Smart Beta Investing in the year of the monkey · 2016-02-23 · 4 Monkey see, monkey do Exploring recent literature Arnott, Hsu Kalesnik and Tindall1 (2013) designed an experiment

February 2016

Smart Beta Investingin the year of the monkey

Presentation only intended for professional investors as defined by MIFID.

Non contractual document.

2

Contents

Factor investing Section 1

Factor investing – portfolio implications Section 2

Rebalancing – a factor? Section 3

Conclusion Section 4

Non contractual document

3

Malkiel’s Monkey Who’s a clever boy? The efficient market hypothesis is characterised by Burton Malkiel in his acclaimed 1973 book ‘A Random Walk Down

Wall Street’:

“A blindfolded monkey throwing darts at a newspaper’s financial pages could select a portfolio that would do just as

well as one carefully selected by experts.”

This idea has been furthered by Nassim Taleb in ‘Fooled by Randomness’:

‘Just as one day some primitive tribesman scratched his nose, saw rain falling, and developed an elaborate method of

scratching his nose to bring on the much-needed rain, we link economic prosperity to some rate cut by the Federal

Reserve Board or the success of a company with the appointment of the new president “at the helm.”’

According to both authors and a larger body of work by Robert Shiller in the 1980s, markets are ‘noisy’. In the short term,

prices fluctuate, but this fluctuation is not predictable.

Morningstar released a report showing that more than three-quarters of active managers lagged the equal weighted

composite of their passive peers during the ten year period to 20141

What does this result mean for investors?

– Growth of passive investing: ETFs, Index funds now nearly 15% of global AUM and increasing

– Preference for the certainty of holding the market

1Source: Morningstar ‘Morningstar’s Active/Passive Barometer’ June 2015 [http://corporate.morningstar.com/US/documents/ResearchPapers/MorningstarActive-PassiveBarometerJune2015.pdf


4

Monkey see, monkey do Exploring recent literature

Arnott, Hsu Kalesnik and Tindall1 (2013) designed an experiment to simulate the monkey’s picking stocks:

– 100 portfolios were randomly selected, each containing 30 stocks from a universe of 100 (equally-weighted)

– Each year a new set of 30 stocks was chosen, from 1964 to 2010

Results:

– 96 out of the 100 portfolios outperformed the cap weighted benchmark

– The average outperformance is 160bps

Why?

– Systematic rebalancing of a portfolio may add excess return

– Value, Size and volatility tilts incorporated into the ‘monkey’s’ portfolios create factor biases – Or to look at it another way, momentum and large-cap bias exists in the market cap index

– Academically this idea was explored in the early 1990s by Fama-French in their factor models

This is backed up by a further study from Clare, Motson and Thomas (2013)2 who conclude:

‘Our results show that between 1968 and 2011 the fundamental index alternatives that we consider have out-performed a

comparable index constructed on the basis of the market capitalisation of the index constituents, in risk-adjusted terms. We find

that this superior risk-adjusted performance cannot be attributed easily to luck’

Factors may therefore add value when compared to a market capitalisation index

1Source: Arnott, Hsu, Kalesnik, and Tindall ‘The Surprising Alpha From Malkiel’s Monkey and Upside-Down Strategies’ The Journal of Portfolio Management Summer 2013 2Source: Clare, Motson and Thomas ‘An evaluation of alternative equity indices Part 2: Fundamental weighting schemes’ Cass Consulting March 2013


5

Capturing Equity Beta Alpha-Beta divide

– Gradually the existence

of robust premiums and

excess volatility have

become commonly

accepted

– Alternative weighting

schemes address two

main concerns:

Implicit factor biases

Concentration without

rebalancing

Source: HSBC Global Asset

Management, 30 September 2015 For illustrative purposes only.

Pro

sp

ecti

ve r

etu

rns

Alternative Weighting

Strategies

β β

Cap-Weighted Beta Active Fundamental

Stock Selection

β

α

Factor exposure

(explicit)

Factor exposure

(explicit) Factor exposure

(implicit)


6

MOMENTUM

LARGE CAP

GROWTH

β

Potential uses for Alternating Weighting Schemes

Options for asset owners

– Fulfilment options to diversify the passive allocation

– Factor indices allow clients to diversify their passive allocations.

