qCIO Global Macro Hedge Fund Strategy (September 2011)

8/4/2019 qCIO Global Macro Hedge Fund Strategy (September 2011)

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This material does not constitute investment advice and should not be viewed as a currentor past recommendation or a solicitation of an offer to buy or sell any securities or to adoptany investment strategy.

Q.M.S AdvisorsAv. de la Gare, 1 | 1003, Lausanne | CH

tel: 078 922 08 77e-mail: [email protected]

website: www.qmsadv.com

qCIOGlobal Macro Hedge Fund Strategy

September 2011
http://www.qmsadv.com/http://www.qmsadv.com/


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Q.M.S Advisors Av. de la Gare. 1 | 1003, Lausanne CH | tel: 078 922 08 77 | e-mail: [email protected] | website: www.qmsadv.com Page 1Q.M.S Advisors Av. de la Gare. 1 | 1003, Lausanne CH | tel: 078 922 08 77 | e-mail: [email protected] | website: www.qmsadv.com Page 1

qCIO:

Capitalizing on Market Inefficiencies

Long-Term Returns from Short-Term Dislocations

In the long run, markets tend to behave like weighing

machines, which value assets rationally on the basis of

what they are actually worth. In the short term,

however, he knew them to be more like voting

machines, which reflect the often erratic desires and

fears of fickle publics and willful national governments.

Benjamin Graham
http://www.qmsadv.com/http://www.qmsadv.com/http://www.qmsadv.com/http://www.qmsadv.com/


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qCIO:

Exploiting Temporary Mispricings

qCIO seeks to exploit these constantly evolving

economic conditions and the temporary mispricings

that result among individual geographies and asset

classes, opportunistically adjusting our investmentviews in response to the changing patterns of risk and

reward in the markets.

qCIO does this through close quantitative analysis of

global pricing trends, business cycles, volatility levelsand other macro-economic signals.


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qCIO:

A Market Neutral Global Macro Fund

Bespoke Tactical Macro Investing

qCIOs returns are driven not by the directional

movement of any one market but by exploiting short-

term mispricings among the markets themselves.

Additionally, qCIOs derived alpha tends to be highly

efficient due to the targeted balance of risk and return

it achieves across markets. qCIO: a customizable strategy with a consistent return

per unit of risk.


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This material does not constitute investment advice and should not be viewed as a currentor past recommendation or a solicitation of an offer to buy or sell any securities or to adoptany investment strategy.

Quantitative Global MacroHedge Fund StrategySeptember 2011


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Q.M.S Advisors Av. de la Gare. 1 | 1003, Lausanne CH | tel: 078 922 08 77 | e-mail: [email protected] | website: www.qmsadv.com Page 5

Table of Contents

Portfolio Objectives

Asset Classes and Market Coverage

Model Overview and Investment ProcessOverview of Signals Across Investment Strategies

Derivation of Relative Return and Risk Expectations

Blending: Aggregation and Apportioning of Views

Portfolio Construction


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Historical simulation does not guarantee future performance of any individually managed account or fund.

Example:Objective

Excess Return over Cash 10 - 20%Volatility 5 - 10%Sharpe Ratio 2.0

Relative Tactical positions are formulated on an Absolute Return basis

To maximize risk-adjusted total return

Long or short positions may be taken in any asset classes

The portfolio may be implicitly leveraged

Trades are implemented with futures, forwards or option contracts

Stock-index futures, forwards or options on nine equity markets

10-year government bond futures, forwards or options in seven countries

Currency futures, forwards or options on seven currencies

Portfolio ObjectiveQuantitative Global Macro Strategy Focused On

Maximizing Risk-adjusted Returns


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A set of Models covering multiple Asset Classes and Markets

Markets currently included in the modeling process

9 stock markets: US, Japan, UK, Eurozone, Switzerland, Australia, Canada,

Hong Kong and emerging markets

7 bond markets: US, Japan, UK, Germany, Australia, Canada, Switzerland

7 currency markets: USD, EUR, JPY, GBP, CHF, CAD,AUD

A system built around five independent set of models, with non-

overlapping signals and return drivers

Risk Premia: Intra-country Relative Value: Inter-country

Stock-Bond Stock VS StockBond-Cash Bond VS Bond

Currency

CoverageAsset Classes and Markets


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An quantitative global macro investment strategy built around five

independent sets of models with non-overlapping signals and return drivers

Model OverviewGlobal Macro Strategy: Approach

Cash VS Bond Bond VS Stock

Risk Premia Arbitrage

Intra-country Systems

Market Spreads

Inter-country Systems

FX

Bond VS Bond

Stock VS Stock


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Identification of

common signals for

all pairs

Derive direction

and confidence of

investment views

for all pairs

Portfolio construction:

