Master Thesis - Hugo Cassat

Edhec - M.Sc. in Risk and Asset Management

FINDING AN ALTERNATIVE

TO ALTERNATIVES

Master Thesis – Hugo Cassat

December 2009

Hugo CASSAT – Master Thesis - Finding an alternatives to alternatives Page 2

Hugo Cassat

M.Sc in Risk & Asset Management 2008-2009

Main Category: Hedge Fund Industry and Asset Management


OVERVIEW

I. RECENT ISSUES WITH HEDGE FUNDS INDUSTRY ..................................................... 9

2.1 What did we like about hedge funds? ............................................................................... 10

2.2 Opacity, operational risk .................................................................................................... 14

2.3 Liquidity ............................................................................................................................. 15

2.4 Fees structure .................................................................................................................... 16

II. POSSIBLE SOLUTIONS .................................................................................... 17

3.1 Active replication: managed account platforms ................................................................ 17

3.2 Passive replication ............................................................................................................. 19

3.2.1 Payoff replication approach (Kat) ..................................................................................... 19

3.2.2 Factor-based approach: linear multi-factor (basique) versus non-linear and/or

conditional multi-factor model (Fung-Hsieh, Lo, Martellini, Garcia, etc.) ........................ 22

III. A NEW PERSPECTIVE ..................................................................................... 23

IV. NUMERICAL SIMULATIONS ............................................................................. 25

V. CONCLUSION .............................................................................................. 33


INDEX: GRAPHS

GRAPH 1 : GLOBAL HF’S AUM IN MILLION $ (SOURCE : BARCLAY HEDGE, 2009) ................................................. 9

GRAPH 2 : NATURE OF HF’S INVESTORS (SOURCE : HENNESSEE GROUP, 2006) .................................................... 10

GRAPH 3 : EXAMPLE OF CORRELATION: CS / TREMONT HEDGE FUND INDEX CORRELATION ................................ 12

GRAPH 4 : DIFFERENT HF’S STRATÉGIES (SOURCE : HEDGE FUND RESEARCH, 2009) ........................................... 13

GRAPH 5 : GLOBAL HF’S AUM $MILLION (SOURCE : BARCLAY HEDGE, 2009).................................................... 14

GRAPH 6 : BARCLAYS AGGREGATE BOND (AGG) ................................................................................................. 26

GRAPH 7 : COMPARED EVOLUTION OF ETF, MANAGED ACCOUNT, AND RISK FREE ............................................... 27

GRAPH 8 : DCS WITH A FIXED FLOOR F AND MULTIPLIER M .................................................................................. 27

GRAPH 9 : VARIOUS MULTIPLIER M ........................................................................................................................ 28

GRAPH 10 : ADAPTION OF THE CPPI STRUCTURE WITH A CAPITAL GUARANTEED FLOOR ....................................... 28

GRAPH 11 : ADAPTION OF THE CPPI STRUCTURE WITH ETF AS THE CORE ............................................................. 29

GRAPH 12 : FLOOR EXPRESSED AS A PERCENTAGE OF THE MAXIMUM VALUE ........................................................ 30

GRAPH 13 : SUMMARY OF THE DIFFERENT PORFOLIO STRATEGIES ......................................................................... 31


INDEX: TABLETS

TABLE 1: PAYOFF REPLICATION APPROACH, RESULTS OF TESTING. SOURCE: EDHEC RESEARCH CENTER ............ 21

TABLE 2 : FINANCIAL RATIO OF THE DIFFERENT STRATÉGIES COMPARED TO THE CORE AND THE SATELLITE ......... 32


Finding an alternative to alternatives

Before the current crisis, Hedge Funds have become popular amongst institutional and private

investors because they allowed them to reach the set of payoffs they didn’t have access to.

Hedges Funds show particularly appealing properties in terms of diversification with respect

to existing asset classes through exposure to alternative risk factors. Hedge Funds investments

suffer however from two main problems: lack of liquidity and lack of transparency. The

recent crisis has heightened investors’ concerns over these two dimensions, and the future

sustainability of the Hedge Funds industry is currently seriously challenged. In this context,

the question arises regarding the emergence of new alternative forms of investment strategies

that could provide investors with Hedge Funds-like payoffs while relaxing the liquidity and

transparency constraints.

The situation we are facing is thus the following: Investors needed these alternative classes of

assets in their wealth management process and were satisfied with what Hedge Funds used to

provide in terms of Payoff and Return Distribution. But the present crisis underlined the limits

of Hedge Funds and motivates the all industry to go further and find a way to overcome

liquidity and transparency matters.

Thus, the answer is not to run away from these alternatives investments and stick to

traditional assets because the allocation process will be too deeply hit by such a behavior.

Rather, the answer is to improve what we consider as the actual Alternative Classes and find

the new paradigm of alternative management. In other words, we want to look for an

Alternative to Alternatives.