Cap-weighted strategies have inherent style tilts due to their

construction, and can become driven by a small number of stocks

or sectors

– Completion options to compliment active exposures

– Active portfolios will exhibit particular exposures representative of

the chosen investment style of styles. Pure factor strategies can

complement the systematic risk in these portfolios

Cap-weighted

indices perform

best when these

factors are in

favour

β +

QU

AL

ITY

LO

W R

ISK

MO

ME

NT

UM

SIZ

E

INC

OM

E

HE

SI

RE

BA

LA

NC

ING

VA

LU

E

Source: HSBC Global Asset Management, 31 December 2015.

How might rebalancing be seen a distinct ‘factor’ to take advantage of when assessed in the prism of fundamental indexing/ investing?


Options for asset allocators (SAA/TAA)

– Combinations of factor indices can deliver tailored

strategic systematic exposure to portfolios (SAA)

– The indices also allow managers to tactically allocate to

factor exposures in a cost-effective way (TAA)

1. Factor Investing

8

Building Factor Indices Creating an index which represents a “pure” exposure

Source: HSBC Global Asset Management. For illustrative purposes only.

Bespoke

Solutions

Market Neutral Long/Short

Factor

Pure Single Factor Indices

High Exposure Factor Indices

Broad (High Capacity) Factor Indices

Market Cap Weighted Benchmark Index

We aim to implement the factor signals in an index where we

deliver an index exposed to a desired factor while minimising

exposure to other factors - combining efficiency, transparency

and robustness

Hunstad and Dekhayser (2014) – Evaluating the Efficiency of ‘Smart Beta’ Indexes, Working Paper

Goldberg, Leshem and Geddes (2013) – Restoring Value to Minimum Variance, Forthcoming in

Journal of Investment Management

Sig

na

l P

urity

bu

t m

ore

Com

ple

xity

Factor Indices ‘Pyramid’ Pure Factor Portfolios

Our Objective

For illustrative purposes only

PURE

Precise

Efficient

Robust

Unbiased

Single target factor

Clear Ex – post Return Attribution

Clear Ex – ante Risk Decomposition Factor Efficiency Ratio

risk from desired factor

unwanted risks =


9

-1

-0.5

0

0.5

1

Jun-03 Jun-04 Jun-05 Jun-06 Jun-07 Jun-08 Jun-09 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15

Pure Value-Momentum Index Raw Value-Momentum Index

Value

(Pure)

Size

(Pure)

Momentum

(Pure)

Low Risk

(Pure)

Quality

(Pure)

Fundamental

Index (HESI)

Value (Pure) 0.4 (0.0)A (0.2) 0.2 0.4

Size (Pure) 0.7 0.1 0.3 0.1 0.2

Momentum

(Pure) (0.1)A 0.2 0.3 (0.0) (0.4)

Low Risk (Pure) (0.3) (0.1) 0.4 0.1 (0.2)

Quality (Pure) 0.4 0.6 0.3 0.1 (0.0)

Fundamental

Index (HESI) 0.5 0.2 (0.2) (0.2) 0.1

Pure Factor Indices: Backtests Lower correlation at excess return level

Style neutrality translates

into lower correlations

among factor excess returns

“Pure” factor portfolios

represent more

“independent” sources of

returns and risk

– A popular factor blending

approach is to combine

value and momentum.

However, in extreme

circumstances, these

correlations can break

down

– The raw momentum –

value line clearly shows

that correlations are time

varying and not static as

is often suggested

– For ‘pure factor indices’

the 2 year historic

correlation between

value and momentum

shows far greater

consistency

Source: HSBC Global Asset Management.

FactSet, Worldscope, IBES, Bloomberg

Correlations have been calculated using monthly excess total returns against MSCI World Index in USD from 31/07/2001 – 31/12/2015. Trading costs of approximately 20bps have

been assumed in the simulations. Simulated data is shown for illustrative purposes only, and should not be relied on as indication for future returns. Simulations are based on Back

Testing assuming that the optimization models and rules in place today are applied to historical data. As with any mathematical model that calculates results from inputs, results may

vary significantly according to the values inputted. Prospective investors should understand the assumptions and evaluate whether they are appropriate for their purposes. Some

relevant events or conditions may not have been considered in the assumptions. Actual events or conditions may differ materially from assumptions.

