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The Role of Managed Futures and Commodity Funds: Protecting Wealth during Turbulent Periods Professor John M. Mulvey Department of Operations Research and Financial Engineering Bendheim Center for Finance Princeton University Chairman, DPT Capital Management, LLC February 2012 WHITE PAPER

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Page 1: The Role of Managed Futures and Commodity Fundsdocs.edhec-risk.com/mrk/120503_Princeton/Research_papers/JMulvey...institutional investors, however, due to their size, organizational

The Role of Managed Futuresand Commodity Funds:Protecting Wealth during Turbulent PeriodsProfessor John M. MulveyDepartment of Operations Research and Financial EngineeringBendheim Center for FinancePrinceton UniversityChairman, DPT Capital Management, LLC

February 2012

W H I T E P A P E R

Role of Commodities_Whitepaper_US_21_2_Whitepaper 24/02/2012 09:21 Page 1

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Abstract

Often, investors are willing to accept short-term risks

in order to achieve long-term portfolio gains. A form

of this tradeoff has led to a movement away from

traditional equity and fixed-income investments and

towards illiquid alternative categories – private equity and

venture capital, real assets, and hedge funds. Leading

university endowments, many public pension plans, and

wealthy individual investors have embraced the shift to

illiquid investments.

The nature of illiquid alternative investments poses severe

challenges for protecting investor wealth during crash

periods and for achieving rebalancing gains. In this paper,

we discuss the advantages of highly liquid investments –

such as in the managed futures domain – for protecting

capital and for dynamic asset allocation.

The Role of Managed Futures and Commodity Funds Page 2

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The Role of Managed Futures and Commodity Funds Page 3

How can an investor protect his wealth against possible future

adverse events? We propose three basic approaches and

variants therein.

First, the investor can choose ultra conservative funds, including

cash management accounts and treasury bills, as his primary

investment vehicle. While protecting nominal wealth, short-term

fixed-income securities will inevitably lead to low returns,

especially under the current close-to-zero interest rate

environment throughout much of the world.

Safe short-term cash-like instruments fail as a hedge against

inflation risks. For longterm investors such as pension plans,

low asset return performance will result in the need for

relatively high contributions over time – which can be an

expensive approach for achieving short-term protection over

extended periods.

A second approach to wealth preservation is by anticipating

turbulent periods. Here, the investor lowers risk dynamically by

moving from risk bearing assets such as stocks to safe

investments such as short-term government bonds. Such a

flight-to-quality approach can be difficult to implement for large

institutional investors, however, due to their size, organizational

structure, and shift to illiquid alternative investments (Swensen

2000). Also, dynamic asset allocation can be expensive due to

market impact costs, false positive indicators, and time delays.

A third approach is to invest in assets and strategies that are

likely to perform well during

turbulent crash periods. There are two primary variants: a) tail

risk strategies; and b) strategies or asset categories that have

done well historically during turbulent periods. The former is

designed to pay off during a crash, whereas the latter is not

guaranteed but may be less expensive to implement.

As we discuss in this paper, managed futures in general, and

commodity futures in particular, fits the third approach and

accordingly should be considered an important component of a

long-term investor’s portfolio.

Managed futures encompass four general asset categories:

commodities (agricultural markets, energy products, and

metals); currencies; bonds; and equity indices. In each of these

cases, a futures (or forward) market is established by

participants to either hedge or speculate on the underlying

instrument. At any given time, a futures pricing curve can be

constructed by plotting the prices of futures contracts expiring

across the expiration spectrum.

There can be some confusion in futures/commodity

nomenclature due to historical circumstances and regulatory

issues. In the United States, the Commodity Trading Futures

Commission (CTFC) and National Futures Association (NFA)

regulate futures markets and their participants. The first futures

markets were commodities markets such as grains, softs (e.g.

cotton) and metals; energy products then followed.

