The performance of information

The Performance of Information
Thesis to complete the post-graduate program Treasury Management at the VU
June 9, 2009
By drs. G.Ph. Wielenga
Mentor Prof. Dr. Ir. H. Rijken

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Contents
1 Management Summary______________________________________________________ 3
2 Introduction_______________________________________________________________ 5
3 Methodology ______________________________________________________________ 7
3.1 Mathematical expression of the hypotheses _______________________________________ 7
3.2 Δ performance_______________________________________________________________ 7
3.3 Δ risk disclosure _____________________________________________________________ 8
3.4 Selection of the companies _____________________________________________________ 9
3.5 Testing the data: the steps taken _______________________________________________ 10
4 Results __________________________________________________________________ 11
4.1 The correlation between Δ performance and Δ risk disclosure ______________________ 11
4.2 The correlation between the stability of Δ performance and Δ risk disclosure__________ 13
5 Analysis and conclusions ___________________________________________________ 15
5.1 General____________________________________________________________________ 15
5.2 Risk disclosure, managing expectations? ________________________________________ 16
5.3 Risk disclosure, stabilizing results?_____________________________________________ 16
5.4 Risk disclosure, useful to investors? ____________________________________________ 16
5.5 Summary of conclusions______________________________________________________ 17
6 Discussing conclusions with a professional_____________________________________ 18
7 Data / Literature __________________________________________________________ 19
Acknowledgments _____________________________________________________________ 20
Appendix 1 the dataset in detail ________________________________________________ 21
Table 1 Correlation between performance and Δ risk disclosure (starting point)____________ 21
Table 4 Correlation between the stability Δ performance and proxy 1-4 (Starting point) _____ 21
Table 7 Overview of dataset _______________________________________________________ 22
Table 8 Results thesis 1 (Starting point)______________________________________________ 23
Table 9 Results thesis 1 (Starting point, ex financials) __________________________________ 24
Table 10 Results thesis 1 (Maximal correlation)______________________________________ 25
Table 11 Results thesis 1 (Maximal correlation, ex financials) __________________________ 26
Table 12 Results thesis 2 (Starting point) ___________________________________________ 27
Table 13 Results thesis 2 (Starting point, ex financials)________________________________ 28
Table 14 Results thesis 2 (Maximal correlation)______________________________________ 29
Table 15 Results thesis 2 (Maximal correlation, ex financials) __________________________ 30

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1 Management Summary
Introduction
This research paper examines the relation between the performance of a company and the quantity
of risk disclosure by measuring the correlation between the two. Performance has been measured
two ways: first it has been expressed as the change in net income, reported in an annual report.
Secondly, the performance has been quantified by the change in stock price performance. Please
note that the observed values were actual values, no corrections have been made in relation to
overall performance in the market sector.
The stability of the performance is measured by using the absolute values of the calculated change
in performance. A higher absolute value indicates a lower stability of the performance.
Risk disclosure has been measured by four proxies: the number of pages of the risk section in the
annual report, the number of words of the risk section in the annual report, the number of tables in
the risk section and the overall number of times the word “risk” has been mentioned in the annual
report.
Central questions
The following three questions will be answered. 1) Is there a correlation between the quantity of
risk disclosure in an annual report versus the change in performance of a company? 2) Is there
correlation between the stability of the performance and the amount of risk disclosure in an annual
report? 3) If so, can investors use this relationship to make better investment decisions?
Results
The correlation between performance and risk disclosure has been calculated using Δ stock price to
quantify performance and the number of pages and words of the risk management section to
measure risk disclosure. The other proxies turned out to be less useful. The results show a negative
correlation when performance in 2006 is compared with the risk disclosure of 2007 and a positive
correlation when comparing 2007 performance with the risk disclosure of 2007. When the same
correlation is calculated using the absolute values of performance (to quantify the stability of the
performance), positive correlation coefficients are observed. The correlations become stronger
when the financials are excluded.
Conclusions
The answer to the first question is yes. The results indicate that the performance in the previous
year is negatively correlated with the risk disclosure in the current year. There seems to be logic in
this; in bull markets, where stock prices are rising, people in general have a tendency to forget
about risks (take the internet bubble or sub prime crisis as an example) and are more interested in
investing in new opportunities. This could well explain a tendency for management to disclose less
on risk management. The logic is also present the other way around.
The answer to the second questions is also yes. The results indicate that the stability of
performance is positively correlated with the amount of risk disclosure. If we do assume that risk
disclosure is an indicator of a company’s efforts on risk management, the assumption could be
made that increased risk disclosure leads to a more stable performance. In other words, when a

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company spends more attention to managing its risk (investors observe an increase in risk
disclosure), the stability of its performance is expected to increases as a result.
The answer to the third question is no. Investors can not use this information to improve their
investment decisions. Risk disclosure is possibly used as a marketing tool. It does not necessarily
imply that actual efforts on risk management are undertaken. Also, annual reports come at the end
of a year. This implies that possible damage to the performance is already done.

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2 Introduction
Have you ever read an annual report that was not optimistic about the current company’s business?
When the company’s profit is decreasing year after year and it is clear that the company is a sitting
target for a takeover or worse, heading for a bankruptcy, the annual report would still view last
year as “full of turmoil”. Managements’ focus is aimed on future “opportunities”.
An annual report, apart from presenting the company’s financials, can for a great part be seen as a
marketing tool. The potential “nasty” truth will always be presented in a less nasty way. This could
imply that when the company is doing well, the amount of “extra positive news” would be less
necessary and vice verse. This phenomenon could be referred to as the (negative correlated)
relation between the performance of a company and the amount of “polishing up” reality.
This research paper, examines the relation between the performance of a company and the quantity
of risk disclosure by measuring the correlation between the two. Both “performance” and “risk
disclosure” are measured in different ways. The following discussion is based on the assumption
that the higher the quantity of risk disclosure in an annual report is, the more professional the
company’s risk management department is.
In the past, various research has been undertaken in the field of risk disclosure and risk
communication in annual reports (see chapter 7 Data/Literature).
Lajili and Zéghal (2005) for instance, conclude that more formalised and comprehensive risk
disclosure might be desirable in the future to effectively reduce information asymmetries between
management and stakeholders.
Another example is the work of Lisley and Schrives (2006). They find a significant association
between the number of risk disclosure and company size. In line with the article by Lajili and
Zéghal (2005), they also conclude that a lack of coherence in the risk narratives will imply the
existence of a risk information gap. This will lead to the inability of stakeholders to adequately
assess the risk profile of a company.
Beretta and Bozzolan (2004), propose a framework for the analysis of risk communication and an
index to measure the quality of risk disclosure. According to the authors, attention has to be paid
not only to how much is disclosed but also to what is disclosed and how.
This paper will try to answer the following central questions. 1) Is there a correlation between the
amount of risk disclosure in an annual report versus the change in performance of a company? 2)
Is there a correlation between the stability of the performance and the amount of risk disclosure in
an annual report? 3) If a correlation is observed, can investors use this relationship to make better
investment decisions?
To answer these questions, the following two hypotheses will be tested:
1 Δ performance is correlated with Δ risk disclosure
2 the absolute value of “Δ performance” is correlated with Δ risk disclosure