What I want to expose in this document is not the ultimate answer to this all industry shift. I

will try to explain and test one of the approaches which exist and which, in my opinion, is the

best present candidate. The main issue I will be facing is that it is a very current focus and


right now, papers are being written about it and new products are launched following these

new developments. Thus, my document might lack from the very last research.

Recent advances in asset pricing theory regarding the strong correspondence between option

pricing and dynamic portfolio allocation problems suggest that it is in fact possible to design

novel forms of investment strategies that are designed to meet investors’ needs and

constraints, while meeting the requirements of transparency and liquidity.

From the investor point of view, the main approaches that can be used in this perspective

willonly differ in terms of how requirements are defined:

1. Active replication will be the first level attempt. By directly transferring the

management but copying strategies, these products aim at over passing hedge funds

deal breaking issue while keeping the spirit of it.

2. With passive replication, investors will specify their expectations in terms of

moments of return distribution as well as co-moments with respect to their existing

portfolio. Example of investor’s requirement: a strategy that will deliver the

maximum performance with a 10% volatility and a 0% correlation with stocks.

3. To finish with, Generalized DCS strategies willask investors to specify their

expectations in terms of risk budgets with respect to floors and goals. In both last

cases, option-pricing methodology is used to generate a suitably designed dynamic

portfolio strategy that will deliver the targeted properties.


The document is based on the following structure:

Introduction: Recent issues with Hedge Funds industry

I will try to analyze the recent criticisms made about hedge funds and how far are they

relevant from the investor point of view. We will see firstly how Hedge Funds performed

through the crisis with regards to their goals and in which measures the investor community is

progressively withdrawing from this alternative investment, waiting for new solution.

Possible Solution

The recent crisis created a consensus for new theory regarding how investor should approach

hedge fund structures. Different attempts where made toward replication. I will try to give a

brief understanding of active and passive replication models and underline the limits of these

developments.

A new perspective

It seems to me that Dynamic Core-Portfolio implementation would be at the moment the new

paradigm in asset management. I’ll try to explain this approach regarding the needs of former

Hedge Investors

Numerical simulations

I will run numerical simulation in order to back test DCS methods by my own. These

simulations already exist but I will try to benefits from the learning of the implementation in

order to give a better understanding of the theory.

Conclusion

I’ll try to say something that sounds smart

Hugo CASSAT – Master Thesis -

I. RECENT ISSUES

In this part, my aim is to explain how Hedge Funds have been very attractive in growth period

but deceived most investors through the crisis. The key point is that Hedge funds are usual

design and marketed to be crisis shield and bring diversification of performances when the

market turns down but other factors than performances makes them unattractive during these

same time frame.

In the following chart we can see the asset under Hedge Funds management growing

massively between 2002 and 2008. We have to understand that this asset growth is both

driven by good performances and by new inflows.

Graph 1 : Glob

These inflows are mostly provided by Institutional Investors, Funds of Hedge Funds, Family

offices and few particular direct investors. The type of investors is a relevant data to

understand what are the needs and the expectation in investing in Hedge Funds.

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- Finding an alternatives to alternatives

WITH HEDGE FUNDSINDUSTRY


but deceived most investors through the crisis. The key point is that Hedge funds are usual





driven by good performances and by new inflows.

Global HF’s AUM in million $ (Source : Barclay Hedge, 2009)



the needs and the expectation in investing in Hedge Funds.

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but deceived most investors through the crisis. The key point is that Hedge funds are usually







the needs and the expectation in investing in Hedge Funds.


Graph 2 : Nature of HF’sinvestors

We are now able to notice the sharp increase of Hedge funds asset under management leaded

by wealthy individuals on the 2002

In order to achieve this industry growth, some useful characteristic of Hedge Funds

that time to investor needs…but we will see later on that 2008

constraints that hedges funds investments come with and which triggered

and the need for a new industry paradigm.

2.1 What did we like about hedge funds?

The first advantage of Hedge funds investment is a higher return. Or at least, this is the first

aspect marketed to investors. These higher expected

what is called the industry Alpha. There is more and more controversy

either we should split it in “Alternative Beta” and “Alternative Alpha”

develop this subject for now.

Nevertheless, these higher returns are supposed to be generated out of

by the manager: to invest in more complex derivative financial products, lower law constraint

in offshore registration, strong expertise in very particular market environment or niches,

11%

20%


Nature of HF’sinvestors(Source : Hennessee Group, 2006)


by wealthy individuals on the 2002-2007 time frames.

In order to achieve this industry growth, some useful characteristic of Hedge Funds

or needs…but we will see later on that 2008-2009 revealed the negatives

that hedges funds investments come with and which triggered off

and the need for a new industry paradigm.

we like about hedge funds?


aspect marketed to investors. These higher expected risk adjusted returns are embedded in

what is called the industry Alpha. There is more and more controversy about this term and

either we should split it in “Alternative Beta” and “Alternative Alpha” or not

Nevertheless, these higher returns are supposed to be generated out of special abilitiesclaimed

to invest in more complex derivative financial products, lower law constraint


7%9%

53%

Endowment Funds

Pensions/Retirement Plans

Corporations

Fund of Funds

Wealthy Individuals

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In order to achieve this industry growth, some useful characteristic of Hedge Funds suited at

2009 revealed the negatives

off huge outflows


returns are embedded in

about this term and

or not, but we won’t

special abilitiesclaimed

to invest in more complex derivative financial products, lower law constraint



better managers than everywhere else,

data or technological advantages.