1. Introduction

2010 20

1119

8019

8119

8219

83 1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999 20

0020

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0320

0420

0520

0620

07 2008

2009

$0

$70

$140

$210

$280

$350

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nder

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agem

ent (

$bn)

0 0 1 1 1 1 2 4 6 7 11 15 19 26 25 23 24 33 36 41 38 41 51

87

132131

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268

Series1, 320

YTD

207 206 214

Exhibit 1Growth of managed futures and commodity markets

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The Role of Managed Futures and Commodity Funds Page 4

Eventually, futures markets have expanded significantly to

include currencies, fixed income instruments and equity

indices. Today, professional money managers who trade

primarily futures are designated as commodity trading

advisors (CTAs), regardless of which sectors they trade. In this

report, we differentiate the broader managed futures area

from the original commodity futures markets.

Commodity investments have gained in interest by individual

and institutional investors over the past decade. For example,

trading volume in exchange traded commodities has

increased dramatically. Furthermore, assets under

management more than doubled between 2008 and 2010 to

nearly $380 billion (Exhibit 1). And commodity prices have

increased. Market participants attribute the recent price

increases in commodities to increased demand for consumer

goods, particularly from the populous countries of India and

China. In contrast, the size of the world stock market was

estimated at about $46.8 trillion at the end of March 2010.

As we show, for traditionally diversified investors, an

allocation to a fund that invests exclusively in commodity

markets offers not only a hedge against inflation, but also

effective diversification because of its low correlation with

traditional asset classes. In the long run, commodity

investment funds show equity-like returns, but are

accompanied by lower volatility and shortfall risk.

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The Role of Managed Futures and Commodity Funds Page 5

Fundamental flaws in traditional portfolio models became

apparent during the severe 2008/09 banking, real estate, and

general economic crash. Among other problems, many investors

had assumed that correlations in rates of return among asset

categories would approximate historical values going forward.

Under this assumption, the investor would be adequately and

safely diversified to “protect” his capital during a crash.

Unfortunately, most asset categories suffered together and lost

substantial value. The extreme level of contagion occurring

during this crisis can be attributed to several factors. First,

market risk soared to unprecedented levels; for example, the

implied volatility of U.S. stocks exceeded 70% annualized value

and correlation among asset categories trended towards 1.0 or

-1.0. As we know from asset pricing, the “fair value” of a

security depends upon risk adjusted discounting of future cash

flows, or via risk neutral valuation (arbitrage free pricing). In

both cases, if the risks increase along with much higher

volatility, prices will plunge. As this crash showed, the financial

sector is critical to the health of the overall economy, hence the

spreading of extreme contagion throughout the equity, fixed-

income, and other asset categories. The U.S. real estate crisis

and a sharp drop in confidence accompanied the crisis in the

financial sector.

Finally, liquidity considerations caused many markets and

strategies to become unstable since investors could not sell their

asset in response to severe turbulence; market liquidity

evaporated for many securities.

Most asset allocation and asset-liability management (ALM)

models assume that the

2. Where’s the Diversification?

Exhibit 2Portfolio models often assume fixed-correlation betweenasset returns

Estimated Correlation Matrix for Asset Returns from a ALM Study for a

Large Public Pension Plan

These results do not properly Model Contagion during Market Crashes

CORRELATION MATRIX

Class Liquidity Fixed Income Real Estate Global Equity Absolute Equity Private Equity

Liquidity 1.00

Fixed Income 0.30 1.00

Real Estate 0.25 0.40 1.00

Global Equity 0.10 0.01 0.40 1.00

Absolute Return 0.00 0.60 0.30 0.35 1.00

Private Equity 0.15 -0.10 0.50 0.80 0.10 1.00

Exhibit 3Correlation between equities and government bond returns changes over time based on economic conditions(normal versus crash) – weekly time steps

Jan-19

60

Jan-20

00-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Jan-19

80

Jan-19

90

Jan-19

70

Jan-20

09

Jan-19

65

Jan-20

05

Jan-19

85

Jan-19

95

Jan-19

75

Jun-20

09

Source: Global Financial Database, S&P500.

