Nomura Securities International, Inc. U.S. Quantitative ... · U.S. Quantitative Research Bacteria vs Dinosaurs • Bacteria are, and always have been, the dominant forms of life

U.S. Quantitative Research

Nomura Securities International, Inc.U.S. Quantitative Research

Nomura Global Quantitative Equity Conference in London

Natural SelectionNatural Selection

Joseph Mezrich Please read the analyst certifications and important di l 27 29 l

17 May 2011

Nomura Securities International Inc, New York.Global Quantitative Research

disclosures on pp. 27-29. gl


Bacteria vs Dinosaurs

• Bacteria are, and always have been, the dominant forms of life on Earth.

• The fossil record of life begins with bacteria.

• Bacteria exist in overwhelming number and unparalleled variety.

• Bacteria inhabit effectively every place suitable for the existence of life.y y p

• Should quantitative investors emulate dinosaurs or bacteria?

2Joseph Mezrich, 212.667.9316, [email protected]


Do quants have ‘dinosaur’ risk?

How do bacteria diversify? Local adaptation to changing environments

Local adaptation = optimizing to a specific (local) objective function



Outline Examples of structural change in popular factors –Examples of structural change in popular factors

sources of ‘dinosaur’ risk

Selection for different objectives – examples of adaptive investing

• Factor momentum and the success of quants – dinosaurs?

• Low factor volatility and high factor momentum

Risk parity for strategy combination• Risk parity for strategy combination

• Alpha repair – yet another adaptive strategy



“Regime change” for factors: Example 1 …Regime change for factors: Example 1 …

350

400

250

300

350

etur

n (%

)

Up-to-down Revisions

100

150

200

lati

ve fa

ctor

re

0

50

100

Cum

u

EBITDA/EV

N t Sh l ti thl t t t d i i d EBITDA/EV i R ll 1000 i F t t

-50

1979

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Notes: Shows cumulative monthly returns to up-to-down revisions and EBITDA/EV in Russell 1000 universe. Factor returns are based on equal-weighted decile spread returns. Analysis ranges from January 1979 through April 2011. Transaction costs are not considered.Source: Nomura Securities International Inc. , Russell. I/B/E/S, Compustat, IDC.


… Example 2: Accruals still work for high-estimate-dispersion stocks

250

300High estimate dispersion stocksMid estimate dispersion stocksLow estimate dispersion stocks

… Example 2: Accruals still work for high estimate dispersion stocks

200

n to

Acc

rual

(%

)

p

Recession

100

150

umul

ativ

e re

turn

Regulation FD

0

50

8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0

Cu

Regulation FD

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Note: Universe is Russell 3000. Shows cumulative monthly returns to accruals (equally weighted quintile spread) in each of threegroups categorized by level of dispersion of analyst estimates for current-year earnings (deflated by the absolute value of meanestimate). Accruals are based on Sloan’s (1996) definition using three-month change in trailing four-quarter average in financial statements not using 12-month change in annual financial statements as Sloan originally used Period of analysis is from January


statements, not using 12-month change in annual financial statements as Sloan originally used. Period of analysis is from January 1989 through March 2011. Transaction costs are not considered.Source: Nomura Securities International Inc., Compustat, IDC, Russell, I/B/E/S, NBER.


… Example 3: B/P has moved from low beta to no betaa p e 3 / as o ed o o beta to o beta

0 5

0.6B/P- Estimate dispersion

0.2

0.3

0.4

0.5

elat

ion

p

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-0.1

0

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Rank

Cor

r

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B/P-Beta

Note: Shows cross-sectional rank correlations between B/P and beta, and between B/P and estimate dispersion in the Russell 1000 universe. Period of analysis is from July 1984 through February 2011. Source: Nomura Securities International Inc., Russell, Compustat, IDC, I/B/E/S.



Factor momentum – selection based on return persistence


Notes: Shows monthly factors (factors are non-sector neutral) selected using the highest factor momentum strategy (60-month) in the Russell 1000. At each point of time, there are three selected factors. The factor labels are sorted according to frequency of selection, with highest frequency at the bottom. Period of analysis are from January 1984 to March 2011.Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell and IDC


Quant core funds beat fundamental core funds in Q1 2011

Quant vs. Fundamental

Q f d

6

8

%)

+4 bp in YTDQuant core funds

2

4

mul

ativ

e al

pha

(

+151 bp in YTD

0

2

Cu

Dec 2010Fundamental core funds

Notes: Shows cumulative average alpha (relative return to the benchmark) in large-cap core funds based on quantitativemethodologies (dark blue line) and large-cap core funds based on fundamental methodologies (light blue line). Currently, 16

-2

2003 2004 2005 2006 2007 2008 2009 2010 2011


g ( ) g p g ( g ) yquant core funds and 48 fundamental core funds are in each fund universe. Transaction costs are not considered. Period ofanalysis is from January 2003 through April 2011.Source: Nomura Securities International Inc., Bloomberg, Russell, S&P.