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The performance will be measured two ways: as Δ net income and as Δ stock price. The stability
of the performance will be measured by taking the absolute value of the performance. Δ risk
disclosure will be measured with the following proxies: the number of pages & words of the risk
(management) paragraph; the number of tables in the risk (management) paragraph; the number of
times the word “risk” is mentioned in the annual report and the different kind of risks mentioned in
the risk (management) paragraph.
The remainder of this paper is structured as follows. Section 3 will give a detailed overview of the
methodology. In section 4, a summary of the results will be presented. Section 5 discusses the
results and presents the conclusions. In the next chapter, the conclusions will be discussed with a
professional. The paper ends with an overview of the data and literature (section 7), my
acknowledgements and an appendix with a detailed overview of most data used.

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3 Methodology
3.1 Mathematical expression of the hypotheses
As presented in the introduction, the mathematical expressions of the hypotheses are as follows:
1 Δ performance company (P) is correlated with Δ risk disclosure (I)
2 ABS(Δ performance company (P)) is correlated with Δ risk disclosure (I)
Or in short:
Thesis 1 Δ P is correlated with ∆ I
Thesis 2 │Δ P│is correlated with ∆ I
3.2 Δ performance
Δ performance will be measured in two ways. At first an “objective” approach will be used by
using accounting figures. In this case the relative Δ of published net income will be used.
The second approach will take a more “subjective” approach: the performance will be measured by
calculating the relative Δ of the stock price during a time interval of a year.
In summary:
• Δ net income: [net income 2007- net income 2006]/ [net income 2006]
• Δ stock price: [stock price(t) – stock price (t-1y)]/[stock price (t-1y)]
Example calculating Δ net income
For example: in the annual report of 2007, AEGON reported a decrease in net income of (2251
-3169)/3169= 19,5%. For some companies, the net income was not published. In this case net
profit or EBITA (earnings before interest and tax) were used.
Example calculating Δ stock price
For AEGON the following stock prices where found:
The resulting Δ stock price is (12,09-14,44)/14,44=-16%
2006 2007
AEGON 14,44 12,09

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As a starting point, Δ stock price of the year ultimo 2007 and 2006 will be taken. Later on all stock
prices between Δ year end 2006-2005 and Δ year end 2007-2006 will be used to calculate different
Δ stock prices.
Figure 1 Example: calculating different Δ stock prices over a period of time
2006 2007
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
delta P(S)
delta P(S)
delta P(S)
etc
3.3 Δ risk disclosure
There are various ways to measure the amount (and subsequently Δ) of risk disclosure.
In this research paper, the following “proxies” have been selected.
Proxy 1 The number of pages in the annual report spent on the risk related paragraph related
to the total pages of the annual report.
At first glance, this proxy seems a good indicator. The more words spent on this topic, the more
pages, right? The problem with this proxy is that it is a bit rough. Suppose that company “A”
increases the risk management chapter from 0,78 page to 1,17 page; these kind of increases are
more difficult to quantify. One way to improve this is to relate the pages to the total pages of the
annual report.
Proxy 2 The number of words in the annual report spent on the risk related paragraph related
to the total amount of words of the annual report.
Obviously, this proxy is strongly related to the number of pages, but can be measured more in
detail with the “word count” option in word. This proxy will also be related to the total amount of
words.
Proxy 3 The number of tables used in the annual report spent on the risk related paragraph.
It is said that a picture (or table) says more than a thousand words. This given, an increase in the
use of tables is considered an indicator of risk disclosure. Therefore, this proxy is considered to be
useful and, also important, easy to quantify.

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Proxy 4 Number of times the word “risk” has been mentioned in the annual report related to
the total amount of words in the annual report.
In this thesis, it is assumed that the more the word risk is used in an annual report, the more the
company is concerned with risk management. There is however the concern that this proxy is
correlated with the amount of words used in the risk section. This proxy will be also related to the
total words in the annual report.
Proxy 5 The different kind of risks (f.i. interest rate/foreign exchange/counterparty etc.)
mentioned.
This proxy seemed a good indicator of the company’s concern with risk. Unfortunately, during the
process of gathering the data, it turned out that this proxy was difficult to quantify. First, it could
not be counted automatically. Secondly, the lack of coherence in the risk narratives made it
difficult to quantify.
Proxy 6 The different kind of methods mentioned to manage risks (f.i. value at risk, interest
rate sensitivity analysis, hedging policy, etc.)
As with proxy 5, this proxy seemed a good indicator of the company’s concern with risk.
Unfortunately, during the process of gathering the data, it turned out that this proxy was difficult to
quantify. First, it could not be counted automatically. Secondly, the lack of coherence in the risk
narratives made it difficult to quantify.
3.4 Selection of the companies
The dataset consists of information extracted out the annual reports of the 24 AEX listed
companies. I could have also made a different selection (other country, only mid cap companies,
only small cap companies, only companies of the same sector etc.). The most important criterion is
that a company, being part of the dataset, is assumed to have a professional person/department
being responsible for the annual report. This criterion is assumed to be true for all publicly listed
companies. For the ease of the author, the choice fell on the AEX listed companies. First an overall
correlation will be calculated; later, correlations will be measured while excluding the financials.
Please note
All the annual reports can be downloaded from internet (company’s website). Via the option
“search” it is possible to count how much a certain word is used. Via copy / paste, parts of text can
be copied to Microsoft Word where the “word count” option is available.