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The Role of Managed Futures and Commodity Funds Page 6

correlations among asset returns are relatively constant. Exhibit

2, for example, depicts the assumed correlation matrix for a

$140+ billion California pension plan (Collier and Olleman,

2010). Note in particular, the correlation between equities and

bonds is assumed to be close to zero. As shown in Exhibit 3,

however, the rolling correlation between stocks and

government bond returns takes on a distinctive pattern –

positive during normal business conditions, and negative during

recessions and crashes.

These charts show the existence of distinct economic regimes.

Including these more realistic conditions in an asset allocation

study will improve investor performance.

Even absolute performance hedge funds failed to protect

investor capital during 2008/9 (Exhibits 4, 5 and 6). Exhibit 4

shows the weekly correlations of the returns of hedge fund

categories to FTSE U.S. equity 500 returns over the span

September 2005 to August 2011. As evident, several hedge

fund categories – emerging markets, multi-strategy, long-short

equity, distressed, fixed-income arbitrage, and risk arbitrage --

had a higher correlation to the FTSE 500 returns than the other

categories. Two categories – dedicated short bias and managed

futures – stand out with very low correlation to the FTSE 500.

The orange colors depict hedge-fund categories with negative

returns over the target period; categories in blue have positive

returns.

Exhibit 5 shows cross connections among the hedge fund

categories. Most funds had relatively high cross correlations,

with a couple of exceptions, and most had positive performance

over 2005-11. Here again, managed futures and dedicated

short stand out with relatively low or uncorrelated performance

to the other hedge fund categories.

Exhibit 4Correlations between FTSE U.S. 500 and Major HedgeFund Categories – 2005 to 2011(heavy line = correlation > .5; light line = correlationbetween .2 and .5; no line = correlation < .2)

GSCI(6.15%)

FTSE U.S. 5002.09%

Event DrivenDistressed

5.33%

Long/ShortEquity0.71%

Event DrivenMulti-Strategy

6.48%

Event Driven4.08%

Event DrivenRisk Arbitrage

5.04%

Equity MarketNeutral(3.23%)

Global Macro1.99%

DedicatedShort Bias(4.39%)

ManagedFutures7.12%

Fixed IncomeArbitrage(4.62%)

ConvertibleArbitrage

1.60%

Multi-Strategy1.26%

EmergingMarkets3.75%

Exhibit 5Correlations among Major Hedge Fund Categories –2005 to 2011(heavy line = correlation > .5; light line = correlationbetween .2 and .5; no line = correlation < .2)

GSCI(6.15%)

FTSE U.S. 5002.09%

Event DrivenDistressed

5.33%

Long/ShortEquity0.71%

Event DrivenMulti-Strategy

6.48%

Event Driven4.08%

Event DrivenRisk Arbitrage

5.04%

Equity MarketNeutral(3.23%)

Global Macro1.99%

DedicatedShort Bias(4.39%)

ManagedFutures7.12%

Fixed IncomeArbitrage(4.62%)

ConvertibleArbitrage

1.60%

Multi-Strategy1.26%

EmergingMarkets3.75%

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Exhibit 6 examines the recent crash period. Here we see that

the correlation matrixbecomes almost completely covered with

ones. Of particular note: 1) most hedge-fund categories lost

money during this period (even dedicated short bias funds); and

2) the precipitous drop of 51.4% in the Goldman Sachs

Commodity Index (GSCI) over the specified year which includes

a maximum 75+% drawdown within the one-year period. This

clearly calls into question the efficacy of a long-only approach

to commodities as a value-added asset. The managed futures

category was the sole category with positive performance.

Most investors who thought they were adequately diversified

learned the hard way that this simply wasn’t the case. Even top

university endowments – Harvard, Yale, and Princeton

Universities – experienced losses of 25% to over 30%. This level

of loss of capital usually has critical consequences for achieving

the goals of long-term investors.