Factor momentum fuels quant core funds

35

408 Cu

Quant fund alpha and factor momentum

Quant core funds

20

25

30

4

6

mulative return ot

core

fund

s (%

)

Aug 2007

0

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10

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of 5yr factor momve

alp

ha o

f qua

n

Five year factor momentum

gQuant meltdown

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0

-2

0

mentum

(%)

Cum

ulat

i

Aug 2010Five-year factor momentum

Notes: Shows cumulative average alpha (relative return to the benchmark) of quant core funds (dark blue line) together withcumulative return of five-year factor momentum strategy, where the best five factors (long/short baskets) are owned as long-short positions among our 52 factors based on five-year factor performances in the Russell 1000 universe. Currently, 16 quantcore funds are in the fund universe. Transaction costs are not considered. Period of analysis is from January 2003 through

2003 2004 2005 2006 2007 2008 2009 2010 2011


core funds are in the fund universe. Transaction costs are not considered. Period of analysis is from January 2003 throughMarch 2011.Source: Nomura Securities International Inc., Bloomberg, Compustat, I/B/E/S, Russell, S&P and IDC.


Factor momentum historically fuels quant core funds

140

160y

(%)

Quant fund alpha and factor momentum

Five-year factor momentum (best 5 factors from 52 factors)

5

10

100

120

140 Cumulative alph

men

tum

str

ateg

y (best 5 factors from 52 factors)

Five-year factor momentum (best 10 factors from 52 factors)

Quant core funds

-5

0

40

60

80

ha of Quant Core

urn

of f

acto

r m

om Aug 2007Quant meltdown

-15

-10

-20

0

20

funds (%)

Cum

ulat

ive

retu

Notes: Shows cumulative average excess return of quant core funds relative to their benchmark (dark blue line) together withcumulative return of five-year factor momentum strategy, where the best five factors (light blue line) or the best 10 factors (dark blueline) are owned as long-short positions among our 52 factors based on five-year factor performances in Russell 1000 universe.C l 16 f d i h f d i T i id d P i d f l i i f J

1520

1989

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2011


Currently, 16 quant core funds are in the fund universe. Transaction costs are not considered. Period of analysis is from January1989 through March 2011.Source: Nomura Securities International Inc., Bloomberg, Compustat, I/B/E/S, Russell, S&P and IDC.


Alpha similarities in quant and fundamental core investmentsAlpha similarities in quant and fundamental core investments

0.7Alpha correlation in quant and fundamental core funds

0.5

0.6

elat

ion

Aug 2007Quant meltdown

Quant core funds

0.3

0.4

-yea

r alp

ha c

orre

Fundamental core funds

0.1

0.2

Thre

e-

Notes: Shows three-year alpha correlation in quant core funds (dark blue line) and fundamental core funds (light blue line),where the average of all pairwise alpha correlations are calculated within each fund group. Currently, 16 quant core funds and48 fundamental core funds are in each fund universe Period of analysis is from January 2000 through April 2011

0

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


48 fundamental core funds are in each fund universe. Period of analysis is from January 2000 through April 2011.Source: Nomura Securities International Inc., Bloomberg, Russell, S&P.


Factor momentum fuels quant value and growth funds

Quant growth fund alpha and growth-style factor momentum

q g

20

Quant value fund alpha and value-style factor momentum

15

20

25

30

35

10

12

14

16

Cumulative return g

row

th fu

nds

(%)

Growth-style factor momentum

25

30

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40

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Cumulative return

nt v

alue

fun

ds (

%) Value-style factor momentum

-10

-5

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8

n of factor mom

entum

ulat

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alph

a of

Qua

nt


Quant growth funds10

15

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25

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n of factor mom

entum

mul

ativ

e al

pha

of Q

uan

Quant value fundsAug 2007

Quant meltdown

-20

-15

-2

0

2004 2005 2006 2007 2008 2009 2010 2011

m (%

)Cum

uNotes: Left chart shows cumulative average alpha (relative return to the benchmark) of quant value funds (dark blue line) together with cumulative return of five-year value-

0

5

0

2

2004 2005 2006 2007 2008 2009 2010 2011

m (%

)Cum

g p ( ) q ( ) g ystyle factor momentum strategy, where the best five factors are owned as long-short positions among our 34 value-style factors (value, earnings variability, GARP, andothers categories) based on five-year factor performances in Russell 1000. Right chart shows cumulative average alpha (relative return to the benchmark) of quant growthfunds (dark blue line) together with cumulative return of five-year growth-style factor momentum strategy, where the best five factors are owned as long-short positionsamong our 37 growth-style factors (growth, earnings sustainability [flipped polarity for earnings variability], GARP, and others categories) based on five-year factorperformances in Russell 1000. Transaction costs are not considered. Period of analysis is from January 2003 through 20 April 2011.Source: Nomura Securities International Inc., Bloomberg, Compustat, I/B/E/S, Russell, S&P and IDC.



