paper draft (to be further implemented) - aidea 2013 · web viewthis affects the valuation ratio...

Analysis of the relationship between book value and market value in the bank and insurance sector: the impact of information on intangibles presented in

financial statementsS.Pucci, M.Cenci, R.Luly

(Università Roma Tre)

1. Introduction

2. Literature review

3. Model

3.1. Data

3.2. Results

3.3 Concerns on the impact of intangibles information on non-systemic risk

4. Limitation of the analysis and possible evolutions

References

Appendix

Key words: intangibles, financial statements, book value, market value, banks, insurances

Abstract: The present paper is part of the research done during a PRIN project dedicated to the analysis of company information on intangible assets following a multi-stakeholder approach referring to the financial sector. This paper combines the conclusions reached towards the multi-stakeholder approach (given by a score for each entity included in the sample attributable to unrecognized intangible assets) with a mathematical model that permits evaluation of the link between book value and market value. The aim is to try to verify if the increase or decrease in the disclosure of intangible assets information in financial statements influences the relationship between book and market value. The analysis was conducted using a formula – derived from the Daniel and Titman’s model which binds the annual return of the banks and insurances - measured as the logarithm of the ratio between book value and market value – with the information supplied on intangibles in the end of year accounts.

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1. Introduction

The links between the accounting information of listed firms and their market prices have been analysed by many authors and papers. This kind of research starts from Kalecki’s idea that “the rate of the investment decisions of a single entrepreneur depends on his capital accumulation and on the velocity of change of marginal net profitability”1. The principle of increasing risk of Kalecki shows that, even in a perfectly competitive market, risk increases with investment both for economic and financial reasons: the braking efficiency effect of risk is proportional to the weight that the investment has for the equity investor. For example, if we compare the position of two companies (the first exposed only a little to the tightening of the income statement, the second with higher fixed costs) with the same overall profits, though differently distributed over time, we can infer that they have a different degree of exposure to risk. Although the profit is the same, the second firm is more exposed to the risk of fluctuations in dividends. This affects the valuation ratio and could have negative consequences on the company evaluation. The research started from the above considerations and, at the same time, linked the performances for the period 2006-2011 to the ratio between book value (B) and market price (M) for banking and insurance companies on the basis of data provided by Mediobanca, which shows a significant reduction in the ratio M /Bduring the period examined. It was decided to determine whether values of the ratio M/B < 1 - existing for some of these companies - could be explained by overestimation of financial statement assets of financial institutions or by negative goodwill/intangible assets and therefore if an important role is played by the information available on the value of recognized and unrecognized intangible assets. The numbers which represent intangible assets are defined with a score derived by the application of a multi-stakeholder approach to the information in the financial statements and social and environmental accounts of the banks and companies included in the sample analysis2. The model used to measure the relationship between book and market value is bases on a formula – derived from the Daniel and Titman’s model – measured as the logarithm of the ratio B/M. A stochastic process is used to obtain information on the variables from which the future evolution of the B/M ratio will depend. This analysis is particularly relevant in connection with the financial crisis and the "loss of reputation" issue of the entire financial sector.

2. Literature review

The literature on the role, the evaluation and the accounting of intangible assets and on the relationship between book and market value is vast and belongs to different disciplines. For this reason this paper focuses only on the part of this literature that is closely linked to the concepts and the model used in this paper. Among the numerous works regarding the role and evaluation of intangibles the following have constituted a useful point of reference for this paper: B.LEV, 2001 (who defines the characteristics and the value of intangible assets); B.LEV, J.H.DAUM, 2004; A. DAMODARAN, 2009 (who analyses the role of these assets in the evaluation of a firm); D. ZEGHAL, A. MAALOUD, 2011.

For the part of the work that refers to Management Commentary and KPIs, useful reference points are: C.A.ADAMS, 2008 (that analyses the theme of corporate social responsibility and the reputational risk management); EUROPEAN ON FINANCIAL ANALYSTS SOCIETIES, 2009 (in which the authors analyse the problem of the integration of traditional information and KPI); GLOBAL

1 M.KALECHI, The Principle of Increasing risk, Economica, New Series Vol.4, N.16, Nov 1937, pp.440-447, pag.447 2 The way in which the score for the level of information is attributed to the single banks of the sample is analyzed in: S.PUCCI, Le risorse immateriali nel settore bancario, Giappichelli, Torino, 2013, chap.4.

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REPORTING INITIATIVE, 2009 (in which it is possible to fine both guidelines in the application of KPI and the main stakeholders and joined KPI).

