12.3%
% of return paid in fees = 1% management fee + [20% x (5%-1%)] = 0.8% performance fee
= 1.8% / 10% = 18%
20%/2 + 12.3%/2 = 16.2% < 18% → YES, but barely. Replication may produce similar results to
manager net of fees
Our formula suggests that our replication should roughly match Manager 2’s net of fee results. This is
in part driven by their lower effective fee than for the average hedge fund. Keep in mind that our
formula is meant to serve as a conservative estimate while in reality many managers that do not meet
our criteria should still be replicable. As we can see in the chart below, our replication of Manager 2
matches their net of fee returns in spite of them having high turnover and a significant book of
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international positions.
Finally, we will review one more manager to show replicating a partial portfolio. Below we review a
$20ln long/short global manager, Manager 3. Manager 3 has a growth bias with high turnover (near
100%) and some international exposure. Historically, based on their 13F fillings, Manager 3 has held
around 50% of their capital in the top 10 holdings. Hence we compare replicating only the top 10
versus their full portfolio. Let us again assume a 2 & 20 fee structure and 15% expected return.
Applying our formula to Manager 3 for a full replication versus only for their Top 10 positions:Source:
Bloomberg, Greenline Partners analysis. Data from Nov 2010 to Mar 2015. There is a potential for
loss, as well as gain that is not reflected in the hypothetical information portrayed. The hypothetical
performance results shown do not represent the results of actual trading using client assets but were
achieved by means of the retroactive application of a model designed with the benefit of hindsight.
Investors should carefully review the additional information presented by Greenline Partners as part
of any hypothetical comparison.
Top 10 only replication:
% of portfolio not replicated = 50% (50% held outside of top 10 positions, remaining assumed to
be U.S. only for simplicity)
Reporting lag / Holding Period = 45 days / 365 days = 12.3%
% of return paid in fees = 4.6% / 15% = 30.7%
50%/2 + 12.3%/2 = 31.2% < 30.7% → NO, but close. Replication may produce results close to
manager net of fees
Full portfolio replication:
% of portfolio not replicated = 20% (only international positions excluded)
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Reporting lag / Holding Period = 45 days / 365 days = 12.3%
% of return paid in fees = 4.6% / 15% = 30.7%
20%/2 + 12.3%/2 = 16.2% < 30.7% → YES, replication should outperform
The chart below shows that Manager 3 can be successfully replicated using either the top 10 positions
or the full portfolio, both of which historically outperformed their net of fee returns. The table below of
Manager 3’s net returns shows that either replication would have consistently outperformed.
Source: Bloomberg, Greenline Partners analysis. Data from Jan 2009 to Dec 2015. There is a potential
for loss, as well as gain that is not reflected in the hypothetical information portrayed. The hypothetical
performance results shown do not represent the results of actual trading using client assets but were
achieved by means of the retroactive application of a model designed with the benefit of hindsight.
Investors should carefully review the additional information presented by Greenline Partners as part of
any hypothetical comparison.
In this example, we can see how the high conviction positions drive effectively all of the returns for
Manager 3. We expect this to be similar for many good managers. While our formula is not meant to
be precise, it can be used to inform replication strategy. For example, with Manager 3, our replication
formula suggests that it should be more reliable to go with full portfolio replication on a forward looking
basis as it provides a greater margin of safety.
Our formula is purposely conservative but allows one to make educated assumptions around how
transparency and portfolio turnover factor into which hedge funds we should be able to replicate
successfully.
For this analysis we have only looked at equity managers because of the ease of obtaining their
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holdings information through public fillings. One can also replicate managers of other asset classes
including fixed income, futures and OTC derivatives, given periodic transparency into their holdings. A
token direct investment with the purpose of receiving position reporting would be sufficient to then
replicate and outperform the manager net of fees.
Beyond just return, the other benefits of replication over direct investment are:
1.
2.
3.
4.
Daily liquidity (no lock ups, gates, etc.)
Control
Full transparency
Tax efficiency if relevant (e.g., incorporate tax loss harvesting)
There are pitfalls to replication as well that one should be aware of before embarking in this direction,
which we discuss next.
Shortcomings with hedge fund alpha replication
The benefits of replicating hedge funds versus investing in them directly are the higher returns that
result from significantly lowering fees. Beyond the performance of their portfolio, we think there are
potential benefits from investing directly with a talented manager:
1. Understanding why you own what you own
2. Learning from the manager’s research, which could benefit your broader portfolio
First, we have all heard the investing advice to “know what you own.” We think hedge fund replication
is no exception to this rule. With any good manager, there will inevitably be periods of
underperformance between periods of outperformance. Our discipline to stick with a manager will be
tested during the period of underperformance, and one needs to deeply understand their investment
process, its risks and signs that it is broken in order to make a quality decision about when to stop
replicating. This decision may be made more confidently with direct access to the manager.