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3.5 Testing the data: the steps taken
Thesis 1 Δ performance is correlated with Δ risk disclosure
To create a starting point, the correlation between Δ performance and Δ risk disclosure will be
calculated using the year ultimo of 2007 and 2006. As indicated, Δ performance will be measured
two ways: via the net income found in the annual report and by taking the published stock price
performance. The next step will be to recalculate the correlations while excluding the financials
(banks/insurance companies). This is done because financials are assumed to manage risks by
profession (as opposed to a company that produces chemicals). Finally, the maximum (positive or
negative) correlation coefficient will be calculated by taking different Δ stock prices (see: Figure 1)
In case the standard deviation of the proxies is high, the “ln” of the proxies will be used to re-
calculate the data. This is done with proxy 3 “number of tables in risk section”
Summary of calculation steps:
1. The correlation between Δ net income and Δ risk disclosure;
2. The correlation between Δ stock price and Δ risk disclosure;
3. Recalculation of correlations without the financial companies;
4. Finding maximal (positive or negative) correlation using different intervals for Δ stock
price
Thesis 2 ABS (Δ performance) is correlated with Δ risk disclosure
When testing the second thesis, that measures the correlation between the stability of performance
and risk disclosure, the following steps are taken:
Summary of calculation steps:
1. The correlation between the ABS(Δ net income) and Δ risk disclosure;
2. The correlation between the ABS(Δ stock price) and Δ risk disclosure;
3. Recalculation of correlations without the financial companies;
4. Recalculating correlation using Δ stock price that corresponds with the maximum
correlation with thesis 1. (Effectively to make the comparison within the same time frame.)

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4 Results
4.1 The correlation between Δ performance and Δ risk disclosure
The following results are observed. Δ net income and Δ risk disclosure (both measured in the year
2007) show low correlation (see appendix 1, table 1). The minimum of -0,15 is found with proxy 3
(number of tables in the risk section). The maximum of 0,1 is found with proxy 2 (number of
words in the risk section).
When calculating the correlation (see also the appendix 1, table 1) between Δ stock price and Δ
risk disclosure (both measured in the year 2007) stronger correlations are found. The minimum of
0,13 is found with proxy 4 (the number of times the word “risk” is found in the annual report). The
maximum of 0,17 is found with proxy 2 (amount of words used in the risk section). It is interesting
to note that proxy 4 shows correlation contrary to the correlations found with proxy 1 and 2.
Table 2 Correlation between performance and Δ risk disclosure (excluding the financials)
Results thesis 1 Proxy Proxy Proxy Ln Proxy
1 2 3 (1+proxy 3) 4
pages risk
section
words risk
section
tables risk
section
tables risk
section
word
count
"risk"
Ex financials (banks & insurance)
Δ net income ult 2007-ult 2006 -0,02 0,22 -0,20 0,12 -0,02
Δ stock price ult 2007-ult 2006 0,36 0,43 0,13 0,22 -0,33
When the financials (AEGON, ING and Fortis) are excluded, the correlation between the
companies’ performance and most proxies becomes larger. Relatively high correlations are found:
0,36 between Δ stock price and proxy 1 (number of pages) and 0,43 with proxy 2 (number of
words). This positive result is nevertheless offset by the remarkable negative correlation of -0,33,
found with proxy 4 (number of times the word “risk” is mentioned in the annual report).
The sample size (24 companies) and period (2 years) are relatively small. Furthermore, absolute
returns (in contrary to abnormal returns) are used to test the thesis. These imperfections could be a
possible explanation for this contradictive result. It could be interesting to further investigate this
but with respect to testing thesis 1, proxy 4 (word count “risk”) will be excluded.
The calculated observations for proxy 3 (tables in risk section) are less than 50% of the
correlations of proxy 1 and 2. Since this correlation is relatively weak, this proxy will also be
excluded while continuing with testing the first thesis.

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Figure 2 shows the scatter diagram that results in the correlation of 0,36 with proxy 1 and 0,43 with proxy 2. The
outlier on the bottom left is USG People. The outlier on the top right is Tom Tom. In this dataset, USG people is the
biggest driver of the correlation. To illustrate this: excluding this company would lower the correlations from 0,36 to
0,05 (proxy 1) and from 0,43 to 0,23 (proxy 2)
Figure 2 Scatter diagram of Δ stock price versus proxy 1 (pages) and 2 (words)
Delta stockprice vs proxy 1
-60,0%
-40,0%
-20,0%
0,0%
20,0%
40,0%
60,0%
80,0%
-6,0% -4,0% -2,0% 0,0% 2,0% 4,0% 6,0%
Delta stockprice vs proxy 2
-60,0%
-40,0%
-20,0%
0,0%
20,0%
40,0%
60,0%
80,0%
-6,0% -4,0% -2,0% 0,0% 2,0% 4,0% 6,0% 8,0%
Focussing thus on the stock price and excluding the financials of this dataset, apparently leads to
an increase of the correlation. To further test this increase, the correlation between Δ stock price
and proxy 1 (pages risk section) and proxy 2 (amount of words risk section) will be calculated for
all Δ stock prices in the range “ult 2007-ult 2006” to “ult 2006-2005”.1
The following min and max are found. In line with the previous results, the correlations increase
(in both negative and positive direction) when the financials are excluded.
Table 3 Maximum correlation between performance and proxy 1 and 2
Results thesis 1 Proxy Proxy
1 2
pages risk section words risk section
Finding max
Δ stock price 7 Dec 06-7 Dec 05 -0,51 -0,47
Δ stock price 20 April 07-18 April 06 0,20 0,04
Finding max (Ex financials)
Δ stock price 7 Dec 06-7 Dec 05 -0,56 -0,57
Δ stock price 20 April 07-18 April 06 0,45 0,33
It is remarkable that the observed results seem unstable. A negative correlation of -0,51 and -0,47
is found when comparing performance in 2006 with proxy 1 (pages in risk section) and proxy 2
(words in risk section), which are calculated over the period 2007, whilst a positive correlation of
0,20 and 0,04 are found when comparing performance in 2007 with proxy 1 (pages) and 2 (words).
1
This table and attached calculation sheet is too large to included in the appendix. It is of course available on request.