Tactical trades

implemented via

futures contracts

Derive expected

returns for all

assets through

Bayesian blending

Signals Pairwise Views Blending Portfolio Construction

Within each sub-system Across all sub-systems Portfolio Implementation

Investment ProcessInvestment Procedure Outline


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All recommended strategies of the qCIO Model are based on expected excess returns derivedfrom blending investment views of five independent sub-systems designed for different assetclasses and markets; the weights of the views are determined by their relative statisticalconfidence as well as their dynamic correlations.

qCIOsBlending

Model

Stock-Stock

sub-system

Foreign Exch.

sub-system

Bond-Bond

sub-system

Cash-Bond

sub-system

Bond-Stock

sub-system

Expected Excess

Returns and Risks

Strategies

Investment ProcessInvestment Procedure Outline

SignalsPairwise

Views

Portfolio

Constru.Blending


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Common Signals And ReturnsDiversification Across Signals Of Different Nature

Across Asset Classes Example (bond versus cash): 7 markets 7 iterations of the model

US Bonds vs. US cash, Japanese Bonds vs Japanese Cash, etc.

At each iteration, the dependent variable is defined as the excess return of bonds over

cash, hedged into CHF

The explanatory variables correspond to the signal associated with the country under

consideration

A dynamic constant is included, corresponding to a risk premium

Within Asset Classes Example (equity versus equity): 9 markets: Consider each possible pair 36 iterations

Japan vs. US, EU vs. US, EU vs. JP, UK vs. Japan, etc.

The dependent variable is the excess returns of the two stock markets considered

(relative to cash), hedged into CHF

The explanatory variables correspond to the difference in signals between 2 markets Example: Yield Gap for Japan vs. US = YG(USA)-YG(Japan)

No constant (premium) is included as there is no rationale as to why stock markets

should outperform one another

SignalsPairwise

Views

Portfolio

Constru.Blending


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Investment ProcessTypology of Signals

SignalsPairwise

Views

Portfolio

Constru.Blending


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Each pair of assets is considered in turn

The expected excess return of the pair of assets is the dependent

variable

Hindsight biases are minimized by assuming that all signals work

equally and moderately well at inception

The relative importance of each signal is determined by Bayesian

adaptive regression according to its consistency to performance

Direction and confidence of investment views are both expressed

as expected relative return and standard error

Pairwise ViewsSequential Derivation of Direction and Confidence

of Investment Views for Each Sub-System

SignalsPairwise

Views

Portfolio

Constru.Blending


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FX Sub-System: Current Signal Ranks (1 = Best)

USD JPY EUR GBP CHF CAD AUD

Risk-adjusted Carry 5 6 2 4 7 3 1

Yield Trend 7 1 6 5 2 3 4

Flows 1 4 7 3 6 2 5

Growth 7 1 5 4 6 3 2

GDP Revisions 2 4 7 5 1 6 3

Technicals 1.5 4.5 4.5 6 7 3 1.5

Composite 4 4 5 6 6 2 1

FX Sub-System: Last Week's Signal RanksUSD JPY EUR GBP CHF CAD AUD

Risk-adjusted Carry 5 6 2 4 7 3 1

Yield Trend 7 1 6 5 2 3 4

Flows 1 3 4 2 7 5 6

Growth 6 1 5 2 7 4 3

GDP Revisions 2 4 7 5 1 6 3

Technicals 2 3 5 4 1 6 7

Composite 4 2 5 4 1 6 6

FX Sub-System: Signals' Weights

USD JPY EUR GBP CHF CAD AUD

Risk-adjusted Carry 22% 11% 14% 12% 11% 15% 20%

Yield Trend 15% 12% 12% 8% 12% 9% 11%

Flows 5% 8% 8% 10% 7% 10% 10%

Growth 4% 7% 5% 4% 6% 6% 6%

GDP Revisions 2% 8% 6% 7% 7% 7% 4%

Technicals 53% 53% 55% 58% 56% 52% 49%

FX Signals Contribution By TypeSignals Ranking By Current Relative Explanatory Power

SignalsPairwise

Views

Portfolio

Constru.Blending


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Positive (negative) signals recommend long (short) duration