Graph: Correlations have been calculated using daily excess against MSCI World Index total returns (2 years rolling) in USD from 04/06/2003 – 30/12/2015. Trading costs of

approximately 20bps have been assumed in the simulations.

Average “raw” pairwise correlation ~ 20%

2 Year rolling correlation between Value and Momentum

A

Average “pure” pairwise correlation ~ 10%

Correlation Matrix of excess returns


10

Pure Factor Indices: Clarity of expected outcomes Factor Efficiency

Raw momentum exhibits significant bias to small caps and

high volatility stocks. This unintended exposure could prove

problematic for performance and risk.

Our efficient momentum index is by construction immunised

from such exposure

‘Pure’ momentum eliminated most of unintended exposures

to other sources of risk at the cost of having less exposure to

the raw momentum factor

It is possible that the ‘pure’ momentum index could be

generating less returns. However it is much less subject to

unexpected shocks from unknown sources

Conventional Momentum Index

Pure Momentum Index

Source: HSBC Global Asset Management FactSet, Worldscope, IBES, Bloomberg. Data period LHS graphs 31/07/2001- 31/12/2015, RHS graph as of 31/12/2015.

Simulated data is shown for illustrative purposes only, and should not be relied on as indication for future returns. Simulations are based on Back Testing assuming that the optimisation models and rules in

place today are applied to historical data. As with any mathematical model that calculates results from inputs, results may vary significantly according to the values inputted. Prospective investors should

understand the assumptions and evaluate whether they are appropriate for their purposes. Some relevant events or conditions may not have been considered in the assumptions. Actual events or conditions

may differ materially from assumptions.

Example of pure momentum Active Factor Exposures

Factors efficiency ratios

(2.0)

(1.5)

(1.0)

(0.5)

0.0

0.5

1.0

1.5

2.0

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

(1.0)

(0.5)

0.0

0.5

1.0

VALUE VOLATILITY

MOMENTUM PROFITABILITY

SIZE LEVERAGE

0.0

0.5

1.0

1.5

2.0

Momentum Quality Value Low Volatility

HBCS's Pure Indices MSCI


11

Clarity of expected outcomes Clear attribution

Source: HSBC Global Asset Management, FactSet, Worldscope, IBES, Bloomberg, MSCI , Thomson Reuters

Data : portfolio/benchmark weights for 09/2014 to 12/2015. Simulated data is shown for illustrative purposes only, and should not be relied on as indication for

future returns. Simulations are based on Back Testing assuming that the optimisation models and rules in place today are applied to historical data. As with

any mathematical model that calculates results from inputs, results may vary significantly according to the values inputted. Prospective investors should

understand the assumptions and evaluate whether they are appropriate for their purposes. Some relevant events or conditions may not have been considered

in the assumptions. Actual events or conditions may differ materially from assumptions.

Total Active Return(vs MXWO) Decomposition

Portfolio 1: Relative Performance -1.94%

Total Active Return(vs MXWO) Decomposition

Portfolio 2: Relative Performance -3.07%

-1.20%

-0.80%

-0.40%

0.00%

0.40%

VA

LUE

PR

OFI

TAB

ILIT

Y

TRADING.ACTIVI…

SIZE

GR

OW

TH

EARNINGS.VARI…

LEV

ERA

GE

VO

LATI

LITY

MO

MEN

TUM

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

3.00%

4.00%

Mar

ket

Styl

e

Co

un

trie

s

Ind

ust

rie

s

Cu

rre

nci

es

Re

sid

ual

CTR

to T

R

-3.00%-2.00%-1.00%0.00%1.00%2.00%3.00%4.00%

Mar

ket

Styl

e

Co

un

trie

s

Ind

ust

rie

s

Cu

rre

nci

es

Re

sid

ual

-1.20%

-0.80%

-0.40%

0.00%

0.40%

VA

LUE

PR

OFI

TAB

ILIT

Y

TRADING.ACTIVI…

SIZE

GR

OW

TH

EARNINGS.VARI…

LEV

ERA

GE

VO

LATI

LITY

MO

MEN

TUM

CTR

to S

tyle

Return Sources ?

