September 15, 2008: A Market Analysis By Anthony Renshaw, PhD Director, Applied Research September 17, 2008 © Copyright, Axioma, Inc. 2008 - All rights reserved Introduction

September 15, 2008 was a difficult day for Wall Street, as major announcements concerning AIG,

Lehman Brothers, and Merrill Lynch triggered the worst market sell-off since the first day of

trading after the September 11, 2001 terrorist attacks.

This short article analyzes the market situation using Axioma US fundamental risk model. In

addition to identifying the factors that drove Monday’s returns, the results highlight recent

changes in market conditions that may be important to portfolio managers.

Key findings include:

• The standard factor return for Leverage on 9/15 was -9.93, a value of extraordinary

magnitude. All but one industry suffered negative standard factor returns on this day,

several with values less than -5.0.

• The two style factors with the most negative recent cumulative factor returns –

Leverage and Medium-term Momentum – have also experienced significant changes in

their recent correlations with the other style factors. The style factor with the largest

recent cumulative factor return – Liquidity – has experienced relatively stable

correlations with other style factors.

• Although the overall level of market turnover on 9/16/08 is similar to that of 8/8/2007,

so far market turnover does not exhibit the same level of factor dependence as it did in

August 2007 when quantitative managers experienced far more difficulties than other

portfolio managers.

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Daily Factor Return Analysis

Figure 1 shows the cumulative factor returns for Axioma’s nine, US style risk factors from July

31, 2008 through the close of September 16, 2008. The two, most negative returns are for

Leverage and Medium-term Momentum. The only factor with a significant positive return over

this time period is Liquidity. Several other factors have also experienced negative factor returns,

namely Volatility, Short-term Momentum, and Size.

Figure 1. Cumulative factor returns for Axioma’s nine, US style risk factors.

The magnitude of the sell-off on September 15 is most easily illustrated using standardized factor

returns1. Figure 2 shows the standard factor returns for Axioma’s nine, US style risk factors.

Figure 2. Standard daily factor returns for Axioma’s nine, US style risk factors.

The standard factor return for Leverage on 9/15 was -9.93, a factor return that dwarfs all the other

returns on the chart. Several other factors also had significant standard factor returns: Short- 1 Standard factor returns are daily factors returns normalized by subtracting off the mean and dividing by the standard deviation. We used the previous 750 trading days to define the mean and standard deviation for each factor.

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term Momentum (+3.01), and Volatility (-4.27). On 9/16, the largest factor return was Liquidity

(+4.43).

Table 1 below lists the standard factor returns for the Industry factors for 9/15. The only industry

with a positive return was Airlines (+0.41). All others were negative, significantly so, starting

with Wireless Telecommunication Services (-5.40).

Industry

Std. Daily

Factor

Return Industry

Std. Daily

Factor Return

Wireless Telecommunication Services -5.40 Health Care Equipment & Supplies -3.58

Construction & Engineering -5.33 Multi-Utilities -3.55

Independent Power Producers & Energy Traders -5.21 Chemicals -3.53

Diversified Telecommunication Services -5.19 Electric Utilities -3.50

Oil, Gas & Consumable Fuels -5.08 Food Products -3.45

Gas Utilities -4.94 Health Care Providers & Services -3.33

Diversified Financial Services -4.68 Water Utilities -3.28

Computers & Peripherals -4.47 Automobiles -3.27

Beverages -4.41 Marine -3.14

IT Services -4.29 Machinery -3.06

Real Estate Investment Trusts (REITs) -4.15 Household Durables -2.92

Insurance -4.14 Auto Components -2.89

Consumer Finance -4.14 Paper & Forest Products -2.86

Media -4.07 Biotechnology -2.74

Trading Companies & Distributors -3.96 Office Electronics -2.71

Real Estate Management & Development -3.95 Transportation Infrastructure -2.60

Life Sciences Tools & Services -3.94 Tobacco -2.26

Metals & Mining -3.92 Internet Software & Services -2.18

Energy Equipment & Services -3.88 Thrifts & Mortgage Finance -2.12

Pharmaceuticals -3.85 Semiconductors & Semiconductor Equipment -1.98

Electrical Equipment -3.85 Textiles, Apparel & Luxury Goods -1.90

Household Products -3.79 Multiline Retail -1.79

Commercial Services & Supplies -3.74 Road & Rail -1.62

Building Products -3.72 Specialty Retail -1.54

Communications Equipment -3.71 Construction Materials -1.50

Industrial Conglomerates -3.66 Air Freight & Logistics -1.41

Capital Markets -3.64 Diversified Consumer Services -1.26

Health Care Technology -3.62 Distributors -1.14

Food & Staples Retailing -3.62 Hotels Restaurants & Leisure -1.13

Commercial Banks -3.61 Personal Products -0.92

Containers & Packaging -3.61 Leisure Equipment & Products -0.82

Software -3.60 Internet & Catalog Retail -0.33

Electronic Equipment & Instruments -3.59 Airlines 0.41

Aerospace & Defense -3.58 Table 1. Standard daily factor returns on 9/15/08 for the 67 GICS industries.