Exhibit 6Correlations among Major Hedge Fund Categories –Feb 2008 to Feb 2009(heavy line = correlation > .5; light line = correlationbetween .2 and .5; no line = correlation < .2)

GSCI(51.40%)

EmergingMarkets(42.95%)

Multi-Strategy(29.45%)

ConvertibleArbitrage(38.20%)

Fixed IncomeArbitrage(36.20%)

ManagedFutures15.30%

DedicatedShort Bias(5.23%)

Event DrivenRisk Arbitrage

(1.98%)

Event Driven(14.87%)

Event DrivenMulti-Strategy

(12.57%)

Long/ShortEquity

(22.99%)

Event DrivenDistressed(18.72%)

FTSE U.S. 500(42.57%)

Global Macro(23.37%)

Equity MarketNeutral

(22.82%)

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The Role of Managed Futures and Commodity Funds Page 8

The managed futures category has significant advantages over

traditional assets. Futures markets are some of the most liquid

in the world, providing exposure to currencies, bonds, equity

indices, and commodities. These instruments are readily traded,

even during severe market turbulence. Importantly, the investor

can go long or short without barriers typically associated with

shorting stocks and bonds – no borrowing needed or searching

for assets to borrow, or inverse ETFs. These markets also are

exchange-traded, easily valued, and marked-to-market daily.

Second, leverage in a futures market differs from traditional

leverage. An investment via futures does not require direct

capital; rather, trades are designated by reference to two

distinct “accounts”. The investor’s core capital is placed in a

margin account, which is the depository for daily profits and

losses from the futures positions. For individual investors, the

margin account consists of risk-free assets such as 1-year T-bills.

In contrast, it is relatively easy for an institutional investor to

maintain margin capital in risk bearing liquid assets such as

equities and bonds. The performance of the margin account

can play a significant element in managed futures.

The second “account” tracks the return of the futures positions.

Performance depends upon the characteristics of the underlying

instrument – currencies, bonds, equity index, or commodities.

Futures markets are overseen by regulated exchanges, thus

largely avoiding counterparty risks1. Exchanges require marked-

to-market settlement daily. Also, the exchanges can alter the

margin requirements depending upon current market

conditions. For instance, the margin requirement will increase

when volatility in the underlying instrument expands greatly.

Since futures markets are liquid, an investor can apply dynamic

asset allocation models and strategies without incurring large

market impact costs. For instance, the investor can implement

drawdown constraints over short time periods (Mulvey, et al.

2011). Likewise, rebalancing gains can be exploited by resetting

the asset mix to pre-determined target proportions. In these

cases, liquidity provides a distinct advantage since it plays a role

in improving portfolio performance.

3. Features of Futures Markets

1 Recent problems occurred with MF Global.

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The commodity segment of the managed futures domain can

provide exceptional diversification from equities and fixed

income. Commodity futures markets are among the oldest

organized exchanges in the world, such as the Dojima rice

futures market, which began in 1710 in Osaka Japan, and the

Chicago Board of Trade, which opened in 1848.

In recent years, investors have turned to owning commodities

and other real assets to protect themselves against long-term

risks. First, as the world population approaches seven billion

people, the demand for basic commodities bumps against

limited supply constraints for land, energy supplies, and

agricultural products, and so on possibly resulting in pricing

disruptions. Even safe drinking water is becoming a scarce

commodity in many parts of the world.

A related risk is inflation. Many countries are experiencing

extraordinarily low nominal interest rates2 and massive deficit

spending plans in order to overcome the fallout from the

2008/09 crash. For these countries, there is the temptation to

inflate themselves out of their current monetary problems,

especially if the local constituents do not understand the

importance of fiscal discipline to ensure long-term financial

stability. Further, the current level of negative real interest rates

in a number of countries likely will contribute to future

increased inflation.

Political risks, such as disruptions caused by oil embargos, wars,

and terrorist attacks, present another concern. Owning raw

materials can be profitable during turbulent periods caused by

political factors. Further, it’s likely that equities will drop very

quickly when a political crisis erupts. The 1973 oil embargo, for

example, precipitated a substantial increase in energy prices,

accompanied with higher inflation.

Last, there is a small, but still significant risk due to weather and

catastrophic shocks such as crop freezes, hurricanes, and

tsunamis. Many commodity prices will spike up when these

events are present.