Bond-Cash Sub-System: Signals on scale from -5 to +5

US Jap Eur UK Aus Can Swi

Value -3.4 -1.3 -4.7 -4.0 -2.3 -3.8 -3.3

Growth +3.4 +3.4 +2.0 +2.9 +2.8 +2.5 -0.4

Risk -2.7 -1.2 -2.4 -2.5 -4.1 -3.1 -3.4

Yield Dynamics +2.3 +0.6 +4.0 +3.9 +3.7 +3.0 +4.1

Composite Bond-Cash +2.6 +3.2 +2.4 +3.7 +4.1 +2.7 +3.3

Bond-Cash Sub-System: Signals' change from last monthUS Jap Eur UK Aus Can Swi

Value -2.3 +2.1 -2.0 -0.2 -1.7 +0.6 -1.5

Growth -0.4 -0.2 -0.9 -0.6 -0.7 -0.5 -1.4

Risk -0.5 +0.2 -1.1 -0.7 -1.6 -0.4 -1.2

Yield Dynamics +4.6 +0.6 +4.9 +6.0 +4.8 +4.6 +2.7

Composite Bond-Cash +0.3 +0.9 +0.2 +1.2 +1.5 +1.0 +0.6

Bond-Cash Sub-System: Signals' weights


Value 55% 40% 43% 23% 0% 54% 10%

Growth 31% 24% 38% 57% 48% 36% 48%

Risk 0% 9% 0% 0% 3% 0% 0%

Yield Dynamics 15% 27% 19% 20% 50% 10% 42%

Cash-Bond Signals Contrib. By TypeSignals Ranking By Current Relative Explanatory Power

SignalsPairwise

Views

Portfolio

Constru.Blending


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Bond-Bond Sub-System: Current Signal Ranks (1 = Best)


Yield Dynamics 1 6 5 2 4 3 7

Value 3 1 6 7 4 2 5

Composite Bond-Bond 2 1 6 5 4 3 7

Bond-Bond Sub-System: Last Month's Signal Ranks


Yield Dynamics 1 6 5 2 4 3 7

Value 6 1 3 4 5 2 7

Composite Bond-Bond 1 6 4 2 5 3 7

SignalsPairwise

Views

Portfolio

Constru.Blending

Bond-Bond Signals Contrib. By TypeSignals Ranking By Current Relative Explanatory Power


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Stock-Bond Sub-System: Signals on scale from -5 to +5


Value +2.0 +3.7 +2.8 +2.2 +3.0 +1.1 +2.9

Business Cycles +3.4 +2.7 +3.0 +2.7 +3.7 +3.1 +3.7

Composite Stock-Bond -0.9 +1.2 +0.9 -0.1 -1.1 -0.7 -3.4

Stock-Bond Sub-System: Signals' Change from Last Month


Value +1.1 -0.0 +1.3 +1.0 +2.3 +1.7 +0.9

Business Cycles +0.1 +0.1 -0.0 -0.0 +0.1 -0.0 +0.0

Composite Stock-Bond +1.1 -0.4 +1.8 +0.8 -0.1 +0.8 -0.5

Stock-Bond Sub-System: Signals' Confidence Level (1 = "Normal")


Value 2.4 0.3 1.1 2.7 0.3 1.0 0.5Business Cycles 0.0 0.0 0.0 0.0 0.0 0.0 0.0

SignalsPairwise

Views

Portfolio

Constru.Blending

Bond-Stock Signals Contrib. By TypeSignals Ranking By Current Relative Explanatory Power

Positive (negative) signals recommend to overweight (underweight) Stocks against Bonds


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Stock-Stock Sub-System: Current Signal Ranks (1 = Best)

US Jap Eur UK Aus Can Swi HK EMF

Value 6 8 1 2 9 7 4 3 5

Momentum 4 9 5 2 2 6 7 2 8

Implied Volatility 6 9 2 1 5 8 7 4 3

Energy Prices 9 3 7 6 4 5 8 1 2

Business Cycles 5 7 6 8 4 8 3 1 3

Composite Stock-Stock 5 9 4 2 6 7 8 1 3

Stock-Stock Sub-System: Last Month's Signal Ranks


Value 6 8 2 1 9 7 4 3 5

Momentum 3.5 9 5 1 2 6 7.5 3.5 7.5

Implied Volatility 6 9 2 1 5 8 6 5 3

Energy Prices 9 3 7 6 4 5 8 1 2

Business Cycles 4 7 6 8 5 8 3 1 3Composite Stock-Stock 4 9 3 2 7 7 8 1 3

SignalsPairwise

Views

Portfolio

Constru.Blending

Stock-Stock Signals Contrib. By TypeSignals Ranking By Current Relative Explanatory Power