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Again, when excluding the financials, all correlations increase in both positive and negative
direction). The following graph shows all the calculated correlations between Δ stock price and
proxy 1 (pages) and proxy 2 (words). Please note that the graph shows the correlations where the
financials are included. Without them, the graph looks more or less the same, except that the peaks
are slightly higher.
Figure 3 Correlation between a range of Δ stock prices and proxy 1 and 2
-0,60
-0,50
-0,40
-0,30
-0,20
-0,10
0,00
0,10
0,20
0,30
2-jan-062-m
rt-062-m
ei-062-jul-06
2-sep-062-nov-062-jan-072-m
rt-072-m
ei-072-jul-07
2-sep-072-nov-07
[stock price(t) – stock price (t-1y)]/[stock price (t-1y)]
Correlation
proxy 1 (number of pages of risk section) proxy 2 (amount of words risk section)
4.2 The correlation between the stability of Δ performance and Δ risk disclosure
To test the second thesis, the stability of the performance is first expressed as the absolute value2
of Δ net income. Secondly, the absolute value of Δ stock price performance is used to quantify the
stability of performance. As in the previous section, we first calculate the correlations using the
year end data (starting point). An overview of the results can be found in the appendix (table 4).
With respect to using the absolute value of Δ net income: the maximum (negative) correlation of
-0,17 is found with the proxy 3 (number of tables in the risk section). At the same time, the
maximum positive correlation of 0,11 is found with the ln(1+proxy 3).
When using the absolute vale of Δ stock price to measure the stability of performance, the results
are somewhat better. Maximum (negative) correlation of -0,22 is found with ln(1+proxy 3) (tables
in risk section) and -0,19 with proxy 1 (pages in risk section).
2
In tables depicted as: ABS(Δ net income) or ABS(Δ stockprice)

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Table 5 Correlation between the absolute value of Δ performance and proxy 1-4 (excluding the financials)
1 2 3
(1+proxy
3) 4
pages
risk
section
words
risk
section
tables
risk
section
tables risk
section
word
count
"risk"
Ex financials (banks & insurance)
ABS (Δ net income) ult 2007-ult 2006 -0,03 0,19 -0,16 0,22 0,03
ABS(Δ stock price) ult 2007-ult 2006 -0,20 -0,02 -0,06 -0,19 -0,10
When the financials (AEGON, ING and Fortis) are excluded, the correlations between the absolute
value of Δ net income improve for proxy 1 (from 0,03 to 0,19) and for the ln(1 + proxy 3) (from
0,11 to 0,22). When stability of performance is measured via the absolute value of Δ stock price,
the level of correlation is more or less the same as before excluding the financials.
The last step is to recalculate the correlations between the absolute value of Δ stock price and
proxy 1 (pages) and 2 (words) using the time intervals that gave the maxima (positive and negative)
correlations when testing thesis 1. The following table gives an overview of the results.
Table 6 Maximum correlation between the absolute value of Δ performance and proxy 1 and 2
Results thesis 2 Proxy Proxy
1 2
pages
risk
section
words
risk
section
Finding max
ABS (Δ stock price) 7 Dec 06-7 Dec 05 0,44 0,33
ABS (Δ stock price) 20 April 07-18 April 06 0,13 0,22
Finding max (Ex financials)
ABS (Δ stock price 7 Dec 06-7 Dec 05 0,51 0,40
ABS (Δ stock price) 20 April 07-18 April 06 0,21 0,41
The correlation is strongest when using the Dec 2006-Dec 2005 interval (0,44 and 0,33). When the
financials are excluded, both correlations increase to 0,51 and 0,40. The measured correlation is
lower (but still positive) when using the April 2007-April 2006 interval (0,13 and 0,22).

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5 Analysis and conclusions
5.1 General
This research paper examines the relation between the performance of a company and the quantity
of risk disclosure by measuring the correlation between the two. Performance has been measured
two ways: first it has been expressed as the change in net income, reported in an annual report.
Secondly, the performance has been quantified by the change in stock price performance. Please
note that the observed values were actual values, no corrections have been made in relation to
overall performance in the market sector.
The stability of the performance is measured by using the absolute values of the calculated change
in performance. A higher absolute value indicates a lower stability of the performance.
Risk disclosure has been measured by four proxies: the number of pages of the risk section in the
annual report, the number of words of the risk section in the annual report, the number of tables in
the risk section and the overall number of times the word “risk” has been mentioned in the annual
report.
Central questions
The following three questions will be answered. 1) Is there a correlation between the quantity of
risk disclosure in an annual report versus the change in performance of a company? 2) Is there
correlation between the stability of the performance and the amount of risk disclosure in an annual
report? 3) If so, can investors use this relationship to make better investment decisions?
Results
The correlation between performance and risk disclosure has been calculated using Δ stock price to
quantify performance and the number of pages and words of the risk management section to
measure risk disclosure. The other proxies turned out to be less useful. The results show a negative
correlation when performance in 2006 is compared with the risk disclosure of 2007 and a positive
correlation when comparing 2007 performance with the risk disclosure of 2007. When the same
correlation is calculated using the absolute values of performance (to quantify the stability of the
performance), positive correlation coefficients are observed. The correlations become stronger
when the financials are excluded.
How could one interpret these results?

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5.2 Risk disclosure, managing expectations?
The results show evidence that performance in 2006 is negatively correlated with Δ risk disclosure
in 2007. In 2006 the performance of the AEX was positive (from index value 440 to 495). So for
most companies Δ stock price was positive. Since the correlation is negative, the quantity of risk
disclosure decreased. There seems to be logic in this; in bull markets, where stock prices are rising,
people in general have a tendency to forget about risks (take the internet bubble or sub prime crisis
as an example) and are more interested in investing in new opportunities.
The other way around, the logic seems even more rationale. Suppose you are the CFO of a public
listed company. In December 2006, you observe that your stock is trading lower in comparison
with the previous year. Apart from taking internal actions (for instance cost cutting, change in
strategy, lay offs etc.) to improve your result, it is feasible that you instruct the person responsible
for writing the risk section of the annual report to increase the risk management section. The
rationale behind this is to signal to the firm’s stakeholders that management of the company is
committed to improve the current results by spending more effort in risk management.
This conclusion is thus based on marketing ideas, where the annual report is used as a tool to
manage expectations. For this theory, it is not necessary that the quantity of risk disclosure is an
indicator of a company’s actual efforts in the field of risk management. For the conclusion on
stability of performance and risk disclosure, this assumption is necessary.
What about the second half of Figure 3, where a positive correlation is observed between
performance and risk disclosure?
The second half of Figure 3 shows the contrary of the first conclusion. If the first conclusion
(negative correlation between performance and risk disclosure) is correct than this observance
could be classified as coincidence. Suppose again that you are the CFO of a company and in April
2007 you see that the stock price has increased since past 12 months. Would this, form a marketing
perspective be an incentive to increase the amount of risk disclosure? I can not find a rationale for
this.
Further research in this area is advisable.
5.3 Risk disclosure, stabilizing results?
A positive correlation between the stability of performance and risk disclosure is observed. This
seems feasible. If we do assume that risk disclosure is an indicator of a company’s efforts on risk
management, the assumption could be made that increased risk disclosure leads to a more stable
performance. In other words, when a company spends more attention to effectively managing its
risk (investors observe an increase in risk disclosure), the stability of its performance should
increase as a result.
5.4 Risk disclosure, useful to investors?
If the first conclusion (negative correlation between performance and risk disclosure) is correct,
risk disclosure could be seen as a marketing tool. It does not necessarily imply that actual efforts
on risk management are undertaken. In this case investors can not rely on any change in the
amount of risk disclosure as a result.