Investing in commodities promises to reduce the

aforementioned risks. However, it’s difficult for most investors to

own raw materials outright due to storage and insurance costs,

depreciation, and related issues. Instead, investors have turned

to futures and forward markets in the commodity domain. In

addition, there are several other paths for investing in

commodities, including single commodity exchange traded

funds (ETFs), long-only commodity ETFs (matching indices such

as the Goldman Sachs Commodity Index3), and commodity only

hedge funds such as Clive Capital4 for high net worth

individuals and institutions.

There has been considerable research into the characteristics of

commodity prices over extended time periods. Studies have

shown the presence of trends and regime changes in

commodity markets (e.g. Erb and Harvey 2006; Miffre et al.

2007; and Shen et al. 2007). These patterns are due to multiple

causes, including the gradual diffusion of information, inventory

conditions, the impact of weather, and political risks. In many

cases, prices follow patterns consistent with trend following and

momentum5. These relationships can be traced to several

theories including diffusion of information and noisy traders

(Chan et al. 1996; DeBondt and Thaler 1987; George and

Hwang 2004; Hong and Stein 1999; and Rouwenhorst 1998).

For instance, if a farmer hedges against adverse events one year

and is successful, he may be inclined to hedge the next year.

Likewise, neighboring farmers will often follow the successful

hedger. Gradually, since commodities are employed for

consumption - either final or intermediate, consumers and

producers have to render hedging decisions on an ongoing

basis as a function of their core businesses. Likewise,

speculators will often watch the market for underlying patterns

and take action in concert with these patterns. The basis for

many commodity-trading strategies is sustained price swings –

either positive or negative.

A second source of alpha relates to the shape of the futures

curve. In most commodities,

4. Sources of Alpha in Commodity Markets

2 Interest rates on 10-Year U.S. government bonds have dropped from 15.84% in September 1981 to less than 2% recently.3 The GSCI is the most popular commodity index product, with over $100 Billion tracking the index.4 Clive capital has been a successful hedge fund investing in commodity markets.5 Trend following and momentum tactics are based on differing rules and underlying philosophy.

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The Role of Managed Futures and Commodity Funds Page 10

the price of a futures contract is not determined by arbitrage

arguments. Supply and demand considerations are paramount.

Thus, for example, backwardation occurs when inventories are

low and spikes in demand are present. Tactics based on the

shape of the futures curve can lead to positive performance

(Gorton et al. 2008; and Brennan et al. 1997).

There is some controversy as to whether alpha is present in

managed futures funds. For instance, the study at Yale

University (Bhardwaj et al. 2008) indicates that commodity

trading advisors (CTAs) rarely earn much more than the risk free

rate. This study was completed before the 2008 crash in which

managed futures funds outperformed other hedge fund

categories by a wide margin.

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The Role of Managed Futures and Commodity Funds Page 11

Passive indexing strategies have become well established over

the past thirty years. These strategies are designed to match a

well-defined market segment with a low cost (and possibly tax

efficient) approach to investing. There is considerable evidence

that passive indexing strategies are especially pertinent for large

institutional investors, due to their low cost and fees as well as

transparency. Passive funds typically have lower turnover than

active funds.

Long-only commodity indices have done well over extended

periods of time. Exhibit 7 shows the FTSE 500 alongside a

popular commodity index – the Goldman Sachs Commodity

Index (GSCI). The GSCI is an index of long-only investments in

the most actively traded commodities and is a popular

benchmark for many institutional investors.

There are several evident observations. First, the overall price

patterns of the GSCI and FTSE 500 are roughly similar. The GSCI

outperformed the FTSE 500 and related equity indices over the

entire 1999 to 2011 time period in terms of returns, with

associated higher volatility and drawdown values. Second, the

GSCI experienced severe losses during the crash period

2008/09, partially due to the sharp correction in oil and other

energy based commodities.

Exhibit 8 shows that spot prices of commodities rose along with

equities in early 2009 until early April 2011. However, the

investible version of the GSCI (an exchange traded fund with

the symbol GSG) achieved much lower performance during the

same period. The under performance is largely due to the

presence of contango in many commodity markets, especially

energy products, over the selected time periods. The commodity

prices in contango lowered returns since the index is long-only.