These higher risk-adjusted return

on this same time frame the growth of a hundred dollar investment in Bonds, Equity and

Hedge fund index.

Secondly, it is well recognized that hedge funds are successful at bringing diversification and

un-correlation for investors. It can be

strategy constructed to be beta neutral,

downturn, or because managers are trading markets that are themselves totally

equity or bonds or, as some argue, because Hedge funds managers are the bests and they

never loose.


better managers than everywhere else, privileged relationship with broker, better acce

vantages.

returns are nevertheless not so obvious to notice. We can observe


well recognized that hedge funds are successful at bringing diversification and

s. It can be explained among other numerous reasons

onstructed to be beta neutral, because they are strongly hedged against

downturn, or because managers are trading markets that are themselves totally


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privileged relationship with broker, better access to

are nevertheless not so obvious to notice. We can observe


well recognized that hedge funds are successful at bringing diversification and

among other numerous reasons by a specific

because they are strongly hedged against market

downturn, or because managers are trading markets that are themselves totally uncorrelated to



Graph 3 : Example of Correlation :CS/TremontHedgeFund Index Correlation (Mar 1994 – Jan 2007)

During the past years, we tend to observe a moderate correlation with equity markets.

Each hedge fund is supposed to be unique and have its own story to tell. Actually hedge funds

are often marketed as based on a very strong conviction and original ideas of a manager. Even

these managers’ impressive backgrounds and careers also tell a story and belong to the criteria

investors look when investing in hedge funds. Different Hedge Funds types are so numerous

that none of the strategy mappings existing will never perfectly correspond to the entire

diversity spectrum. What investors appreciate is that they can choose the guy they believe in

with the story they believe in. This behavioral aspect is even truer since wealthy individuals

compose 53% of the investor base. Moreover, an infinite spectrum of strategy and trading

style is also a way for investors to clearly express and pick how they would like to play on the

market without doing it themselves.

The following list shows a strategy classification, which is often used by fund of hedge funds

and gives an idea of how diversified they can be. But other classification with more than 80

strategies (Albourne’s classification for instance) exists.

0,58

0,47

0,44

0,24

0,2

0,13

0,13

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7

Russell 2000

S&P 500

MSCI EAFE

NAREIT

DJ/AIG Commodity Index

Gold Price Index

Lehman Aggregate

CS/Tremont Hedge Fund Index Correlation (Mar 1994-Jan 2007)


Graph 4 :DifferentHF’s stratégies(Source : HedgeFundResearch, 2009)

To finish with, the interest that most investors have in Hedge Funds is the distribution of their

returns. It really makes sense in their investment strategies and they need it in their portfolio

construction methods. But we have to distinguishes why it makes sense in their portfolio and

what are they really looking for. It is not unusual to see investor miss-leaded about their

motivation in putting money into hedge funds. We’ll see latter on that we have to understand

separately what investors are looking for and what Hedge funds are good at.

But the two past years have been drastic for Hedge Funds and totally reversed the trends. The

critical characteristics of Hedge Fund businesses were revealed and the crisis amplified these

bad sides along with the Madoff(among others) story helping to build the bad reputation of

Hedge Funds. Outflows were huge and performances shredded down.


Graph 5 : Global HF’s AUM $Million

2.2 Opacity, operational risk

� Investors were not lured about the fact that Hedge Funds

Managers have usually very few

much higher than their incentive to loss.

� Of course, risk management systems are set up in order to prevent high

but when they want or they need to, it’s not unusual to see manager overcoming ri

management process.

� The only way to have a close follow up of a Hedge Fund is to have massive due

diligence process before investing and then to regularly check if risk management is

respected through time.

� The opacity about what is traded and what stra

also a characteristic that investors are less and less incline

few investors can have access to managers’ book and they only have to rely on what is

explained into monthly letters

� The best example of how opacity is now denounced by investor is the Madoff case.

The book didn’t even exist and no investments were made, falsified performances

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Global HF’s AUM $Million (Source: Barclay Hedge, 2009)

Opacity, operational risk

Investors were not lured about the fact that Hedge Funds manage dangerous position

Managers have usually very few constraints and their incentive to performances is

much higher than their incentive to loss.

Of course, risk management systems are set up in order to prevent high

but when they want or they need to, it’s not unusual to see manager overcoming ri

The only way to have a close follow up of a Hedge Fund is to have massive due


respected through time.

The opacity about what is traded and what strategies are used inside Hedge Funds is

also a characteristic that investors are less and less inclined to accept. Actually very


explained into monthly letters and so called monitoring documents…

The best example of how opacity is now denounced by investor is the Madoff case.