Second, having access to a manager should be educational and drive learnings in your thinking that
can benefit your broader portfolio. If not, the manager is likely not one of the best in their field. The
hope is these learnings are applicable to your broader portfolio, which could yield a benefit worth far
more than the fees paid on a token direct investment. Note that to capture these portfolio level benefits,
one needs to be highly engaged with this top manager, which likely means only having a few such
deep relationships.
Note that both of these potential shortcomings with replicating a manager versus investing directly can
be overcome by making a minimum investment or buying a curated list from a consultant to gain
access to the transparency, research and thought process and then replicating their strategy at the
appropriate size.
Hedge fund beta replication
Switching gears to the beta side of hedge fund replication. Beta is simply the market return anyone can
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earn through a simple and easily replicable strategy. Anyone can buy an S&P 500 index fund to
achieve equity market returns without any skill. And those who follow this approach in a disciplined
manner through up and down markets tend to outperform most other investors. Simple and easily
replicable rules also apply to other strategies such as value investing (e.g. buy low P/E stocks) and
alternatives such as merger arbitrage (e.g., naively buy the acquiree and short the acquirer).
As we have discussed in previous papers (most recently “Bond-like Stocks, and Stock-like Bonds,”
Dec. 2015), we believe most asset class betas can be replicated using a combination of the primary
asset classes: equities, interest rates and commodities. This is because each of these asset classes
respond uniquely to shifts in growth and inflation, the primary risk factors and together can replicate
any exposure to these risk factors. If we can fundamentally understand the biases embedded in a
strategy, then we should be able to find a replicating mix of primary asset classes to closely match it.
Hedge fund beta is no exception.
We start with a simple example, long/short equity managers. We can infer from the long/short equity
return stream that in aggregate these managers are net long ~50% (e.g., long 100%, short 50% of
their capital). Therefore, our simple replication strategy is long 30% S&P 500 + 20% Russell 2000
Value Index to give us the target equity exposure with a value tilt since hedge funds tend to
systematically favor value over growth investing. As you can see in the chart below, the replication
tracks the Hedge Fund Research index of long/short managers with over 90% correlation.
Source: HFRI, Bloomberg, Greenline Partners analysis
As a second strategy, distressed debt is seen as a potentially diversifying exposure in addition to
offering the potential for high returns due to its illiquid and idiosyncratic nature. First, we do not believe
illiquidity on its own means an asset should be diversifying. Private equity is not diversifying to equities
as it is just owning illiquid businesses. Distressed debt can be thought of as lower quality than junk
bonds or having an even more equity like nature than junk. Therefore, we replicate the asset as part
equity risk and part high yield bonds. This simple two asset class replication is 81% correlated to the
universe of distressed debt hedge funds. Furthermore, this shows that distressed debt is mostly just
equity risk and hence should not be diversifying to public equities.
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Source: HFRI, Bloomberg, Greenline Partners analysis
We look at one more class of hedge fund strategies, event driven investing. Event driven strategies
attempt to take advantage of pricing inefficiencies after corporate events such as mergers, spinoffs and
bankruptcies. For example, one could replicate merger arbitrage funds by going long the stock of all
acquirees and shorting the stock of acquirers. Another proxy for such corporate events is the
performance of convertible debt. This type of debt should deliver equity upside if certain conditions for
convertibility materialize (exit from bankruptcy, improving balance sheet, etc.) otherwise a payout with a
debt-like profile. The downside risk on convertibles is much more equity like than the name would
suggest since not meeting the specified financial conditions can trigger a negative credit event,
including bankruptcy. We replicate event driven hedge funds with a delevered exposure to the Barclays
US Convertible Bond index. The resulting replication has an almost 90% correlation with event driven
hedge funds.
Source: HFRI, Bloomberg, Greenline Partners analysis
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If we look across the replication charts above, we can see two things: First, they all zig and zag
together, implying a similar equity-like risk embedded in all of these strategies. And second, our
passive replications have performed better over the last decade in spite of the selection bias in hedge
fund indices, as hedge fund assets have grown and the relevant asset classes have become more
efficient. In spite of the fancy strategy names, there is no fundamental diversification across these
strategies and no easy alpha available. Above are just a few examples of how we would replicate hedge
fund beta. We have also included more examples of hedge fund strategy replications in the Appendix of
this paper.
Given the ease with which we can replicate hedge fund beta using liquid, public market asset classes,
it should come as no surprise that there are already ETFs that attempt to replicate hedge fund beta.