5. A Relative-Value Commodity Index

Exhibit 7Time Series of GSCI and FTSE 500 indices

GSCI Total Return FTSE 500 Total ReturnJul

-1999

Jul-20

070

1000

2000

3000

4000

5000

6000

Jul-20

03

Jul-20

05

Jul-20

01

Jul-20

09

Jul-20

11

Exhibit 8Time Series of GSCI spot index and investible “tracking”fund (GSG) – source Bloomberg

GSCI Spot Index Investible “Tracking” Fund (GSG)

2006

2010

0

50

100

150

200

2008

2009

2007

2011

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The Role of Managed Futures and Commodity Funds Page 12

To address the problems with long-only commodity investments

– primarily large drawdowns and losses due to contango, we

developed a relative-value commodity index using the following

four sub-tactics: long momentum, short momentum, long

futures curve, and short futures curve6. Each of these tactics is

based on a relative ranking of the commodities under study7.

Briefly, the four tactics are designed to capture alpha embedded

in commodity markets, while carefully balancing the long and

short positions in the portfolio – in order to minimize

drawdowns and produce positive returns with excellent

diversification characteristics (as compared with traditional

assets). Recall that managed futures investments can be

designed as an overlay strategy – providing additive

performance to standard assets.

Exhibit 9 depicts the performance of our relative long and short

momentum tactics. Note that the relative long-momentum

tactic outperforms the relative short momentum over most of

the entire span. However, during crash periods – 2001/02 and

2008/09 the short momentum tactic did much better than its

long-only counterpart. The two tactics combine to provide a

more stable return pattern.

A similar characteristic occurs with the long and short futures

curve tactics (Exhibit 10). Here, the long futures tactic has the

better long-term return as compared with the shortfutures

tactic, but does suffer from sharp drawdowns. Again, the

combined long-short tactic has superior return/risk

characteristics.

Momentum Long Only

Jan-19

99

Jan-20

0702468

1012141618

Jan-20

03

Jan-20

05

Jan-20

01

Jan-20

10

Jan-20

09

Jan-20

00

Jan-20

08

Jan-20

04

Jan-20

06

Jan-20

02

Jan-20

11

Momentum Short Only

Jan-19

99

Jan-20

070.00.20.40.60.81.01.21.41.61.8

Jan-20

03

Jan-20

05

Jan-20

01

Jan-20

10

Jan-20

09

Jan-20

00

Jan-20

08

Jan-20

04

Jan-20

06

Jan-20

02

Jan-20

11

Momentum Market Neutral

Jan-19

99

Jan-20

070.00.51.01.52.02.53.03.54.04.5

Jan-20

03

Jan-20

05

Jan-20

01

Jan-20

10

Jan-20

09

Jan-20

00

Jan-20

08

Jan-20

04

Jan-20

06

Jan-20

02

Jan-20

11

Futures Curve Short Only

Jan-19

99

Jan-20

070.00.20.40.60.81.01.21.41.6

Jan-20

03

Jan-20

05

Jan-20

01

Jan-20

10

Jan-20

09

Jan-20

00

Jan-20

08

Jan-20

04

Jan-20

06

Jan-20

02

Jan-20

11

Futures Curve Market Neutral

Jan-19

99

Jan-20

070

1

2

3

4

5

6

7

Jan-20

03

Jan-20

05

Jan-20

01

Jan-20

10

Jan-20

09

Jan-20

00

Jan-20

08

Jan-20

04

Jan-20

06

Jan-20

02

Jan-20

11

Futures Curve Long Only

Jan-19

99

Jan-20

070

5

10

15

20

25

Jan-20

03

Jan-20

05

Jan-20

01

Jan-20

10

Jan-20

09

Jan-20

00

Jan-20

08

Jan-20

04

Jan-20

06

Jan-20

02

Jan-20

11

6 A dynamic long-only commodity index was created by Summerhaven, with an investible ETF whose symbol is USCI. The Summerhaven approach is long-only and employs tactics that are somewhat different than the ones describedin this paper, although we suspect the motivations are similar in spirit.