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When viewing this in relation to the “chicken and egg, who was there first?” discussion, the good
performance was first; the decreased risk disclosure came next. This is in line with reality, where
businesses are started. Only after a positive performance, businesses can grow to become mature
enterprises. This implies that performance leads to growth. So we can conclude that risk
management comes after performance. Change in risk disclosure can thus not be used as indicator
for future performance.
At first instinct, the second conclusion (stability of performance is positively correlated with risk
disclosure) supports a “yes” to the question. The problem however is always that these annual
reports come at the end of a year. This implies that possible damage to the performance is already
done.
The observed results indicate that investors can not use this information to improve their
investment decisions.
5.5 Summary of conclusions
The answer to the first question is yes. The results indicate that the performance in the previous
year is negatively correlated with the risk disclosure in the current year. There seems to be logic in
this; in bull markets, where stock prices are rising, people in general have a tendency to forget
about risks (take the internet bubble or sub prime crisis as an example) and are more interested in
investing in new opportunities. This could well explain a tendency for management to disclose less
on risk management. The logic is also present the other way around.
The answer to the second questions is also yes. The results indicate that the stability of
performance is positively correlated with the amount of risk disclosure. If we do assume that risk
disclosure is an indicator of a company’s efforts on risk management, the assumption could be
made that increased risk disclosure leads to a more stable performance. In other words, when a
company spends more attention to managing its risk (investors observe an increase in risk
disclosure), the stability of its performance is expected to increases as a result.
The answer to the third question is no. Investors can not use this information to improve their
investment decisions. Risk disclosure is possibly used as a marketing tool. It does not necessarily
imply that actual efforts on risk management are undertaken. Also, annual reports come at the end
of a year. This implies that possible damage to the performance is already done.

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6 Discussing conclusions with a professional
The results of this thesis have been presented to Marcel Knoester.
Marcel (1969) studied finance at the Erasmus University of Rotterdam. He started his career as a
management consultant with KPMG. Since 2002, Marcel is working for ING Real Estate where he
has worked in different disciplines. Most recently he has been responsible for the structuring and
management of investment funds. As director “Private Funds” he has a lot of experience in the
field of external reporting.
The thesis concludes that
1. The performance in the previous year is negatively correlated with the risk disclosure in the
current year.
2. The stability of performance is positively correlated with the amount of risk disclosure.
3. Investors can not use this information to improve their investment decisions. Risk
disclosure is possibly used as a marketing tool. It does not necessarily imply that actual
efforts on risk management are undertaken. Also, annual reports come at the end of a year.
This implies that possible damage to the performance is already done.
Looking at the first conclusion, in general, Marcel agrees with the outcome. He acknowledges that
there is a positive correlation between risk disclosure and the performance of a company.
According to him however, the relationship is more direct and not with a one year time lag. Also,
in his view the relationship (correlation) between performance and risk disclosure is more based on
performance expressed as the results in the profit and loss statement (in contrary to the stock prices
used in this thesis).
Marcel fears that the second conclusion does not have enough quantitative support. He points out
that this conclusion is for a great deal based on the assumption that the higher the quantity of risk
disclosure in an annual report is, the more professional the company’s risk management
department is. (see page 4) We both agree that, with respect to this assumption, further analysis is
advisable.
According to Marcel, risk disclosure should give investors a better understanding of how a
company deals with risks. They can use the information published in this section to make better
investment decisions. He states that management of a company will not write about risk
management only to comply with peer pressure. He therefore questions the assumption that risk
disclosure is used as a marketing tool. (Regardless of the fact that risk management is currently
“hot”.) He expects a company only to publish about risks that are actually being managed. If this
was not the case, and one of the described risks turns out not to be managed correctly, management
would feel the repercussion.

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7 Data / Literature
1. The annual reports of all AEX companies of the year 2006 and 2007;
2. Daily stock prices of all AEX companies via Bloomberg over the period 2005 to 2007;
3. A Content Analysis of Risk Management Disclosures in Canadian Annual Reports,
Kaouthar Lajili, Daniel Zéghal, Canadian Journal of Administrative Sciences, 22 (2), 125 -
142 (2005)
5. A framework for the analysis of firm risk communication, Sergio Beretta and Saverio
Bozzolan, The International Journal of Accounting 39 (2004) 265-288
7. The management of corporate financial disclosure: Opportunism, ritualism, policies,
and processes, M Gibbins, A Richardson, J Waterhouse - Journal of accounting research,
1990 - jstor.org
8. Risk reporting: a study of risk disclosures in the annual reports of UK companies, PM
Linsley, PJ Shrives - The British Accounting Review 38 (2006) 387-404
9. An analysis of the association between pollution disclosure and economic performance,
M Freedman, B Jaggi - Accounting, Auditing & Accountability Journal, 1988 -
emeraldinsight.com
10. Corporate Disclosure Policy and Analyst Behavior, M.H. Lang and R.J. Lundholm-
American Accounting Association 1996.

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Acknowledgments
This thesis would not have been completed without the help and guidance of the following people:
my mentor Herbert Rijken, my old school buddy Denny Borsboom, Marcel Knoester and my other
“mentor” (and lovely wife) Brechtje for her ongoing support.
I would also like to thank all staff of the VU who made the post graduate program “Treasury
Management” at the VU Amsterdam a great success. Special thanks to Theo van der Nat and Patty
Eveleens.
Last but not least, a special thanks to my fellow TM9 study buddies Brian, Martin & Arend Jan,
and my favorite colleague Mark!