Typically investors are most

concerned when an

alternative weighting scheme

underperforms the

capitalisation weighted index

In the example below we

show a 15m period where

the value factor

underperformed on a relative

basis. One might expect that

main source of return will be

the targeted factor but this is

not always the case

Portfolio 1: Pure Value Index

Portfolio 2: MSCI Enhanced

Value Index

‘Pure factor’ index avoided

contamination from other

styles which could have led

to further underperformance


2. Factor Investing – Portfolio implications

13

-0.4 -0.2 0 0.2 0.4 0.6

VALUE

VOLATILITY

MOMENTUM

PROFITABILITY

SIZE

-0.3 -0.1 0.1 0.3 0.5

-0.4 -0.2 0 0.2 0.4 0.6

VALUE

VOLATILITY

MOMENTUM

PROFITABILITY

SIZE

-0.3 -0.1 0.1 0.3 0.5

Client solutions - Completion Fine tuning active exposures with pure factor indices

Building portfolios with a bottom-up approach can sometimes

result in a collection of securities that exhibit unwanted factor

exposures

Portfolio 1 on the right, is value-oriented and negatively

exposed to momentum

Using our pure momentum factor index, we are able to

mitigate the unwanted exposure to momentum directly

without contaminating the portfolio’s original feature at the

most efficient and cost-effective way

Completion portfolio = portfolio 1 + pure momentum index

Portfolio 1 with undesirable Momentum tilt -Active

factor exposures (vs MXEF)

Portfolio 2 with tilt correction – adding 10% Mom

tilt - Active factor exposures (vs MXEF)

Note: MXEF is the MSCI EM Index. Source: HSBC Global Asset Management, FactSet, Worldscope, IBES, Bloomberg

Performance has been calculated using monthly total returns in USD from 31/08/2007 – 30/04/2015. Trading costs of approximately 20bps have been assumed in the simulations.





Unbold

Clarity

What’s MXEF

(MSCI Emerging Market Index)?

Cum

ula

tive R

etu

rns

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0

Aug-0

7

Dec-0

7

Apr-

08

Aug-0

8

Dec-0

8

Apr-

09

Aug-0

9

Dec-0

9

Apr-

10

Aug-1

0

Dec-1

0

Apr-

11

Aug-1

1

Dec-1

1

Apr-

12

Aug-1

2

Dec-1

2

Apr-

13

Aug-1

3

Dec-1

3

Apr-

14

Aug-1

4

Dec-1

4

Apr-

15

Portfolio 1 + Momentum Tilt Portfolio 1

Case study: Completing a value-oriented portfolio

Performance


14

(0.4) (0.2) 0.0 0.2 0.4

VALUE

VOLATILITY

MOMENTUM

PROFITABILITY

SIZE

0.0

0.5

1.0

1.5

Information Ratio: MXWO

Defensive Balanced Dynamic

A Dynamic blend would target more cyclical

factors with the highest expected returns –

this gives higher expected returns

Defensive Scenario: 33% value, 33% quality and 33% low vol

Balanced Scenario: 20% value, 20% momentum, 20% quality, 20% size and 20% low vol

Dynamic Scenario: 33% value, 33% momentum and 33% size

Client solutions – Fulfilment Targeting core factor combinations to achieve outcomes

A Defensive blend would use the more

defensive factors – minimises expected

volatility

A Balanced blend would use all available

drivers of excess returns – improves expected

sharpe ratio


Data period: 31/07/2001 – 31/12/2015. Graphs (LHS) shows average factor exposures and graphs (RHS) shows annualised performance information.

Simulated data is shown for illustrative purposes only, and should not be relied on as indication for future returns. Simulations are based on Back Testing assuming that the optimisation models and rules in place today are applied to

historical data. As with any mathematical model that calculates results from inputs, results may vary significantly according to the values inputted. Prospective investors should understand the assumptions and evaluate whether they are

appropriate for their purposes. Some relevant events or conditions may not have been considered in the assumptions. Actual events or conditions may differ materially from assumptions.