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manage dangerous position.

constraints and their incentive to performances is

Of course, risk management systems are set up in order to prevent high drawdowns

but when they want or they need to, it’s not unusual to see manager overcoming risk

The only way to have a close follow up of a Hedge Fund is to have massive due


de Hedge Funds is

to accept. Actually very


The best example of how opacity is now denounced by investor is the Madoff case.



were reported, links between administrator; manager and auditor were

hidden…Without the common acceptance for Hedge Funds opacity, this scandal

would never happen.

2.3 Liquidity

� A big issue for Hedge Funds that arose during the crisis was the liquidity. There is

actually a mismatch between how fast a Hedge Fund can blow up and how fast

investor can withdraw their entire money. Usually Hedge Funds allow redemptions

between monthly and quarterly with one to three months notification period. It means

when you decide to withdraw money you can wait up to 9 months during which

you’re still exposed to manager’s bad performances. The liquidity constraint caused

drastic problem through the crisis even if Hedge Funds performances were good.

Actually investors needed money elsewhere because of the market downturn and were

not able to balance it with Hedge Funds Investments. Here we can remind the

Amaranth case, where 3 months were enough to see the fund vanishes.

� Another issue is the gate activation. Most of hedge funds reserve the right to prevent

clients to withdraw money if they think it could cause damages to the fund. During the

crisis several Hedge funds activated these gates and investors were locked without the

possibility of withdrawing their investment.

� Finally, liquidity issue can arose when managers decide to create side pockets. It’s a

softer version of Gates where investor can only withdraw a part of the investment

according to which percentage of the fund managers consider as illiquid for the

moment. For example the manager would set apart all the CDO he has in his book and

allow its client to withdraw his part in the rest of the fund. The CDO book will be

longer to liquidate and more money can be lost with this exposition.


2.4 Fees structure

During past two years, investors were more and more reluctant with the fees structure applied

in the Hedge Fund industry. The most usual model is the 2/20 where you pay-on a monthly

basis- a 2% annualized rate of the net asset value managed by the fund for you and 20% of the

positive performance.

In addition to that, most of investors are already paying fees to different intermediaries before

entering the Hedge Fund. Wealthy investors often pays fees to a family office, Institutional

investors pays fees to fund of fund managers, or corporate investors pay fees to advisors…this

structure is good when performances is so high that the net performances are still matching

clients expectation, but when margins diminish through the crisis, the structure is not valid

anymore.

Even with the high-water mark system, which prevents the customer from paying two times

for the same positive performance, there is now a common thinking that this fees structure is

not efficient and too costly for the investor. Initiative with 1/15 or 0/30 structure has been

launched in the past years but it won’t solve the other issue hedge funds investors are facing.

As a conclusion to this first part, we can agree on the fact that investors need hedge funds for

their return distribution and are attracted by high risk-adjusted performances. Nevertheless,

the crisis emphasized some issue that has always existed but can no longer be ignored by

investors.

We need to think about how to challenge these new constraints: How to provide a product,

which understands investors need and desire with a better transparency, liquidity and fees

structure.


The new paradigm has already been investigated in theory and even products are launched by

investment banks respecting these new trends. We are going to see what they consist of and

what are the limits and the improvements that can be done.

II. POSSIBLE SOLUTIONS

3.1 Active replication: managed account platforms

The all idea of managed account consist in asking to the manager what is he doing and to do it

yourself.

Managed accounts are inspired, after all, on how most institutional investors give mandates to

traditional long only managers: as advisors to a portfolio which sits on the balance sheet of

the institution. The investor would keep control over the assets while the asset management

firm would simply acts as an advisor. Here, the asset management firm will be the hedge fund

manager. Then, some service providers called “platform” would be in charge of implementing

the transaction copied over the hedge fund's strategies. These platforms offer to open

Managed accounts in a large choice of hedge funds in order to allow investors to access easily

to manage accounts shares. We often see confusion between segregated (or separate) accounts

and managed accounts. The former is simply a customized mandate. It offers some form of

flexibility, but no control over the assets, which is the key aspect of a true managed account.

We should see it as the hedge fund manager being hired as a trading advisor with authority to

transact in the account but no control over the assets.

Since the goal to extract the operations out of the hedge funds firms, it instantly gives a full

transparency over what is being done inside your investments. Sotheby, the lack of

transparency, which was one of the deal breaking cons of Hedge funds is fully over passed.

Of course some hedge fund managers might want to protect themselves and request that the


actual list of securities held in the portfolio remain with the platform operator while it allows

for aggregate reports to be sent to the investors. In this situation, the platforms operators

should carry specifics in the contract linking him to the investor in order to keep this

transparency as high as possible.