Alpha diversification among quant styles

16

18Alphas in Quant Core, Value and Growth funds

Quant Core funds

10

12

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16

nt f

unds

(%

)

Q

Quant Growth funds

Quant Value funds

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e al

pha

of q

uan

-2

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4

Cum

ulat

ive


Notes: Shows cumulative median alpha (relative return to the benchmark) in large-cap core, value, and growth funds based on

-4

2004 2005 2006 2007 2008 2009 2010 2011


quantitative methodologies. Currently, 16 quant core funds, 6 quant value funds, and 10 quant growth funds are in each funduniverse. Transaction costs are not considered. Period of analysis is from January 2003 through 20 April 2011.Source: Nomura Securities International Inc., Bloomberg, Russell, S&P.


Mood for quants is getting better?

Not only useful for alpha opportunities, quant strategies can provide diversification withdiversification with fundamental investments.

15Source: Pensions & Investments.


Outline : Examples of structural change in popular factors –

sources of ‘dinosaur’ risk

Selection for different objectives – examples of adaptive investing

• Factor momentum and the success of quants – dinosaurs?

• Low factor volatility and high factor momentum

• Risk parity for strategy combination

• Alpha repair – yet another adaptive strategy



Combinatorics – a cheap approach to factor discoveryCombinatorics a cheap approach to factor discovery

20,000

12,000

16,000bi

nati

ons

4,000

8,000

Com

b

0

3 10 20 30 40 50

Number of factors

Notes: Shows number of combinations to select three factors from a different number of factors.Source: Nomura Securities International Inc.



Return to low-volatility factor selection strategy

120

140

80

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120

thly

ret

urns

, %

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60

Cum

ulat

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mon

t

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Note: Shows cumulative monthly returns to a strategy of selecting three factors out of 45 factors with the lowest last-one-year return volatilities. Universe isthe Russell 1000. Period of analysis is from January 1980 through end September 2010. Transaction costs are not considered. Past performance shouldnot and cannot be viewed as an indicator of future performance.Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell, and IDC.



Three strategies f t t (b t t ) l l tilit d bi tiThree strategies: factor momentum (best returns), low volatility, and combination

300

low volatilities Best Returns combined

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hly

ret

urn

s, %

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mu

lati

ve m

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Note: Shows monthly cumulative returns (top chart) and summary (bottom chart) of three strategies: (1) selecting three factors out of 45 with the lowest

low volatility best return combinedAnnualized Return 4.16 8.61 6.39Annualized Volatility 4.88 11.36 6.20Annualized IR 0.85 0.76 1.03


y ( p ) y ( ) g ( ) g12-month return volatilities, blue line; (2) selecting three factors out of 45 with the best 12-month returns, red line; and 3) investing equally in strategies (1) and (2). Universe is the Russell 1000. Period of analysis is from January 1980 through end September 2010. Factors are constructed sector-neutral. Transaction costs are not considered. Past performance cannot and should not be viewed as indicative of future performance. Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell, and IDC.


What gets selected using the low-volatility strategyg g y gy


Note: Shows monthly factors (sector-neutral) selected using the lowest volatility strategy in the Russell 1000. At each point to time, there are three selectedfactors. The factor labels are sorted according to frequency of selection, with highest frequency at the bottom. Period of analysis is from January 1980through September 2010.Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell, and IDC.


What gets selected using the factor-momentum strategyat gets se ected us g t e acto o e tu st ategy


Note: Shows monthly factors (sector-neutral) selected using the highest factor momentum strategy in the Russell 1000. At each point to time, there are threeselected factors. The factor labels are sorted according to frequency of selection, with highest frequency at the bottom. Period of analysis is from January1980 through September 2010.Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell, and IDC.


Priced and priceless —plow-volatility and factor-momentum strategies select different types

of factors

68%

77%

%

80%

90%

nfactor momentum low vol

32%40%

50%

60%

70%

ncy

of

sele

ctio

n

32%

23%

0%

10%

20%

30%

Fre

qu

en

Note: Shows frequency of price-related factor and non-price-related factor selection in (1) low-volatility strategy and (2) highest factor-momentum

0%

Non-Price factors Price factors


Note: Shows frequency of price related factor and non price related factor selection in (1) low volatility strategy and (2) highest factor momentum strategy. Period of analysis is from January 1980 through September 2010. Universe is the Russell 1000.Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell, and IDC.