(0.4) (0.2) 0.0 0.2 0.4

VALUE

VOLATILITY

MOMENTUM

PROFITABILITY

SIZE

0.0%

1.0%

2.0%

3.0%

Tracking Error: MXWO

Defensive Balanced Dynamic

(0.6) (0.4) (0.2) 0.0 0.2 0.4

VALUE

VOLATILITY

MOMENTUM

PROFITABILITY

SIZE

0.0%

1.0%

2.0%

3.0%

Active Premium: MXWODefensive Balanced Dynamic


15

Client solutions – Diversification Combining factors to create diversification benefit

Simulation: Asia Pacific Multi-Factor

For the purpose of illustration; we constructed an

equally-weighted factor portfolio with exposure to

value, quality and low risk to demonstrate the

performance relative to the MSCI Asia Pacific Index

We noted the portfolio

– outperformed the benchmark on a long term

basis;

– produced a higher information ratio;

– provided the exposure to three factors in one

portfolio which offers the diversification

through out the business cycles

Source: HSBC Global Asset Management For Illustration purposes only.

Performance have been calculated using monthly gross returns in USD from 31/08/2007 – 30/10/2015.

Data shown is gross and the effect of commission, fees and other charges will reduce the overall return





0%

20%

40%

60%

80%

100%

120%

May

-01

Jan

-02

Sep

-02

May

-03

Jan

-04

Sep

-04

May

-05

Jan

-06

Sep

-06

May

-07

Jan

-08

Sep

-08

May

-09

Jan

-10

Sep

-10

May

-11

Jan

-12

Sep

-12

May

-13

Jan

-14

Sep

-14

May

-15

Cum

ula

tive R

etu

rns

Excess

-100%

-50%

0%

50%

100%

150%

200%

250%

300%

350%

400%

May

-01

Jan

-02

Sep

-02

May

-03

Jan

-04

Sep

-04

May

-05

Jan

-06

Sep

-06

May

-07

Jan

-08

Sep

-08

May

-09

Jan

-10

Sep

-10

May

-11

Jan

-12

Sep

-12

May

-13

Jan

-14

Sep

-14

May

-15

Cum

ula

tive R

etu

rns

Portfolio Benchmark

Cumulative Returns

Excess Returns


3. Rebalancing – a factor?

26

11

0 –

AM

G5

16

21

a

17

Source: HSBC Global Asset Management

For illustrative purposes only.

Rebalancing can enable a portfolio to add value Alternative Weighting Strategies

Pure play on rebalancing

Tempered factor exposures

Take advantage of ‘noisy’ prices

Capture the equity risk premium and use rebalancing to harvest short-term pricing errors in

equity markets

Investment

objective:


26

11

0 –

AM

G5

16

21

a

18

Index methodology comparison HSBC Economic Scale Indexation

Source: HSBC Global Asset Management. For illustrative purposes only.

Diversification does not protect against a loss in a particular market. There is no guarantee that any investment strategy will work under all market conditions. Investing involves risk including the possible loss

of principal.

HSBC ESI Emerging Markets FTSE RAFI Emerging Markets MSCI Value Weighted

Weighting basis Contribution to GNP

Average of weights

Sales

Dividend

Cash Flow

Book Value

Average of weights

Sales

Cash Earnings

Earnings

Book Value

Index constituents

Screen stocks for information

availability, liquidity, availability

and size to enable full

replication

~ 850 names

Use FTSE Emerging Market

universe (953 stocks) elect

companies with the top 350

fundamental scores

~ 361 names

Uses MSCI Emerging Market

stock universe Index has

~ 838 stocks

Rebalance

frequency Twice yearly Annually Twice yearly


26

11

0 –

AM

G5

16

21

a

19

Index data prior to 15 June 2012 is back-tested (simulated) data calculated by the independent calculation agent, Euromoney Indices. Data subsequent to the Index launch date has been calculated daily by

Euromoney Indices. Past performance and back-tested (simulated) data are not a reliable indication of future returns. Back-tested performance results have many inherent limitations and were

achieved with the benefit of hindsight by means of a retrospective application of the HSBC Economic Scale Index rules-based methodology to determine the appropriate weightings. The results do not

represent the results of actual trading using client assets and as such do not include any dealing costs that may be incurred by funds tracking an index. No representation is being made that the Index will or

is likely to achieve results similar to those shown. In fact, there are frequently sharp differences between back tested performance results and actual results subsequently achieved. The data is supplemental

to the GIPS® compliant presentation at the end of this material.