Since the assets are not in the Hedge funds firm books anymore, the liquidity of managed

accounts is also greatly improved. Most managed account platforms will offer excellent

liquidity terms such as daily, weekly or monthly whereas most Hedge Funds firm would only

offers quarterly or semi-annual or annual redemption with often long notice period. Moreover,

many funds of hedge funds are now facing serious asset/liability mismatch as they promised

better liquidity terms than what they had with the underlying hedge funds and thus drives

them as weak competitors on the liquidity field.

To finish with the key advantage of managed account is to be able to have the control over the

assets and being able to deviate slightly from the original replicated investment in order to fit

it better to investors needs. For example, the platform would be able to overweight an

investment made by the advising manager in order to have a better-adapted product for its

final customers.

Nevertheless, this alternative is deceiving in terms of performances. The low performances of

managed account investments can mostly be explained by the accumulation of fees through

the process. Actually, it's obvious that the Hedge Fund Manager would ask expensive fees for

its advising role since he pretty gives a full transparency on his transactions and strategies

which are his key success factors in the business. We can also guess that replicating the

transaction of the managers should cost a lot of money and logistics to the platforms,

especially if they hold a large portfolio of Managed Accounts.


3.2 Passive replication

Since the active replication fail at achieving high performances and notably due to a heavy

fees structure, and a hardly sustainable business model, academics investigated the possibility

of theoretically mimic performances with models. Passive replication approach give up to

clone hedge funds investments position by position and focused on the basic claim that

originate these researches: “What investors are interested in is the return distribution.”

The working assumption is no longer to look inside the Hedge Fund to copy the idea and hope

to achieve similar return, but to only look at the time series, extract the statistical

characteristics and trying to produce the same output from different tools.

While Amin and Kat tried to achieve this goal trough replication of the expected return with

option based tools, the factor based approach tried to guess the hedge funds exposure and

achieve same returns by replicating these exposures.

3.2.1 Payoff replication approach (Kat)

This approach was developed by Amin and Kat in 2003. They assume that investors will be

attentive to look at more evolved risk adjusted performance indicators than just the Sharpe

ratio which has been proven to be an inefficient measure since return distribution are not

systemically Gaussian. Thus, they focus on replicating the co-moments of the return

distribution.

The idea of Payoff replication consists in a two-step process using Option pricing theory in

order to build up the “clone” portfolio.


Firstly, they study the relationship between the targeted Hedge fund and an index. After

analyzing the behavior of both time series during a long enough period to be significant, they

suppose that they are able to extract the conditional probability of achieving certain

distribution.

They manage now how the probability of the hedge funds to achieve certain distribution is

supposed to statistically drive the index performances. From this deduction they can set up an

optional portfolio, with the index as underlying, in order to match the hedge fund distribution.

Then the modern option pricing theory can be used to compute the price of the strategy using

cash and the index. In order to be efficient, the price of the strategy should be cheap enough

so the returns can also match.

We have to notice that the first aim of payoff replication is to replicate the distribution. Thus,

if it succeeds, they will be able to obtain two investments with similar co-moments. But the

primary needs of investors are often focused on absolute performances so the moment of the

replicated investment also has to be analyzed. Even if the two distributions of returns can

perfectly identical, the returns mean (first moment) can be totally different.

The Edhec research center tested this methodology in 2008. They used the 13 strategies of the

Edhec Hedge Funds Indices and tried to replicate them using basic risky asset like the S&P

500. They reported the differences between the first four moment of each strategy clones and

the original indice.


The results were analyzed and the main conclusions are the following:

� The average returns of clones are most of the time different from the original indices.

We expected that this methodology would drive us to different mean but it seems that

it is consistently lower (13 out of 13). It can be explained in part by the bear market

that heated the S&P 500 around 2002. The precaution would be to be very careful in

the choice of the chosen replication investible tool.

� Most of strategies can be replicated with a fairly good fidelity to the distribution. But

some strategies like fixed income arbitrage gave very poor results and their clones

don’t stick to the indices. Nevertheless, the fact that some strategy are harder to

replicate clearly shows on the other hand that some time series are easier to replicate.

One improvement would be to test this model on single hedge funds rather than on

Table 1 : Edhec Research center results testing Payoff Replication Approach


indices. We would see if single hedge funds time series share more properties with

fixed income arbitrage index or with convertible arbitrage index or if index and single

fund of a same strategy behave the same.

� There is good matching between index and clones concerning standard deviation,

skewness, kurtosis, and value at risk while the Sharpe ratio, due to lower mean, is

constantly lower.

� A longer calibration will give best results but to have a satisfying matching, they need

around 6 years of data, which is very long at the investor horizon level.

� Investors are also looking at the time series characteristics, which also take into

account the order of each return. The tests show that there is a poor correlation

between index and clones. It means that investor willing to use hedge funds as

diversification providers for their portfolio and want investments un-correlated from

main stock exchange won’t find these characteristics in Payoff Replication models.

To conclude with, the payoff replication model is able to assess some important claims of

investors, which are transparency, liquidity and return distribution.