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Appendix 1 the dataset in detail
Table 1 Correlation between performance and Δ risk disclosure (starting point)
1 2 3 (1+proxy 3) 4
pages risk
section
words risk
section
tables risk
section
tables risk
section
word
count
"risk"
Δ net income ult 2007-ult 2006 -0,02 0,10 -0,15 0,08 0,07
Δ stock price ult 2007-ult 2006 0,17 0,12 -0,07 0,08 -0,13
Table 4 Correlation between the stability Δ performance and proxy 1-4 (Starting point)
1 2 3 (1+proxy 3) 4
pages risk
section
words risk
section
tables risk
section
tables risk section
word count
"risk"
ABS (Δ net income) ult 2007-ult 2006 -0,08 0,03 -0,17 0,11 -0,03
ABS(Δ stock price) ult 2007-ult 2006 -0,19 -0,06 -0,07 -0,22 -0,08

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Table 7 Overview of dataset
2007-2006 1 2 3 4 2006-2005 1 2 3 4
Company Δ P(NI) Δ P(S) pages words tables
Count
risk Δ P(NI) Δ P(S) pages words tables
Count
risk
aegon -19,5% -16,3% 5,0% 10% 20 0,25% 2,1% 5,0% 2,7559% 5,2% 12 0,35%
ahold 221,9% 18,2% 4,0% 11% 6 0,21% 526,7% 27,3% 3,1% 8,0% 8 0,13%
akzo nobel 29,0% 18,6% 7,2% 9% 6 0,25% 20,0% 18,0% 4,4% 4,9% 2 0,17%
arcelor mittal 94,1% 65,8% 2,9% 3% 9 0,13% -22,4% 42,9% 2,1% 2,8% 5 0,12%
asm lith 10,1% 15,0% 2,6% 2% 1 0,13% 100,6% 11,5% 1,4% 1,5% 1 0,15%
bam groep 156,2% 9,6% 1,8% 2% 2 0,18% -10,6% 3,6% 1,9% 1,9% - 0,19%
corio (2007 vs
2005) 36,0% -10,5% 1,7% 3% 9 0,16% 97,7% 34,9% 1,3% 0,8% 3 0,15%
dsm -21,6% -13,6% 2,4% 4% 6 0,20% 3,8% 8,5% 2,7% 4,5% 5 0,21%
fortis -30,0% -44,3% 2,1% 2% 1 0,39% 24,4% 19,9% 3,3% 3,4% 1 0,55%
fugro 53,2% 45,9% 2,6% 4% 2 0,19% 41,9% 33,4% 2,7% 4,0% 2 0,14%
heineken -33,4% 22,6% 3,1% 5% 7 0,25% 59,1% 34,7% 2,8% 4,8% - 0,17%
ing groep 20,1% -20,4% 17,4% 25% 40 1,29% 6,7% 14,6% 10,2% 11,8% 19 0,69%
kpn 7,0% 15,5% 4,7% 4% 3 0,14% -5,7% 27,2% 2,5% 3,4% 3 0,09%
philips -22,6% 3,3% 5,3% 7% 10 0,12% 87,7% 8,8% 5,7% 6,7% 9 0,13%
randstad 7,0% -48,4% 1,6% 1% - 0,31% 49,0% 42,8% 0,8% 0,7% - 0,30%
reed elsevier 20,0% 5,7% 1,0% 2% 5 0,16% 3,0% 9,5% 0,6% 1,3% - 0,16%
royal dutch shell a 21,3% 7,6% 0,9% 2% - 0,12% 0,2% 3,6% 0,8% 1,5% - 0,11%
sbm offshore 23,0% -17,1% 5,6% 8% - 0,29% -4,2% 52,7% 5,6% 7,3% - 0,22%
tnt -6,6% -13,3% 4,1% 3% 10 0,22% 11,1% 23,4% 0,3% 0,7% 1 0,11%
tomtom 43,0% 57,4% 5,7% 9% 1 0,28% 74,0% 12,8% 4,1% 3,7% - 0,35%
Unilever -3,0% 21,5% 1,4% 2% - 0,15% 6,6% 7,4% 0,7% 1,3% 0,14%
usg people 26,3% -43,9% 1,2% 4% - 0,27% 425,9% 85,0% 6,5% 9,2% - 0,19%
wereldhave -37,0% -25,9% 2,7% 4% - 0,26% 7,9% 31,6% 2,0% 3,6% - 0,20%
wolters kluwer 4,0% 3,2% 2,7% 4% - 0,20% 15,9% 27,6% 2,8% 4,8% 1 0,14%

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Table 8 Results thesis 1 (Starting point)
Measuring correlation Δ P Δ P Proxy Proxy Proxy Ln Proxy
ult 2007-ult 2006
Company Net Income Stockprice 1 2 3 (1+prox 3) 4
aegon -20% -16% 2,3% 4,5% 8 2 -0,094%
ahold 222% -5% 0,9% 3,1% 2- 0,082%
akzo nobel 29% 19% 2,8% 4,4% 4 2 0,080%
arcelor mittal 94% 47% 0,8% 0,4% 4 2 0,002%
asm lith 10% 2% 1,2% 0,2% - - -0,021%
bam groep 156% 10% -0,1% 0,1% 2 1 -0,011%
corio 36% -11% 0,4% 1,9% 6 2 0,011%
dsm -22% -14% -0,3% -0,3% 1 1 -0,004%
fortis -30% -33% -1,2% -1,5% - - -0,160%
fugro 53% 46% -0,1% -0,1% - - 0,056%
heineken -33% 23% 0,3% 0,0% 7 2 0,077%
ing groep 20% -20% 7,2% 13,3% 21 3 0,601%
kpn 7% 16% 2,2% 0,9% - - 0,056%
philips -23% 3% -0,4% -0,2% 1 1 -0,007%
randstad 7% -48% 0,8% 0,8% - - 0,009%
reed elsevier 20% 8% 0,3% 1,2% 5 2 0,001%
shell 21% 6% 0,1% 0,2% - - 0,010%
sbm offshore 23% -17% 0,1% 0,7% - - 0,071%
tnt -7% -13% 3,7% 2,7% 9 2 0,107%
tomtom 43% 57% 1,6% 5,5% 1 1 -0,064%
Unilever -3% 21% 0,7% 0,7% - - 0,013%
usg people 26% -47% -5,3% -5,1% - - 0,082%
wereldhave -37% -26% 0,8% 0,5% - - 0,058%
wolters kluwer 4% 3% -0,1% -0,8% 1- 0,057%
Correlatie P(NI) and Proxy -0,02 0,10 -0,15 0,08 0,07
Correlatie P(S) and Proxy 0,17 0,12 -0,07 0,08 -0,13