Source: Datastream, data (using weekly total returns in GBP with gross dividends re-invested) from 4th July 2001 to 28 October 2015.

Fundamental indexing is not simply an alternative way of obtaining exposures to systematic factors

that have historically contributed to outperformance

In the case of fundamental indexation, there is a tempered exposure to value and small cap factors,

but these are small in comparison to the strategy’s alpha

Fundamental Indexation Tempered style exposures – Supplemental Information

Index Out-

performance 'Alpha' Market beta

Small-cap

beta Value beta Tracking error

1 HSBC ESI Worldwide 1.77% 1.21% 1 0.24 0.26 2.69%

2 HSBC ESI Emerging

Markets 3.68% 3.47% 0.98 0.05 0.3 3.69%

3 HSBC ESI World 1.48% 1.02% 1 0.21 0.26 2.74%

The proprietary HSBC Economic Scale indices can generate alpha through harnessing rebalancing and taking

advantage of equity price inefficiency


26

11

0 –

AM

G5

16

21

a

20

Based on performance back tests that assume no trading costs or fees. Weekly data for the period 29 December 2005 to 31 December 2015. Simulated data calculated by the Euromoney Indices Team

based on weekly total returns in GBP. Simulated performance should not be seen as an indication of future returns . HSBC Economic Scale Index data prior to 15 June 2012 is back tested (simulated)

data calculated by the independent calculation agent, Euromoney. Data subsequent to the Index launch date has been calculated daily by Euromoney. The data is supplemental to the GIPS® compliant

presentation at the end of this material. Past performance and back tested (simulated) data are not a reliable indication of future returns. Back tested performance results have many inherent limitations

and were achieved with the benefit of hindsight by means of a retrospective application of the HSBC Economic Scale index rules based methodology to determine the appropriate weightings. The results

do not represent the results of actual trading using client assets and as such do not include any dealing costs that may be incurred by funds tracking an Index. No representation is being made that the

Index will or is likely to achieve results similar to those shown. In fact, there are frequently sharp differences between back tested performance results and actual results subsequently achieved.

Emerging Markets performance – Supplemental Information HSBC Economic Scale Indexation

Value of GBP100 invested in HSBC ESI Emerging Markets versus RAFI and equivalent MSCI index over the last 10 years

Return p.a. (%) Excess return p.a.

(%) Volatility p.a. (%) Sharpe ratio

MSCI Emerging Markets 5.56% 20.91% 0.17

HSBC ESI Emerging Markets 7.97% 2.28% 20.39% 0.29

FTSE RAFI Emerging Markets 5.63% 0.06% 21.64% 0.17

0

50

100

150

200

250

300

350

De

c 0

5

Ap

r 0

6

Au

g 0

6

De

c 0

6

Ap

r 0

7

Au

g 0

7

De

c 0

7

Ap

r 0

8

Au

g 0

8

De

c 0

8

Ap

r 0

9

Au

g 0

9

De

c 0

9

Ap

r 1

0

Au

g 1

0

De

c 1

0

Ap

r 1

1

Au

g 1

1

De

c 1

1

Ap

r 1

2

Au

g 1

2

De

c 1

2

Ap

r 1

3

Au

g 1

3

De

c 1

3

Ap

r 1

4

Au

g 1

4

De

c 1

4

Ap

r 1

5

Au

g 1

5

De

c 1

5

HSBC ESI Emerging Markets MSCI Emerging Markets FTSE RAFI Emerging Markets


26

11

0 –

AM

G5

16

21

a

21

Source: Euromoney, Datastream, HSBC Global Asset Management

For Emerging Markets: Analysis based on weekly gross total returns from 11 July 2007 to 25 June 2014. For Worldwide: Analysis based on weekly gross total returns from 5 October 2005 to 25 June

2014. Index data prior to June 2012 is back tested (simulated) data calculated by the independent calculation agent, the Euromoney Indices team. Data subsequent to the Index launch date has been

calculated daily by Euromoney. Past performance and back tested (simulated) data are not a reliable indication of future returns. Back tested performance results have many inherent limitations and were

achieved with the benefit of hindsight by means of a retrospective application of the HSBC Economic Scale index rules based methodology to determine the appropriate weightings. The results do not

represent the results of actual trading using client assets and as such do not include any dealing costs that may be incurred by funds tracking an Index. No representation is being made that the Index will

or is likely to achieve results similar to those shown. In fact, there are frequently sharp differences between back tested performance results and actual results subsequently achieved. The data is

supplemental to the GIPS® compliant presentation at the end of this material.