But some imperative constraints like high enough returns, diversification and decorelation

were not successfully achieved trough empirical tests. Moreover, we have to analyze the price

of the option based portfolio construction, which should remain competitive or at least

comparable to the 2/20 fees structure.

3.2.2 Factor-based approach: linear multi-factor (basique) versus non-linear and/or

conditional multi-factor model (Fung-Hsieh, Lo, Martellini, Garcia, etc.)

In fact the factor approach to hedge fund replication faces a series of formidable challenges.

These challenges notably include the difficulty in identifying the right factors, as well as the

difficulty in replicating in a robust manner the time- and state-dependent exposures of hedge


fund managers with respect to these factors. This paper has provided an attempt to assess the

performance of non-linear and conditional factor models in terms of replication ability. We

find that going beyond the linear case does not necessarily enhance the replication

performance. We also find that selecting factors on the basis of an economic analysis allows

for a substantial improvement in out-of-sample replication quality, whatever the underlying

form of the factor model. Overall, we confirm the findings in Hasanhodzic and Lo (2007) that

the performance of the replicating strategies is systematically inferior to that of the actual

hedge funds.

As a conclusion, while the replication of hedge fund factor exposures appears to be a very

attractive concept from a conceptual standpoint, one has to conclude that it still is very much

work in progress. In the end, the relevant question may not be "is it feasible to deliver hedge

fund returns at lower cost?", for which the answer appears to be a clear negative, but instead

"can suitably designed mechanical trading strategies provide a cost-efficient way for investors

to get an access to alternative beta exposures?”. With respect to the second question, there are

reasons to believe that such low-cost alternatives to hedge funds might still be useful to

investors and managers of funds of hedge funds, either for benchmarking or for risk

management purposes.

III. A NEW PERSPECTIVE

As opposed to trying an replicate some exogenous HF performance, which has no very good

reason to be optimal for anyone, why not turning to investors and analyze their basic needs,

and generate an investment process to meet these needs.

Actually, the approaches we use to find an alternative to Hedge funds should be aiming at

finding investments able to fulfill the needs that made Hedge Funds successful: it's not a


matter of reproducing them with smaller costs but rather reaching the same characteristics of

returns. The working (simplifying) assumption is that investor interested in (non-directional)

HF returns are in fact essentially seeking absolute return performance. Good performances

when either the market is going down or up. In order to achieve this idea, the dynamic core-

satellite portfolios strategy has been developed during the past years.

The core-satellite approach aims at separating investor's portfolio management into the

construction of a strategic benchmark and the generation of outperformance of that

benchmark. The outperformance would be sought within the satellite investment while the

core would be made of an investment in broad market indices. This separation will allow the

investor to structure the portfolio in a coherent manner matching its needs: The core portfolio

will represent its long terms objectives in terms of risk-adjusted profile by a standard

exposure in commercial indices (through ETF for example) while the satellite portfolio will

generate outperformance with exposure to traditional risk premia or abnormal returns

obtained with active strategies (alpha).

The core portfolio will adhere to the defined benchmark and the tracking error would only be

generated by the satellite portfolio. Thus, a tracking error of 20% with a satellites’ weight of

10% should imply a 2% tracking error in the overall portfolio. Nevertheless, in order to

benefit more from good tracking errors (outperformance of the benchmark) it is necessary to

dynamically adjust the allocation between the core and satellite portfolios. In order to achieve

these dynamic shifts between weights, we will set up systematic rules reflecting investor’s

needs: The needs would reflect the objectives he had as a Hedge Funds customer.

The first advantage of the DCS approach will be to truncate the return distribution since the

rules of allocation will shift the risks for severe under-performances and gives more potential

to out-performances. Setting up a floor to respect will reflect the available allocation for the

risky asset (satellite portfolio) and thus the risk budget. For example, investors would be able


to choose between capital guarantee floor, maximum drawdown floor or trailing performance

floor as dynamic rules adjusting the allocation.

Investors could also consider a cap determined by the wealth level he wishes to reach. It

would allow stopping any drawdown risks as soon as the objectives are fulfilled and also a

downsizing of the strategies costs. All of these tools are perfectly suited in an absolute return

investment profile and thus should be a good alternative for Hedge Funds and more precisely

for the needs that were expressed by Hedge Funds investors.

Another achievement of these approach is to understand that one the objectives looked after

by Hedge Funds customers was to entrust its wealth management without interfering in it with

the use of forecasts and market views. The managers were entitled for that. What is

remarkable with DCS, it's the absence of forecast and thus forecasts risks since the allocation

between core and satellite portfolio are induced by past value and systematic rules settled up

from the beginning. Of course, investors may have access to proprietary forecasts that they

may wish to use to shift the allocation from the core to the satellite or from the satellite to the

core, but it stays as an available option and not a functioning need.

IV. NUMERICAL SIMULATIONS

In this part we are going to observe a numerical simulation of a DCS strategy. The Core will

be invested in a ETF for the reason I will explain and the satellite will be a managed account.