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Changes in Factor-Factor Correlations

Table 2 illustrates how the correlations between the nine style factors have changed recently.

The factor-factor correlations predicted by Axioma US risk model were averaged over two time

windows: 9/17/07 to 7/31/08 and 7/31/08 to 9/16/08. These are shown in the table, together with

a column giving the difference in correlations, with the factor-factor pairs sorted by the

differences.

Factor 1 Factor 2

Average Risk

Model Correlation

9/17/07 to 7/31/08

Average Risk

Model Correlation

7/31/08 to 9/16/08

Correlation

Difference

Medium-Term Momentum Market Sensitivity 0.028 -0.251 -0.279

Medium-Term Momentum Size 0.297 0.062 -0.235

Medium-Term Momentum Growth 0.298 0.071 -0.227

Medium-Term Momentum Value -0.008 -0.231 -0.223

Short-Term Momentum Market Sensitivity -0.053 -0.204 -0.152

Growth Value 0.200 0.112 -0.088

Liquidity Leverage 0.094 0.009 -0.085

Size Growth 0.245 0.166 -0.079

Short-Term Momentum Growth -0.111 -0.188 -0.077

Volatility Short-Term Momentum -0.111 -0.168 -0.057

Medium-Term Momentum Leverage -0.189 -0.244 -0.055

Short-Term Momentum Leverage -0.004 -0.053 -0.049

Short-Term Momentum Liquidity -0.185 -0.221 -0.036

Volatility Market Sensitivity 0.635 0.605 -0.030

Volatility Medium-Term Momentum -0.013 -0.037 -0.023

Short-Term Momentum Value -0.276 -0.284 -0.008

Short-Term Momentum Size 0.108 0.103 -0.004

Liquidity Value 0.017 0.018 0.001

Market Sensitivity Size 0.185 0.187 0.002

Volatility Liquidity 0.239 0.244 0.005

Volatility Size 0.322 0.329 0.007

Medium-Term Momentum Liquidity -0.364 -0.357 0.008

Volatility Growth 0.157 0.169 0.012

Volatility Value 0.019 0.037 0.017

Liquidity Growth -0.041 -0.022 0.019

Market Sensitivity Growth 0.130 0.169 0.039

Liquidity Size -0.291 -0.249 0.042

Growth Leverage -0.102 -0.035 0.067

Volatility Leverage 0.262 0.342 0.080

Liquidity Market Sensitivity 0.136 0.233 0.097

Size Value 0.039 0.152 0.113

Market Sensitivity Leverage 0.239 0.367 0.128

Leverage Value -0.164 -0.005 0.158

Medium-Term Momentum Short-Term Momentum 0.089 0.282 0.193

Market Sensitivity Value -0.099 0.123 0.222

Size Leverage 0.042 0.284 0.242

Table 2. Recent changes in Style factor-factor correlations. Factor pairs with either Medium-term Momentum or Leverage have been highlighted.

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Several of these changes may be of significance to portfolio managers. The four correlations with

the most, negative changes all involve Medium-term Momentum, as does the third most positive

correlation. This indicates that the behavior of Medium-term Momentum over the last month and

a half has been significantly different than in the preceding year. This is supported by the

cumulative factor returns shown in Fig. 1. Note that the correlations differences in these cases are

as great as or greater than the current correlation.

Not surprisingly, the other factor with significant changes has been Leverage, which is in three of

the top five correlation changes.

Market Turnover

Recent research by Axioma has shown that market events are often associated with factor-

dependent changes in market turnover where market turnover is defined as an asset’s daily

volume divided by its market capitalization.2 In particular, the events of last August 2007 when

many quantitative portfolio managers significantly underperformed the market were shown to be

strongly linked to an increase in market turnover as a function of an asset’s exposure to style risk

factors.

For the events of 9/15 and 9/16, there does not appear to be any strong factor related increase in

market turnover although market turnover did increase overall on 9/16 for several factors to

levels commensurate with those of last August. This raises the possibility of a future, factor-

dependent liquidity event. Figs. 3 - 7 show market turnover as a function of exposure to

Leverage, Medium-term Momentum, Value, Market Sensitivity, and Volatility. Figure 8 shows

market turnover as a function of the ten GICS sectors. Overall, there are no systematic trends like

those experienced last August apart from the increased market turnover on 9/16.

2 “Recent Market Turnover and Risk Factor Exposure,” by A. A. Renshaw, in Axioma Advisor, August 2008. Available at www.axiomainc.com.

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Figure 3. Market turnover (%) as a function of Leverage exposure.

Figure 4. Market turnover (%) as a function of Medium-term Momentum exposure.

Figure 5. Market turnover (%) as a function of Value exposure.

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Figure 6. Market turnover (%) as a function of Market Sensitivity exposure.

Figure 7. Market turnover (%) as a function of Volatility exposure.

Figure 8. Market turnover (%) as a function of the ten GICS sectors.