Combining strategiesCombining strategies

180

200

220

Factor Momentum

Minimum Variance

Equal Weighted

120

140

160

y R

etur

ns, %

Risk Parity (unlevered)

Risk Parity (levered 1.5X)

80

100

120

Cum

ulat

ive

Mon

thl

20

40

60C

Note: Shows monthly cumulative returns of five strategies: (1) selecting three factors out of 45 with 60-month minimum variance, purple line; (2) selecting three factors out of 45 with the best 60 month returns red line; 3) investing equally in strategies (1) and (2) blue line; 4)

0

Nov

-88

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(2) selecting three factors out of 45 with the best 60-month returns, red line; 3) investing equally in strategies (1) and (2), blue line; 4) investing in (1) and (2) based on equal risk contribution, green line; 5) 1.5 times leveraged strategy (4), black line. Universe is the Russell 1000. Factors are built non-sector neutral. Period of analysis is from December 1988 through November 2010. Transaction costs are not considered. Past performance cannot and should not be viewed as indicative of future performance. Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell, and IDC.


Combining strategies via dynamic risk parity weightsCombining strategies via dynamic risk parity weights

Weighted according to Risk Parity (FM: factor momentum; MV: minimum variance)1= 11 + = + = 1

Or write the weights in another way= + = +

Strategy Allocations

min variance (60 m)

best return (60 m) Equal Weighted

Risk Parity Weighting

Risk Parity Weighting (1.5X Levered)

Annualized Return 4.64 7.77 6.21 5.77 8.65Annualized Volatility 6.18 17.78 9.05 6.27 9.41

Note: Shows summaries of five strategies: (1) selecting three factors out of 45 with 60-month minimum variance, purple line; (2) selecting three factors out of 45 with the best 60-month returns, red line; 3) investing equally in strategies (1) and (2), blue line; 4) investing in (1) and (2) based on equal risk contribution, green line; 5) 1.5 times leveraged strategy (4), black line. Universe is the Russell 1000. Factors are built non-sector neutral. Period of analysis is from Dec 1988 through November 2010. Transaction costs are not considered. Past performance cannot and should not be viewed as indicative of future performance

Annualized IR 0.75 0.44 0.69 0.92 0.92


cannot and should not be viewed as indicative of future performance. Source: Nomura Securities International Inc., Compustat, I/B/E/S, Russell, and IDC.


Alpha Repair – adaptive selection p p p

40

50

60

rns,

%

regression line

US 11.7% absolute return YTD 2011 Outperformed Russell 1000

10

20

30um

ulat

ive

Exce

ss R

etu

Model public

22 Jan 2007,US Alpha Repairmodel published

p81bps in April, 2011and 2.6% YTD 2011annualized outperformance:3.5% since 2007, model public3.3% past 5 yrs4.1% past 10 yrs

-10

0

Jan-

97

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Cu model published

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(%)_

60

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retu

rn o

ver N

OM

UR

A 4

00 (

Model public

Regression line

JapanOutperformed NOMURA 40056 bp in April 20111.7 % in YTD 2011annualized outperformance:10.4 % since 2008, model public

0

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40ec

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ss

12 Sep 2008,Japan Alpha Repairmodel published

9.8 % past 5 yrs9.7% past 10 yrs

25

Notes: Shows cumulative monthly excess returns of Alpha Repair portfolios for U.S. and Japan. Past model performance should not and cannot be viewed as indicative of future performance; complete details available upon request. Transaction costs are not considered.Source: Nomura Securities International Inc., Compustat, I/B/E/S, IDC, Russell.

De Ju De Ju De Ju De Ju De Ju De Ju De Ju De Ju De Ju De Ju De Ju De


Alpha Repair – uncorrelated with other quant fundsp p q

0.6Alpha correlation in quant core funds and US alpha repair

Aug 2007

0.3

0.4

0.5

lati

on

Quant meltdownWithin Quant core funds

0.1

0.2

0.3

year

alp

ha c

orre

Between US alpha repair and Quant core funds

-0.2

-0.1

0

Thre

e-y

Notes: Shows three-year alpha correlation in quant core funds (dark blue line) and alpha correlation between quant core fundsand US alpha repair (red line), where the average of all pairwise alpha correlations are calculated in quant core funds.

-0.3

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

26

p p ( ) g p p qCurrently, 16 quant core funds and 48 fundamental core funds are in each fund universe. Period of analysis is from January2000 through April 2011.Source: Nomura Securities International Inc., Russell, S&P, Compustat, I/B/E/S, IDC, Bloomberg.


Any Authors named on this report are Research Analysts unless otherwise indicatedy p y

Analyst CertificationI, Joseph Mezrich, hereby certify (1) that the views expressed in this Research report accurately reflect my personal views about any or all of the subject securities or issuers referred to in this Research report, (2) no part of my compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this Research report and (3) no part of my compensation is tied to any specific investment banking transactions performed by Nomura Securities International, Inc., Nomura International plc or any other Nomura Group company.

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