7 Most commodity tactics do not depend upon a relative value approach. For example, trend followers will go long a commodity when the current price exceeds a moving average of past prices

Exhibit 9Momentum tactics (long and short) and market neutralcombination -1999 to 2011

Exhibit 10Futures curve tactics (long and short) and marketneutral combination – 1999 to 2011

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The Role of Managed Futures and Commodity Funds Page 13

Exhibit 11 depicts the performance of the long-short relative-

value commodity strategy, along with market neutral version

over the period 1999 to 2011. The relative value approach

applies regimes for determining the tilting of long and short

positions. Exhibit 12 shows the results of the relative value

index. In addition, we provide the empirical results of a regime

detection system for U.S. equities (Guidolin and Timmermann

2007; and Mulvey et al. 2011).

Since we can gain exposure to commodities via the futures

markets, we can enhance the returns of traditional assets. In this

example, we couple commodities with a regime identifying

equity model (Mulvey et al. 2011). The overall performance is

excellent. In particular, we focus on the ratio of return to risks

wherein risk is measured by the Ulcer Index8 – downside risks

relative to drawdown. The combination of commodities and a

careful, regime bases equity strategy is clearly attractive and has

low correlation with the FTSE 5009.

8 The Ulcer index measures both the length and depth of drawdown over time.9 In an early study, Lintner (1983) showed the advantages of commodity funds for improving performance in conjunction with traditional assets.

Exhibit 11Combining long and short momentum and futures curve tactics: Relative value versus market neutral – 1999 to 2011

DPT Target Relative Value Market Neutral

Jan-19

99

Jan-20

070

1

2

3

4

5

6

7

8

9

Jan-20

03

Jan-20

05

Jan-20

01

Jan-20

10

Jan-20

09

Jan-20

00

Jan-20

08

Jan-20

04

Jan-20

06

Jan-20

02

Jan-20

11

Exhibit 12Combining relative value commodity and regime detecting equity tactics versus FTSE US 500 Index

JULY 1, 1999 TO DECEMBER 31, 2011

Jul 1999-Dec 2011 FTSE500 Equity-regimes + Commodities Commodities only Equity only – regimes60% commodities 40% equities 40% 60% 30% 60%

Geo. Return 1.18% 10.70% 5.23% 7.89% 1.96% 3.89%

Volatility 21.39% 6.26% 3.49% 5.24% 2.59% 5.19%

Sharpe ratio** -0.08 1.23 0.64 0.93 -0.40 0.17

Drawdown 54.73% 7.27% 4.77% 7.13% 3.27% 6.50%

Ret/Drawdown 0.02 1.47 1.10 1.11 0.60 0.60

Ulcer Index 22.44% 2.25% 1.48% 2.22% 1.17% 2.33%

UPI -0.08 3.42 1.51 2.20 -0.89 0.38

Corr w/ FTSE500 1.00 -0.018 -0.019 -0.019 -0.005 -0.005

2% fee 2% fee 2% fee no fees no fees

**3% risk free rate

*Data is back-tested only. All investors should be aware that future results may not be the same as historical performance.

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A fundamental lesson emerging from the 2008/09 economic-

crash is that only a few strategies provide meaningful

diversification from equities when severe contagion strikes.

Standard risk management suffers accordingly, with substantial

portfolio losses.

Even absolute return hedge funds purporting to provide positive

returns failed to protect investor capital -- although losses here

generally were much less than the 50+ percent plunge that

occurred in equity markets. This situation led to a substantial

loss of investor wealth, a reduced chance to attain investment

goals (and for pension plans, to meet legal liabilities), and a

wakeup call for investors who have been applying traditional

portfolio models based on a relatively static framework such as

the Markowitz portfolio model. Instead, a dynamic asset

allocation approach would have been much better (Mulvey et

al. 2006 and 2008).