In order to get a wide range of observation to analyze the possible behaviors of the DCS

strategy, we will implement it with various parameters like leverage, floor or cap.

� An ETF is designed to replicate the performance of an equity index, a bond index or a

commodity index. The composition of the ETF is the same as the index it is supposed


to track and the magnitude of the variation can be

Unlike a conventional mutual fund, the

analysts and thus saves fees

impossible to beat an index and thus would rather save the cost of active management.

� We can argue that most of the existing

index construction since the capitalization weighted indexes for example are proven to

be inefficient but that’s not the subject of this simulation. We will assume that the ETF

used in the simulation satisfies

� We will use a bond ETF in order to have a low volatility core portfolio.

� The use of a managed account will allow us to get an exposure to traditional Hedge

Funds but thank to the liquidity offered we will be able to implement a DCS strategy.

Some managed account have a monthly or even weekly liquidity and thus allow us to

rebalance the DCS portfolio very often, as long as a cost analysis has been run in order

to determine what would be the good frequency. In the following numerical test, the

Rivoli managed account will be used with the following track record:


to track and the magnitude of the variation can be multiplied if leverage is applied.

Unlike a conventional mutual fund, the tracker does not require the use of financial

and thus saves fees.ETF’s supporters think that on the long run it’s almost


We can argue that most of the existing indices can easily be beaten by other passive



used in the simulation satisfies investor needs.

We will use a bond ETF in order to have a low volatility core portfolio.

Graph 6 : Barclays Aggregate Bond (AGG)

The use of a managed account will allow us to get an exposure to traditional Hedge

to the liquidity offered we will be able to implement a DCS strategy.



hat would be the good frequency. In the following numerical test, the

Rivoli managed account will be used with the following track record:

Page 26

multiplied if leverage is applied.

tracker does not require the use of financial

ETF’s supporters think that on the long run it’s almost


indices can easily be beaten by other passive



We will use a bond ETF in order to have a low volatility core portfolio.

The use of a managed account will allow us to get an exposure to traditional Hedge

to the liquidity offered we will be able to implement a DCS strategy.



hat would be the good frequency. In the following numerical test, the


Graph 7 : Comparedevolution of ETF, ManagedAccount, and risk free

� First method would be to implement the DCS with a fixed floor F and multiplier M.

In the following graphs we can observe the impact of varying floor and multiplier.

Here is the evolution of the DCS portfolio value with different floor F:

Graph

We can observe that the variation of the floor will allow the portfolio to

track the behavior of the ETF when it’s set close to 100% whereas the more

it will track the Managed account when the more the floor decrease.

Here is the different kind of behavior when the multiplier


: Comparedevolution of ETF, ManagedAccount, and risk free

implement the DCS with a fixed floor F and multiplier M.


Here is the evolution of the DCS portfolio value with different floor F:

Graph 8 : DCS with a fixedfloor F and multiplier M




Here is the different kind of behavior when the multiplier M is changing.

Page 27

implement the DCS with a fixed floor F and multiplier M.






Graph 9 : various multiplier M

Since we keep a high enough floor, the portfolio will have a behavior close

to the ETF, but a high multiplier will give higher impact of the Managed

account under and over-performances.

But investors might think that we would better adjust dynamically these

parameters through time in order to have a portfolio behavior coherent

with ETF and Managed account performances. That is why we are now

going to try evolving floors.

� The first intuition would be to adapt the CPPI structure with a capital guaranteed floor

adjusted on a risk free asset:

Ft=k×e-r(T-t)×A0

Graph 10 : Adaption of the CPPI structure with a capital guaranteedfloor


We can observe that the dynamic adjustment of the floor according to the

risk free benchmark allows the portfolio to be more allocated in the

Managed account when it’s value over performs a risk free investment. In

the case the portfolio underperform the risk free asset, the allocation to the

satellite will decrease waiting for the benchmark to catch up with the

capital guaranteed level.

But we can argue that an underperforming Core would be a good reason to

switch allocation to the satellite. That’s why the next step would be to adapt

the floor to the core the benchmark performance.

� Since we are facing investors who understand their goals, they will choose a

benchmark according to their liabilities and not as an absolute return goal. Thus, they

will be more likely to adapt the floor directly to the ETF they use as core instead of a

risk free asset. This parameter might show bigger underperformances but the

rebalancing between core and satellite should be better adapted to investor’s liabilities.

Ft=k× Bt

Graph 11 : Adaption of the CPPI structure with ETF as the core

Here we can observe that the portfolio will have a good timing in switching

the asset allocation to the risky satellite when the Core is underperforming.

Thus this reallocation can be dangerous when the satellite registers bigger


underperformances in the same time. Never the less we can expect that the

investor will be more likely to chose a Satellite with low or even reverse

correlation with the Core.

� Other constraint like maximum drawdown can also been adapted. With a floor

expressed as a percentage of the maximum value reached by the benchmark the

allocation in the portfolio will maximize the less risky asset as long as the portfolio is

in a drawdown period.