One example is Index IQ’s Hedge Multi-Strategy tracker (ticker: QAI). This fund had 116 holdings
across at least a dozen asset classes and styles as of January 31, 2016 and uses a statistically driven
process to match the beta exposures in the HFR Fund Weighted Composite Index. The result of their
unnecessarily complex replication methodology is shown in the chart below. The results do not track
the HFRI as well as our simple global stocks and Treasuries replication.
Simple replication is 50% MSCI World ETF (ticker: URTH), 20% US Treasury ETF (ticker: GOVT),
30% 3 Month US T-Bills backfilled with index data prior to ETF inception in Feb 2012. Source:
Bloomberg, Greenline Partners analysis. Data from Mar 2009 to Dec 2015.
Aside from reinforcing the K.I.S.S. (keep it simple, stupid) rule, the take away is that most hedge fund
beta can be simply replicated using 1-2 public market asset classes and, therefore, should not be
diversifying to the traditional asset classes that we use to replicate them. We will let you draw your own
conclusions as to the usefulness of hedge fund beta in a portfolio.
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Conclusion
Prior to the 1970s, active stock and bond management was the only way to buy a diversified portfolio
of securities. Net of fees, the average manager underperformed the S&P 500 and most of their returns
were driven by the market, not their skill. The invention of the index fund in 1972 gave investors a low
cost way to earn the market return.
Hedge funds have reached a similar point in their lifecycle where it has become well known that the
industry as a whole does not outperform market averages. Hedge fund replication is the same
innovation as index funds were over 40 years ago. Like with index funds, a thoughtful replication of a
manager should outperform net of their fees.
In general, we do not recommend investing in hedge fund strategies. Paying the high fees involved
ignores the extremely competitive nature of capital markets and how this puts the odds of earning
adequate returns against you. Replicating a manager or strategy, as a starting point to avoid high fees,
is a way to put the odds back in your favor.
Maneesh Shanbhag is co-founder of Greenline Partners and is responsible for the investment
process. Greenline Partners is an asset management and advisory firm focused on constructing
unlevered, cost and tax-efficient portfolios across multiple asset classes. We work with a range of
investors including foundations, endowments, family offices and wealth advisors as both an
investment manager and advisor. The firm was founded by alumni of Bridgewater Associates, who
served on the firm’s investment team and acted as lead advisors on asset allocation, liability
management, risk budgeting and manager selection for leading institutional investors including
pension funds, endowments, foundations and family offices.
Greenline Partners is headquartered in New York, NY with offices in Seattle, WA. For more
information, please visit http://www.glinepartners.com or email info@glinepartners.com.
Appendix: Hedge fund beta replication strategies
We analyzed various hedge fund strategies based on the data published by Hedge Fund Research, Inc
(HFRI). The results of replicating each strategy with simple combinations of one or two cheaply
available market risk premia is shown below. Note that most hedge fund indices have a selection bias
that boosts their reported return and has been documented in academic papers but is outside the
scope of this paper. In spite of this, our replications using public market indices outperform most hedge
fund indices over the past decade. All data is from January 2000 to December 2015, obtained from
Bloomberg.
1. HFRI Fund Weighted Composite
Replicated using 50% delevered S&P 500 with 87% correlation.
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2. HFRI Equity Market Neutral funds: Replicated using a mix of 20% long Russell 2000 Value and
short 5% S&P 500 with 67% correlation.
3. HFRI Equity Fundamental Value funds: Replicated using 50% delevered Russell 2000 Value
with 95% correlation.
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4. HFRI Equity Sector Energy/Materials Funds: Replicated using a mix of 60% Energy sector/20%
Materials sector/20% cash allocation with 80% correlation.
5. HFRI Equity Sector Technology/Healthcare funds: Replicated using 50% Technology sector with
95% correlation.
6. HFRI Equity Short Bias funds: Replicated with a 100% short S&P 500 position with 85%
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correlation.
7. HFRI Global Macro funds: Replicated using a mix of 25% Commodity futures + 25% Currency
carry (long high yield currencies/short low yielding currencies) with 46% correlation.
8. HFRI Macro Commodities funds: Replicated using a mix of 35% Commodity futures overlayed
with a 6-month moving average trend following strategy with 73% correlation.
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9. HFRI Macro Currency funds: Replicated using a 50% de-risked exposure to the US Dollar trend
following index based on a 6-month moving average, with 41% correlation.
10. HFRI Fixed Income Relative Value funds: Replicated using a mix of 65% High Yield debt/35%
cash with 90% correlation.
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11. HFRI Emerging Market funds: Replicated using 50% delevered MSCI Emerging Market
equities index with 96% correlation.