HSBC Economic Scale Indexation Stable and tempered factor exposures relative to FTSE RAFI – Supplemental Information

Worldwide Emerging Markets

Value Beta against value (Rolling 3yr regression) Value Beta against value (Rolling 3yr regression)

Size Beta against size (Rolling 3yr regression)

Beta Beta against the market (Rolling 3yr regression)

Size Beta against size (Rolling 3yr regression)

Beta Beta against the market (Rolling 3yr regression)

0.0

0.2

0.4

0.6

0.8

1.0

Oct-08 Sep-09 Aug-10 Aug-11 Jul-12 Jul-13 Jun-14

Beta

FTSE RAFI All World 3000 HSBC ESI Worldwide

0.0

0.1

0.2

0.3

0.4

0.5

0.6


Beta


0.95

1.00

1.05

1.10


Beta


0.2

0.3

0.4

0.5

Jul-10 Jul-11 Jun-12 Jun-13 Jun-14

Beta

FTSE RAFI Emerging Markets HSBC ESI Emerging Markets

(0.3)

(0.2)

(0.1)

0.0

0.1

0.2


Beta


0.95

1.00

1.05


Beta



4. Conclusion

23

Capturing Equity Beta Capabilities: Key strategy building blocks

Note:

1. To be launched (Pure factors)

For illustrative purposes only.

Worldwide

World

Europe

Europe ex UK

UK

US

Canada

Japan

Emerging

Markets – BRIC

Asia Pacific ex

Japan – China

– Korea

– Taiwan

– Malaysia

– Indonesia

Russia

Turkey

South Africa

Latin America

Brazil

Mexico

Real Estate

Full suite of

geographic

constructs

Global

Regional

Country

Portfolio

construction

strategies

Core

Income

Small cap

Real estate

Thematic

Full suite of

geographic

constructs

Global

Regional

Country

Full suite of

geographic

constructs

Global

Regional

Country

Cap-Weighted

Beta

Active Fundamental

Stock Selection Fundamental Lower Volatility Multi-Factor Pure Factor Beta

Full suite of

geographic

constructs

Global

Regional

Country

Customisable to

client investment

universe,

constraints and

risk requirements

Full suite of

geographic

constructs

Global

Regional

Country

Pure Factors1

– Value

– Quality

– Small Cap

– Momentum

– Low volatility

Traditional

Alpha

Traditional

Beta Bespoke Solutions


24

Conclusion

Factor indices/ strategies represent a highly accessible and efficient way of investing in

factor premia through passive vehicles

Combining factors can smooth performance, but should be done with clarity and control

– Individual factor returns can be cyclical and underperform the market

Rebalancing can be seen as either a component part of a smart beta strategy or

potentially a factor in its own right

Factors can be seen either as tactical allocation tools (fulfilment), complimentary

portfolio allocation or an opportunity for portfolio diversification


Any reference to performance information refers to the past and should not be seen as an indication of future returns. Any forecast, projection or target contained in this presentation is for information

purposes only and is not guaranteed in any way. HSBC accepts no liability for any failure to meet such forecasts, projections or targets.


25

Important information

This presentation is distributed by HSBC Global Asset Management (France) and is only intended for professional investors as defined by MiFID.