Graph 12 : Floorexpressed as a percentage of the maximum value

We can observe on the graph that the portfolio will behave like the

benchmark when its asset value is below the maximum value reached by the

benchmark, whereas it behaves much more like the satellite when the

drawdown floor is broken.

Now that we reviewed different ways to set a dynamic floor in our DCS strategy, let’s see

how, in this particular example, they differ from each others.


Graph 13 : Summary of the differentporfoliostrategies

To conclude with we observe a clear amelioration of the risk return profile

of any DCS portfolio compared either to the ETF or the Managed account.

1. Portfolios managed to keep an annualized volatility around 3.75%

whereas the managed account is at 7.40%...

ETF Managed Account

Mean Return 4,65% 9,59%

Anualized Vol 2,19% 7,40%

Sharpe 0,752 0,891

Excess Kurtosis 2,580 0,892

Skewness -0,281 0,206

Max Drawdown 14,73% 36,32%

Fixed Floor 90% Capital Guaranteed Benchmark Max Drawdown

Mean Return 6,93% 5,74% 4,97% 6,03%

Anualized Vol 3,29% 3,88% 3,43% 4,08%

Sharpe 1,195 0,706 0,575 0,742

Excess Kurtosis 0,492 1,093 0,792 1,049

Skewness 0,152 0,198 0,126 0,177

Max Drawdown 12,29% 11,09% 10,64% 13,86%

Table 2 : Financial ratio of the different stratégies compared to the core and the satellite


2. While annualized mean returns of the ETF are beaten by around 2

point.

3. The most revealing figures are the maximum drawdown. Both asset

composing the DCS have higher drawdown (14% and 36%) that any of

the portfolios. This can be explained by the use of floors. But contrary

to traditional CPPI, this result is very interesting since we are not using

risk free asset. This good result can this been explained by a good

allocation timing and underlines the importance of the choice of good

matching ETF and managed account.

4. We finally notice a consistent positive good skewness on the 4 portfolios.

Butwehave to keep in mindthatthemainaim of thestrategyisnotfocused on absolute

betterreturnsorevenvolatilitybut on meetinginvestorsneeds.Inthis way wecansaythatthe test

showsachievingresultsthrough a large decrease in themaximumdrawdowns in parallele with a

consistent better skewness.


V. CONCLUSION

Then late evolution of hedge fund market stress out the fact that new approaches need to be

found in order to keep Asset and investors interested in the industry.

Like it is often the case, the crisis underlined the weak sides of the business and for the

coming years, investors will keep attentive eyes on the following limits of alternative

Investments that we identified:

� Opacity

� Liquidity

� Fees structures

But investors will always been looking for uncorrelated portfolios, high returns, coherent

distribution and special opportunities of investment which were the main reasons they where

exposed to hedgefunds.

This paradox leaded us to look for the new paradigm in Altenative Investments.

After looking at the main existing answers like active replication and passive replication Pay-

off approache and Factor-based approache, it seemed that a new perscpetive was about to

bring a better solution: Dynamic Core-satellite Portfolio Strategies. The main idea of this

aproach aims at separating investor's portfolio management into the construction of a strategic

benchmark and the generation of outperformance of that benchmark.

We implemented numerical test in order to find out quantitative proof of benefits brought by

this strategy. It appears that in addition of bringing better volatility and anualized returns, the

drawdowns, which were one of the main default of hedge funds are clearly minimized while

the distribution of returns achieve consistent better skewness.

Thus, we can think that in the following years, the focus point of the alternative investment

industry should be to devellope new approaches allowing investors to regain confidence in

this kind of product and maintain the high level of asset under management reached recently.


Otherwise, investors will need a long time after the crisis to forget the main repulsor of hedge

funds and this asset class will have to go through huge withdrawing in the following years.


Bibliography

� A survey of A Survey of Demographics and Performance In the Hedge Fund Industry,

Arindam Bandopadhyaya , July 2006

� The Evolution and regulation of Hedge Funds, Andrew Crockett, April 2007

� The Hand Book of Hedge Funds, François-Serge Lhabitant, 2006

� The Myths and Limits of Passive Hedge Fund Replication, Edhec Risk and Asset

Management Researche Center ,June 2007

� Replication and Evaluation of Hedge Funds, Kat H. and Palaro E., 2006

� Hedge Fund Benchmarks: A RiskBased Approach, Fung and Hsieh, 2004

� Managed Account, Hedgeweek Special Report, Jan 2010

� The Edhec European ETF Survey, Edhec RAM Reaserche Center , May 2009

� Passive Hedge Fund Replication, Edhec RAM Reaserche Center , January 2008

� Realignement of Interest in Hedge Funds using a Managed Account Plateform,

Martin Gagnon – Innocap, January 2009

� Passive Hedge Fund Replication, A critical Assesment of existing tecniques, Amenc,

Meyfredi, Martellini, Gehin, 2008.

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Master Thesis - Hugo Cassat