DISCLOSURES:
The information contained herein is the property of Greenline Partners, LLC and is circulated for
information and educational purposes only. There is no consideration given for the specific investment
needs, objectives or tolerances of any of the recipients. Additionally, Greenline's actual investment
positions may, and often will, vary from its conclusions discussed herein based upon any number of
factors, such as client investment restrictions, portfolio rebalancing and transaction costs, among
others. Reasonable people may disagree about a variety of factors discussed in this document,
including, but not limited to, key macroeconomic factors, the types of investments expected to perform
well during periods in which certain key economic factors are dominant, risk factors and various
assumptions used. Recipients should consult their own advisors, including tax advisors, before making
any investment decision. This report is not an offer to sell or the solicitation of an offer to buy the
securities or instruments mentioned.
HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS:
Hypothetical or simulated results are subject to inherent limitations and do not represent actual trading
or the costs associated with managing a portfolio. The hypothetical or simulated results shown have
been achieved through the retroactive application of a back-tested model designed with the benefit of
hindsight.
Unless otherwise indicated, results shown are gross of fees, include the reinvestment of interest, gains
and losses, and do not take into account the reduction of any management fees, costs, commissions,
or other expenses that may be associated with the implementation of a portfolio. The individuals
involved in the preparation of this document receive compensation based on a variety of factors,
including individual and firm performance. Additional information about Greenline Partners, LLC,
including fees charged, is located in Greenline’s Form ADV, which is accessible at
http://www.adviserinfo.sec.gov. Greenline’s CRD Number is 164192.
Page 19, ©2019 Advisor Perspectives, Inc. All rights reserved.
Past performance is not a guarantee of future results.
Forward-Looking Statements and Opinion:
Certain statements contained in this presentation may be forward-looking statements that, by their
nature, involve a number of risks, uncertainties and assumptions that could cause actual results or
events to differ materially, potentially in an adverse manner, from those expressed or implied herein.
Forward-looking statements contained in this presentation that reference past trends or activities
should not be taken as a representation that such trends or activities will necessarily continue in the
future. Greenline Partners undertakes no obligation to update or revise any forward—looking
statements, whether as a result of new information, future events or otherwise. Opinions offered
herein constitute the judgment of Greenline Partners, as of the date of this presentation, and are
subject to change. You should not place undue reliance on forward-looking statements or opinions, as
each is based on assumptions, all of which are difficult to predict and many of which are beyond the
control of Greenline Partners. Greenline Partners believes that the information provided herein is
reliable; however, it does not warrant its accuracy or completeness.
Information presented herein (including market data and statistical information) has been obtained
from various sources which Greenline Partners, LLC considers to be reliable including but not limited
to the Federal Reserve, International Monetary Fund, National Bureau of Economic Research,
Organization for Economic Co-operation and Development, United Nations, US Department of
Commerce, World Bureau of Metal Statistics as well as information companies such as BBA Libor
Limited, Bloomberg Finance, L.P., Global Financial Data, Inc., Hedge Fund Research Inc., Markit
Economics Limited, Moody's Analytics, Inc., MSCI, Standard and Poor's, and Thomson Reuters.
However, Greenline Partners, LLC makes no representation as to, and accepts no responsibility or
liability whatsoever for, the accuracy or completeness of such information. Greenline Partners, LLC
has no obligation to provide recipients hereof with updates or changes to such data. All projections,
valuations and statistical analyses are provided to assist the recipient in the evaluation of the matters
described herein. They may be based on subjective assessments and assumptions and may use one
among alternative methodologies that produce different results and, to the extent that they are based
on historical information, they should not be relied upon as an accurate prediction of future
performance.
This material is not intended to represent a comprehensive overview of any law, rule or regulation and
does not constitute investment, legal, or tax advice. You should exercise discretion before relying on
the statements and information contained herein because such statements and information do not take
into consideration the particular circumstances or needs of any specific client. Accordingly, Greenline
Partners, LLC makes no representation or warranty as to the accuracy of the information contained
herein and shall have no liability, howsoever arising to the maximum extent permitted by law, for any
loss or damage, direct or indirect, arising from the use of this information by you or any third party
relying on this presentation.
The information contained in this document is current as of the date shown. Greenline Partners has no
obligation to provide the recipient of this document with updated information or analysis contained
herein. Additional information regarding the analysis shown is available upon request, except where the
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proprietary nature precludes such dissemination.
This material is furnished on a confidential basis only for the use of the intended recipient and only for
discussion purposes, may be amended and/or supplemented without notice, and may not be relied
upon for the purposes of entering into any transaction. No part of this document or its subject matter
may be reproduced, disseminated, or disclosed without the prior written approval of Greenline
Partners, LLC.
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