It is incomplete without the oral briefing provided by the representatives of HSBC Global Asset Management (France). The information contained herein is subject to change without notice. All

non-authorised reproduction or use of this commentary and analysis will be the responsibility of the user and will be likely to lead to legal proceedings. This document has no contractual value

and is not by any means intended as a solicitation, nor a recommendation for the purchase or sale of any financial instrument in any jurisdiction in which such an offer is not lawful. The

commentary and analysis presented in this document reflect the opinion of HSBC Global Asset Management on the markets, according to the information available to date. They do not

constitute any kind of commitment from HSBC Global Asset Management (France). Consequently, HSBC Global Asset Management (France) will not be held responsible for any investment or

disinvestment decision taken on the basis of the commentary and/or analysis in this document. All data come from HSBC Global Asset Management unless otherwise specified. Any third party

information has been obtained from sources we believe to be reliable, but which we have not independently verified. Any forecast, projection or target where provided is indicative only and is not

guaranteed in any way. HSBC Global Asset Management (France) accepts no liability for any failure to meet such forecast, projection or target.

The fund presented in this document may not be registered and/or authorised for sale in your country. The performance figures displayed in the document relate to the past and past

performance should not be seen as an indication of future returns. It is important to remember that the value of investments and any income from them can go down as well as up and is not

guaranteed. Please note that the fund is authorised to invest a in structured products and derivatives, which may be less liquid than standard bond issues. The fund is exposed to Over the

Counter (OTC) markets for all or part of its total assets. The fund will therefore be subject to the risk that its direct counterparty will not perform its obligations under the OTC transactions and

that the Sub-Fund will sustain losses. Investment in Financial Derivative Instruments (FDI) may result in losses in excess of the amount invested. This is because a small movement in the price

of the underlying financial instrument may result in a substantial movement in the price of the FDI. Please note that the fund is invested in investment grade, below investment grade and non

rated issues. Non rated issues represent a higher risk of default compared to Investment Grade issues. Fluctuations in the rate of exchange of currencies may have a significant impact on fund

performance. Please note that according to article 314-13 of AMF General Regulation, performance for periods of less than 12 months cannot be shown to non-professional investors, as defined

by MiFID.

Important information for Luxembourg investors: HSBC entities in Luxembourg are regulated and authorised by the Commission de Surveillance du Secteur Financier (CSSF).

Important information for Swiss investors: This document may be distributed in Switzerland only to qualified investors according to Art. 10 para 3, 3bis and 3ter of the Federal Collective

Investment Schemes Act (CISA). The presented fund is authorised for public distribution in Switzerland in the meaning of Art. 120 of the Federal Collective Investment Schemes Act. (Potential)

investors are kindly asked to consult the latest issued Key Investor Information Document (KIID), prospectus, articles of incorporation and the (semi-)annual report of the fund which may be

obtained free of charge at the head office of the representative: HSBC Global Asset Management (Switzerland) Ltd., Bederstrasse 49, P.O. Box, CH-8002 Zurich. Paying agent: HSBC Private

Bank (Suisse) S.A., Quai des Bergues 9-17, P. O. Box 2888, CH-1211 Geneva 1. Investors and potential investors should read and note the risk warnings in the prospectus and relevant KIID.

Before subscription, investors should refer to the prospectus for general risk factors and to the KIID for specific risk factors associated with this fund. Issue and redemption expenses are not

taken into consideration in the calculation of performance data. The fund presented in this document is a sub-fund of HSBC Global Investment Funds, an investment company constituted as a

société à capital variable domiciled in Luxemburg.

HSBC Global Asset Management is the brand name for the asset management business of HSBC Group. The above document has been approved for distribution/issue by the following entity:

HSBC Global Asset Management (France) - 421 345 489 RCS Nanterre. Portfolio management company authorised by the French regulatory authority AMF (no. GP99026) with capital of

8.050.320 euros.

Postal address: 75419 Paris cedex 08, France.

Offices: HSBC Global Asset Management (France) - Immeuble Coeur Défense - 110, esplanade du Général Charles de Gaulle - 92400 Courbevoie - La Défense 4 – France. (Website:

www.assetmanagement.hsbc.com/fr).

HSBC Global Asset Management (Switzerland) Limited

Bederstrasse 49, P.O. Box, CH-8027 Zurich, Switzerland (Website: www.assetmanagement.hsbc.com/ch)

Copyright © 2016. HSBC Global Asset Management (France). All rights reserved.

Non contractual document, updated in February 2016 / AMFR_Ext_079_2016


http://www.assetmanagement.hsbc.com/fr

http://www.assetmanagement.hsbc.com/ch

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