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* All bond markets and all stock market except Hong Kong and Emerging Markets are currency-hedged into US dollars

Pairwise ViewsExpected Excess Returns over USD Cash

SignalsPairwise

Views

Portfolio

Constru.Blending

-10%

-5%

0%

5%

10%

15%

20%

United

States

Japan Eurozone United

Kingdom

Australia Canada SwitzerlandHong Kong Emerging

Markets

Stocks Bonds FX vs USD


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qCIO is based on the sequential analysis of all expected returns

and standard error of all asset pairs for each sub-system

qCIO is designed so as to ensure an optimal and robust dynamic

modeling of all pairs of assets considered by utilizing advanced

Bayesian methodologies

For each of the five sub-systems, we obtain:

The expected excess return for every pair of assets

The expected risk for every pair of assets

The evolution of the weights for each signal

In total 92 pairs of assets are systematically dynamically modeled

and analyzed

Pairwise ViewsProcess

SignalsPairwise

Views

Portfolio

Constru.Blending


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BlendingAggregation and Apportioning of Views

Stock-Bond System

US Stocks vs BondsJapan Stocks vs Bonds

Eurozone Stocks vs Bonds

etc

Bond-Bond System

US vs Japan

US vs Eurozone

Japan vs Eurozone

etc.

Bond-Cash System

US Bonds vs Cash

Japan Bonds vs Cash

Euro Bonds vs Cash

etc.

Stock-Stock System

US vs Japan

US vs Eurozone

Japan vs Eurozone

etc.

Currency System

USD vs JPY

USD vs EUR

EUR vs JPY

etc.

Blending

Expected Returns

and Standard Errors

SignalsPairwise

Views

Portfolio

Constru.Blending


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c

b

S

Bonds

Stocks

e

e

e

CashE

RE

RE

+=

-

-

%75.0

%5.0

%1

)(

)(

)(

001

110

011 Stocks outperform bonds by 1%

Bonds outperform cash by 0.5%

Stocks will generate a 0.75% return

P E(ret) = V + e S=diag(cov(e))

Bayesian blending mechanism to obtain expected returns based on:

Prior expectations: Excess returns are set to 0 in the absence of views, their

covariance is estimated historically using exponential decay

Views: Expected excess returns obtained from the Bayesian regression

Confidence of the views

The expected returns can be interpreted as a weighted average of the

equilibrium prior and the tactical views. The weights are determined by

the relative confidence that we have in the views and the risk of the

assets

Expression of the pairwise views:


SignalsPairwise

Views

Portfolio

Constru.Blending


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The conditional expected returns of each asset class is expressed as:

E(R) = [ ( t W )-1 + PT S-1 P ] -1 . [ ( t W )-1P+ PT S-1 V ] With:

P the vector of equilibrium returns (set to 0) W the covariance of returns (based on historical data)

P the matrix of views

S the covariance of the views

t a calibration factor (set to 0.02, no consensus on its value in the literature)

Limiting cases: P=0: No views BL returns= Equilibrium returns (0) Inv(S): No forecast error BL returns = Views


SignalsPairwise

Views

Portfolio

Constru.Blending


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The expected excess return of each asset is influenced by views inall five sub-systems. Some of these influences are not surprising: The expected returns of stocks are heavily influenced by views in the stock-

stock and stock-bond sub-systems

The expected returns of bonds are heavily influenced by views in the bond-bond and bond-cash sub-systems

The expected returns of currencies are heavily influenced by views in the FXsub-system

But because of correlation among assets, a sub-system can influence theexpected return of assets that are not directly involved in its own views.For example:

The stock-stock sub-system is contributing to higher expected returns for allcurrencies against the US dollar. This is because the stock-stock sub-systemexpects the US stock market to out-perform European stock markets incurrency-hedged terms, and this is associated with a weaker dollar.

SignalsPairwise

Views

Portfolio

Constru.Blending

Blending: Systems InterdependenceExcess Returns Are Derived From Every Sub-Systems


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Sub-Systems' contributions to expected excess returns of stock markets over cash, % p.a.