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Table 9 Results thesis 1 (Starting point, ex financials)
ult 2007-ult 2006
ahold 222% -5% 0,9% 3,1% 2- 0,082%
akzo nobel 29% 19% 2,8% 4,4% 4 2 0,080%
arcelor mittal 94% 47% 0,8% 0,4% 4 2 0,002%
asm lith 10% 2% 1,2% 0,2% - - -0,021%
bam groep 156% 10% -0,1% 0,1% 2 1 -0,011%
corio 36% -11% 0,4% 1,9% 6 2 0,011%
dsm -22% -14% -0,3% -0,3% 1 1 -0,004%
fugro 53% 46% -0,1% -0,1% - - 0,056%
heineken -33% 23% 0,3% 0,0% 7 2 0,077%
kpn 7% 16% 2,2% 0,9% - - 0,056%
philips -23% 3% -0,4% -0,2% 1 1 -0,007%
randstad 7% -48% 0,8% 0,8% - - 0,009%
reed elsevier 20% 8% 0,3% 1,2% 5 2 0,001%
shell 21% 6% 0,1% 0,2% - - 0,010%
sbm offshore 23% -17% 0,1% 0,7% - - 0,071%
tnt -7% -13% 3,7% 2,7% 9 2 0,107%
tomtom 43% 57% 1,6% 5,5% 1 1 -0,064%
Unilever -3% 21% 0,7% 0,7% - - 0,013%
usg people 26% -47% -5,3% -5,1% - - 0,082%
wereldhave -37% -26% 0,8% 0,5% - - 0,058%
wolters kluwer 4% 3% -0,1% -0,8% 1- 0,057%
Correlatie P(NI) and Proxy -0,02 0,22 -0,20 0,12 -0,02
Correlatie P(S) and Proxy 0,36 0,43 0,13 0,22 -0,33

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Table 10 Results thesis 1 (Maximal correlation)
7 Dec 06-7 Dec 05 20 April 07-18 April 06
Company Stockprice Stockprice 1 2 3 (1+prox 3) 4
aegon -3% 8% 2,3% 4,5% 8 2 -0,094%
ahold 19% 46% 0,9% 3,1% 2- 0,082%
akzo nobel 12% 33% 2,8% 4,4% 4 2 0,080%
arcelor mittal 44% 31% 0,8% 0,4% 4 2 0,002%
asm lith 14% 22% 1,2% 0,2% - - -0,021%
bam groep -4% 19% -0,1% 0,1% 2 1 -0,011%
corio 24% 36% 0,4% 1,9% 6 2 0,011%
dsm 8% 0% -0,3% -0,3% 1 1 -0,004%
fortis 19% 21% -1,2% -1,5% - - -0,160%
fugro 34% 20% -0,1% -0,1% - - 0,056%
heineken 37% 28% 0,3% 0,0% 7 2 0,077%
ing groep 10% 9% 7,2% 13,3% 21 3 0,601%
kpn 25% 32% 2,2% 0,9% - - 0,056%
philips 14% 19% -0,4% -0,2% 1 1 -0,007%
randstad 37% 12% 0,8% 0,8% - - 0,009%
reed elsevier 0% -7% 0,3% 1,2% 5 2 0,001%
shell 14% 16% 0,1% 0,2% - - 0,010%
sbm offshore 43% 22% 0,1% 0,7% - - 0,071%
tnt 24% 19% 3,7% 2,7% 9 2 0,107%
tomtom 8% -2% 1,6% 5,5% 1 1 -0,064%
Unilever 2% 20% 0,7% 0,7% - - 0,013%
usg people 85% -5% -5,3% -5,1% - - 0,082%
wereldhave 20% 28% 0,8% 0,5% - - 0,058%
wolters kluwer 24% 8% -0,1% -0,8% 1- 0,057%
Correlatie P(S) and Proxy -0,51 -0,47 -0,188 -0,260 0,090
Correlatie P(S) and Proxy 0,20 0,04 -0,11 0,00 0,01

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Table 11 Results thesis 1 (Maximal correlation, ex financials)
ahold 19% 46% 0,9% 3,1% 2- 0,082%
akzo nobel 12% 33% 2,8% 4,4% 4 2 0,080%
arcelor mittal 44% 31% 0,8% 0,4% 4 2 0,002%
asm lith 14% 22% 1,2% 0,2% - - -0,021%
bam groep -4% 19% -0,1% 0,1% 2 1 -0,011%
corio 24% 36% 0,4% 1,9% 6 2 0,011%
dsm 8% 0% -0,3% -0,3% 1 1 -0,004%
fugro 34% 20% -0,1% -0,1% - - 0,056%
heineken 37% 28% 0,3% 0,0% 7 2 0,077%
kpn 25% 32% 2,2% 0,9% - - 0,056%
philips 14% 19% -0,4% -0,2% 1 1 -0,007%
randstad 37% 12% 0,8% 0,8% - - 0,009%
reed elsevier 0% -7% 0,3% 1,2% 5 2 0,001%
shell 14% 16% 0,1% 0,2% - - 0,010%
sbm offshore 43% 22% 0,1% 0,7% - - 0,071%
tnt 24% 19% 3,7% 2,7% 9 2 0,107%
tomtom 8% -2% 1,6% 5,5% 1 1 -0,064%
Unilever 2% 20% 0,7% 0,7% - - 0,013%
usg people 85% -5% -5,3% -5,1% - - 0,082%
wereldhave 20% 28% 0,8% 0,5% - - 0,058%
wolters kluwer 24% 8% -0,1% -0,8% 1- 0,057%
Correlatie P(S) and Proxy -0,56 -0,57 -0,038 -0,156 0,486
Correlatie P(S) and Proxy 0,45 0,33 0,08 0,17 0,36

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Table 12 Results thesis 2 (Starting point)
ult 2007-ult 2006
aegon 20% 16% 2,3% 4,5% 8 2 -0,094%
ahold 222% 5% 0,9% 3,1% 2- 0,082%
akzo nobel 29% 19% 2,8% 4,4% 4 2 0,080%
arcelor mittal 94% 47% 0,8% 0,4% 4 2 0,002%
asm lith 10% 2% 1,2% 0,2% - - -0,021%
bam groep 156% 10% -0,1% 0,1% 2 1 -0,011%
corio 36% 11% 0,4% 1,9% 6 2 0,011%
dsm 22% 14% -0,3% -0,3% 1 1 -0,004%
fortis 30% 33% -1,2% -1,5% - - -0,160%
fugro 53% 46% -0,1% -0,1% - - 0,056%
heineken 33% 23% 0,3% 0,0% 7 2 0,077%
ing groep 20% 20% 7,2% 13,3% 21 3 0,601%
kpn 7% 16% 2,2% 0,9% - - 0,056%
philips 23% 3% -0,4% -0,2% 1 1 -0,007%
randstad 7% 48% 0,8% 0,8% - - 0,009%
reed elsevier 20% 8% 0,3% 1,2% 5 2 0,001%
shell 21% 6% 0,1% 0,2% - - 0,010%
sbm offshore 23% 17% 0,1% 0,7% - - 0,071%
tnt 7% 13% 3,7% 2,7% 9 2 0,107%
tomtom 43% 57% 1,6% 5,5% 1 1 -0,064%
Unilever 3% 21% 0,7% 0,7% - - 0,013%
usg people 26% 47% -5,3% -5,1% - - 0,082%
wereldhave 37% 26% 0,8% 0,5% - - 0,058%
wolters kluwer 4% 3% -0,1% -0,8% 1- 0,057%
Correlatie P(NI) and Proxy -0,08 0,03 -0,17 0,11 -0,03
Correlatie P(S) and Proxy -0,19 -0,06 -0,07 -0,22 -0,08