This paper discusses the advantages of commodity futures, and

managed futures in general, as bona fide standalone

investments and as meaningful diversifiers within a portfolio of

traditional assets. The managed futures category of hedge

funds performed particularly well during the 2008/9 crash

periods. In fact, it was the sole hedge fund category with

positive performance in 2008/9.

We have seen similar results in previous crash periods including

the Asian currency crisis in 1997-98, the Russian debt debacle

and LTCM in 1998-99, and the technology bubble and crash and

the 9/11 disaster in 2001-03. The positive performance can be

attributed to several factors: 1) the ready ability to go long or

short depending upon economic and other circumstances; 2) the

availability of deep liquidity allowing for dynamic asset allocation;

and 3) the opportunity to take advantage of volatility via

rebalancing gains and regime changes. Each element provides a

small advantage. When combined, however, a portfolio of

commodity tactics can substantially improve overall investment

performance, especially when traditional assets are doing poorly.

6. Conclusions

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The Role of Managed Futures and Commodity Funds Page 15

The performance of a portfolio of managed futures tactics in a

fund can be subdivided into three components. The first

element involves return on the capital set aside for providing

the margin for the futures securities. In many cases, especially

for individual investors, their margin funds must be placed in

risk free and highly liquid funds such as 1-year T-bills. Today,

these investments are likely to remain close-to-zero

performance, given the ultra-low level of interest rates across

the globe. Institutional investors are allowed to post other liquid

assets in their margin accounts, such as equities and

fixedincome securities, with the possibility of sizeable returns

(with greater risks naturally).

Second, the return of individual tactics as standalone

investments is a primary component. For example, we might

construct a trend following rule for investing in gold futures.

The geometric mean of an index based on this tactic provides

attribution of this component – about 2-4% per year over the

past thirty years.

The third component involves portfolio determinatives.

Accordingly, a fund that employs the fixed proportional

investment rule, such as, 60% equity and 40% bonds will,

in many cases, outperform a buy-and-hold (do nothing) rule.

This excess return is called rebalancing gains, which can be

substantial for highly volatile markets and tactics such as we

have seen in the commodity arena. In other cases, the

rebalancing gains will depend upon more complex rules and

models such as via financial optimization models. Any excess

(or shortfall) return of this dynamic portfolio over the buy-and-

hold rule falls into this component. Luenberger (1998), and

Mulvey and Kim (2008) provide further discussion. More recent

studies in other areas have confirmed these empirical tests

(e.g. Mulvey et al. 2007, and the Rydex equal weighted version

of the S&P 500).

Appendix: Performance Attribution

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This publication does not constitute an offer or invitation to buy or sell any investment or participate in any investment activity, nor any advice concerning the acquisition or disposal of securities. This publication has not been approved by a

person authorised under the Financial Services and Markets Act 2000 (“FSMA”) for the purposes of section 21 of FSMA. Accordingly this publication and the information contained within it is only made to, and for the use of, persons whom

FTSE believes to be investment professionals within the meaning of article 19(5) of the Financial Services and Markets Act 2000 (Financial Promotion) Order 2005 or U.S. institutional investors and major U.S. institutional investors, as provided

by Rule 15a-6 under the U.S. Securities Exchange Act of 1934. This publication and the information contained within should not be relied upon by anyone else. All information is provided for information purposes only and is derived from historical

data and information deemed to be reliable and generally available to the public in its primary form. Nothing in this publication constitutes financial or investment advice, nor any advice concerning the acquisition or disposal of securities. You

should exercise your discretion in your use of the information contained within this publication and if you do not have the relevant professional expertise in relation to investments of the kind referred to in this publication, before using the

information you should consult an investment professional who does for advice. FTSE makes no claim, prediction, warranty or representation whatsoever, expressly or impliedly, either as to the results to be obtained from the use of the information

contained within this publication or the fitness or suitability of such information for any particular purpose to which it might be put. No responsibility or liability can be accepted by FTSE for any errors or for any loss from the use of this publication.

All figures and graphical representations in these slides refer to past performance and are sourced by FTSE. Past performance is not a reliable indicator of future results. “FTSE®” is a trade mark of the London Stock Exchange Group companies

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