FX Sub-System -0.3% -1.5% -1.2% 0.4% 1.2% 0.4% -2.0% -0.7% -0.3%

Bond-Cash Sub-System 1.7% 0.5% 2.1% 2.0% 2.0% 1.6% 1.7% 2.7% 1.7%

Bond-Bond Sub-System 1.1% -0.1% -0.5% -0.3% 0.4% 0.7% -0.3% 0.3% 0.5%

Stock-Bond Sub-System -1.0% -0.1% -0.4% -0.5% -0.8% -0.8% -1.6% -1.0% -0.7%

Stock-Stock Sub-System 1.0% -7.5% 1.5% 2.9% -0.1% -0.2% -0.2% 8.2% 4.7%

Expected Stock Excess Return 2.5% -8.6% 1.5% 4.4% 2.8% 1.7% -2.4% 9.6% 5.8%

* All stock markets except HK & EMF are currency-hedged into US dollars

Sub-Systems' contributions to expected excess returns of bond markets over cash, % p.a.US Jap Eur UK Aus Can Swi

FX Sub-System 0.1% 1.4% 0.1% 0.5% 0.0% -0.1% -0.1%

Bond-Cash Sub-System 1.8% 1.6% 1.8% 2.0% 2.0% 1.9% 1.4%

Bond-Bond Sub-System 1.2% 1.2% -0.5% -0.1% 0.2% 0.9% -1.1%

Stock-Bond Sub-System 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.1%

Stock-Stock Sub-System 0.5% 0.4% 0.6% 0.8% 0.4% 0.5% 0.3%

Expected Bond Excess Return 3.6% 4.6% 1.9% 3.1% 2.6% 3.1% 0.6%

* All bond markets are currency-hedged into US dollars

Sub-Systems' contributions to expected excess returns of currencies over USD, % p.a.

JPY EUR GBP AUD CAD CHF

FX Sub-System 15.9% 7.4% 5.4% 6.5% -2.1% 11.5%

Bond-Cash Sub-System 0.2% - 0.1% -0.1% 0.0% 0.1% 0.2%

Bond-Bond Sub-System 0.4% 0.1% 0.5% 0.2% 0.1% 0.5%

Stock-Bond Sub-System 0.1% 0.1% 0.0% 0.0% 0.0% 0.1%

Stock-Stock Sub-System 0.6% 0.0% -0.2% -0.1% 0.2% 0.2%

Expected Currency Excess Return 17.2% 7.6% 5.6% 6.6% -1.7% 12.5%

Blending: Systems InterdependenceExcess Returns Are Derived From Every Sub-Systems

SignalsPairwise

Views

Portfolio

Constru.Blending


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Portfolio Construction

Model Tradeoff between return and risk is made

The objective function is to maximize single-period expected

return subject to tracking error target

Flexible control of turnover can be achieved by means of atransaction penalty parameter (factor is highest in the first half of

the month), and other methods

Round-trip transaction costs assumptions are 12 bp, 4 bp, and 8

bp for stocks, bonds and FX

Portfolios with different objectives and constraints are

constructed using the same set of expected return, ensuring

information consistency

SignalsPairwise

Views

Portfolio

Constru.Blending


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Portfolio BacktestsUnrestricted Global Macro Program

The unrestricted program is the most accurate reflection of the models views.

Where a benchmark is present, no short-selling or leverage is permitted.

SignalsPairwise

Views

Portfolio

Constru.Blending

qCIO targeting 3.5% Tracking Error

Stocks Bonds FX Stocks Bonds FX

United States -0.6% 11.5% -6.1% 0.0% 0.0% 0.0%

Japan -1.1% -1.7% 13.2% 0.0% 0.0% 0.0%

Eurozone 3.2% -2.3% -27.1% 0.0% 0.0% 0.0%

United Kingdom 2.0% -5.0% 3.1% 0.0% 0.0% 0.0%

Austral ia -2.0% 1.8% 11.2% 0.0% 0.0% 0.0%

Canada -1.7% 2.2% -15.5% 0.0% 0.0% 0.0%

Switzerland -2.0% 1.6% 21.2% 0.0% 0.0%

Hong Kong 0.8% 0.0%

Emerging Markets 1.3% 0.0%

Net -0.1% 8.0% 0.0% 0.0%

Expected Information Ratio Confidence

Current 2.32 Very high

Five-year average 1.96 High

Average

Low

Very low

Unrestricted Bets Bets vs Benchmark


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Q M S Advisors Av de la Gare 1 | 1003 Lausanne CH | tel: 078 922 08 77 | e-mail: info@qmsadv com | website: www qmsadv com

MonthlyAlpha - Unrestricted Global Macro Program

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Portfolio BacktestsUnrestricted Global Macro Program

SignalsPairwise

Views

Portfolio

Constru.Blending

1.14Information Ratio =

3.20%Tracking Error =

3.64%Annual Alpha =

Past 15 years

The unrestricted program is the most accurate reflection of the models views.

Where a benchmark is present, no short-selling or leverage is permitted.

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