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Table 13 Results thesis 2 (Starting point, ex financials)
ult 2007-ult 2006
ahold 222% 5% 0,9% 3,1% 2- 0,082%
akzo nobel 29% 19% 2,8% 4,4% 4 2 0,080%
arcelor mittal 94% 47% 0,8% 0,4% 4 2 0,002%
asm lith 10% 2% 1,2% 0,2% - - -0,021%
bam groep 156% 10% -0,1% 0,1% 2 1 -0,011%
corio 36% 11% 0,4% 1,9% 6 2 0,011%
dsm 22% 14% -0,3% -0,3% 1 1 -0,004%
fugro 53% 46% -0,1% -0,1% - - 0,056%
heineken 33% 23% 0,3% 0,0% 7 2 0,077%
kpn 7% 16% 2,2% 0,9% - - 0,056%
philips 23% 3% -0,4% -0,2% 1 1 -0,007%
randstad 7% 48% 0,8% 0,8% - - 0,009%
reed elsevier 20% 8% 0,3% 1,2% 5 2 0,001%
shell 21% 6% 0,1% 0,2% - - 0,010%
sbm offshore 23% 17% 0,1% 0,7% - - 0,071%
tnt 7% 13% 3,7% 2,7% 9 2 0,107%
tomtom 43% 57% 1,6% 5,5% 1 1 -0,064%
Unilever 3% 21% 0,7% 0,7% - - 0,013%
usg people 26% 47% -5,3% -5,1% - - 0,082%
wereldhave 37% 26% 0,8% 0,5% - - 0,058%
wolters kluwer 4% 3% -0,1% -0,8% 1- 0,057%
Correlatie P(NI) and Proxy -0,03 0,19 -0,16 0,22 0,03
Correlatie P(S) and Proxy -0,20 -0,02 -0,06 -0,19 -0,10

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Table 14 Results thesis 2 (Maximal correlation)
aegon 19% 46% 2,3% 4,5% 8 2 -0,094%
ahold 12% 33% 0,9% 3,1% 2- 0,082%
akzo nobel 44% 31% 2,8% 4,4% 4 2 0,080%
arcelor mittal 14% 22% 0,8% 0,4% 4 2 0,002%
asm lith 4% 19% 1,2% 0,2% - - -0,021%
bam groep 24% 36% -0,1% 0,1% 2 1 -0,011%
corio 8% 0% 0,4% 1,9% 6 2 0,011%
dsm 34% 20% -0,3% -0,3% 1 1 -0,004%
fortis 37% 28% -1,2% -1,5% - - -0,160%
fugro 25% 32% -0,1% -0,1% - - 0,056%
heineken 14% 19% 0,3% 0,0% 7 2 0,077%
ing groep 37% 12% 7,2% 13,3% 21 3 0,601%
kpn 0% 7% 2,2% 0,9% - - 0,056%
philips 14% 16% -0,4% -0,2% 1 1 -0,007%
randstad 43% 22% 0,8% 0,8% - - 0,009%
reed elsevier 24% 19% 0,3% 1,2% 5 2 0,001%
shell 8% 2% 0,1% 0,2% - - 0,010%
sbm offshore 2% 20% 0,1% 0,7% - - 0,071%
tnt 85% 5% 3,7% 2,7% 9 2 0,107%
tomtom 20% 28% 1,6% 5,5% 1 1 -0,064%
Unilever 24% 8% 0,7% 0,7% - - 0,013%
usg people 0% 0% -5,3% -5,1% - - 0,082%
wereldhave 0% 0% 0,8% 0,5% - - 0,058%
wolters kluwer 0% 0% -0,1% -0,8% 1- 0,057%
Correlatie P(NI) and Proxy 0,44 0,33 0,41 0,41 0,15
Correlatie P(S) and Proxy 0,13 0,22 0,00 0,15 -0,27

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Table 15 Results thesis 2 (Maximal correlation, ex financials)
ahold 12% 33% 0,9% 3,1% 2- 0,082%
akzo nobel 44% 31% 2,8% 4,4% 4 2 0,080%
arcelor mittal 14% 22% 0,8% 0,4% 4 2 0,002%
asm lith 4% 19% 1,2% 0,2% - - -0,021%
bam groep 24% 36% -0,1% 0,1% 2 1 -0,011%
corio 8% 0% 0,4% 1,9% 6 2 0,011%
dsm 34% 20% -0,3% -0,3% 1 1 -0,004%
fugro 25% 32% -0,1% -0,1% - - 0,056%
heineken 14% 19% 0,3% 0,0% 7 2 0,077%
kpn 0% 7% 2,2% 0,9% - - 0,056%
philips 14% 16% -0,4% -0,2% 1 1 -0,007%
randstad 43% 22% 0,8% 0,8% - - 0,009%
reed elsevier 24% 19% 0,3% 1,2% 5 2 0,001%
shell 8% 2% 0,1% 0,2% - - 0,010%
sbm offshore 2% 20% 0,1% 0,7% - - 0,071%
tnt 85% 5% 3,7% 2,7% 9 2 0,107%
tomtom 20% 28% 1,6% 5,5% 1 1 -0,064%
Unilever 24% 8% 0,7% 0,7% - - 0,013%
usg people 0% 0% -5,3% -5,1% - - 0,082%
wereldhave 0% 0% 0,8% 0,5% - - 0,058%
wolters kluwer 0% 0% -0,1% -0,8% 1- 0,057%
Correlatie P(NI) and Proxy 0,51 0,40 0,55 0,47 0,15
Correlatie P(S) and Proxy 0,21 0,41 -0,06 0,12 -0,21

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