The papers examined referring to bank intangibles assets are: W.BEAVER, C.EGER, S.RYAN, M.WOLFSON, 1989; A.DAMODARAN, 2009 (that analyses the relevance of intangibles in financial sector); O. DEEV, 2011; F.FIORDELISI, P.MOLYNEUX, 2006 (in which the problems is analysed from a shareholders perspective); H.ISIDRO, D.GRILO, (that analyse the accounting based valuation model for commercial banks); J.M.KOLBECK, 2004, (in which the author tries to analyse how investors incorporate information about intangibles in the prices of banks); J.M.KOLBECK, T.D.WARFIELD, 2007 (in which the authors analyse the effects of banks intangibles assets on abnormal earnings); Z.MATOLCSY, A.WYATT, 2005 (that analyses the relationship between intangible assets and dispersion of earnings forecasts).

In addition to the previous literature, used to build the mathematical model, other papers have also been considered regarding the search for links between the information provided by financial statements of listed companies and their market price, which has been the main subject of many important studies in finance. The extrapolation of links between the official market price and increasing market efficiency would be extremely useful to investors. Many works have studied the predictive capabilities of financial statement data - such as book value - on the price of the underlying equity security (E.F. FAMA, K.R. KENNET, 1992; E.F. FAMA, K.R. KENNET, 1993; E.F. FAMA, K.R. KENNET, 1995; E.F. FAMA, K.R. KENNET, 1998), while others have studied the reactions of share prices to information obtained from the financial statements of companies (K.DANIEL, S.TITMAN, 2006; W.F.M. DE BONDT, R.H. THALER R.H., 1985; W.F.M. DE BONDT, R.H. THALER R.H, 1987). The analysis in this paper follows this last approach and focuses on the temporal evolution of the ratio between book value and market prices of Italian banks and insurances in order to determine whether there is a common factor in the financial sector that justifies the fact that the recent market prices of these institutions are, in some cases, lower than their book value, considering the impact of intangible assets.

3. The model

When the book value to market price ratio is >1, the company is less exposed to takeover and to the possibility of top managers losing control than when this ratio is less than one.

A basic analysis could highlight that, to buy shares on the market is less expensive than to buy company assets according to accounting data that is evaluated at a higher value. Of course, this analysis disregards the fact that, as a result of increased demand for stocks, the share price would rise. However, the maintenance of a situation in which the relationship between book value and market value is > 1 must be analysed to understand what the causes of this mismatch are and to identify which elements influence the expectations of the market. The analysis is performed by tying the annual yield of each company to two components. The first is identified by tangible information derived from financial statement data that should summarise past performance and growth prospects, while the second is derived from information on unrecognised intangibles or on the related reactions of investors to the realisation of unpredictable events in the current year that influence the development of share prices.

We will refer to a year in which, at time t-1, the yield at time t is not known and is a random

variable that will be denoted by . Using the suggested decomposition, it is possible to define the following equation:

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11, 1, 1, 1,

T I

tr t t E r t t r t t r t t

(1)

where:

1 1,tE r t t

represents the expected return on the period 1,t t ;

1,Tr t t

is the random variable that represents the return due to tangible elements;

1,Ir t t is the random variable that represents the return due to intangible elements.

Similar to what it is suggested by DANIEL AND TITMAN (2006), it is assumed that the logarithm of

the book value to market value ratio at time t is a proxy for the return on time 1,t t and it is assumed that this proxy follows a Markov stochastic process. This means that, at time t, all the information about the past evolution will be contained in the information known at time t-1, which immediately precedes it.

Indicating with:

Bt the book value at time t,

Mt the market price at time t,

the following equation is given:

1

1 1 1

log log log logt t t t

t t t t

B B B MM M B M

(2)

where:

1

1

log t

t

BM

, known at t-1 time, is a proxy of the expected return on 1,t t period;

1

log t

t

BB

is a proxy of the book value return on 1,t t period;

1

log t

t

MM

is a proxy of the expected return linked to intangible information.

The proposed model is based on the decomposition of the logarithm inversion of the valuation ratio in the sum of three different components each of them has a precise financial meaning.

The analysis will consider the effect of temporal regression based on the official data published in the financial statements of the banks of the sample.

To improve the model some adjustments have been made. For example an adjustment for the dividends distributed in the period analysed. Considering this adjustment the final equation may be written as:

bmt=bmt−1+rb ( t−1 ,t )−ri ( t−1, t ) (3)

where:

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log tt

t

B bmM

1

log ( 1, )t t tb

t

B D Nr t t

B

1

log ( 1, )ti

t

M r t tM

This formula has been applied for every banks of the sample (cfr.3.1.) and has been also used to obtain a global evaluation.

3.1 Data

The data used to verify the effectiveness of the proposed model, for analysing the impact of intangible information on the valuation ratio, refer only, at this first stage, to the Italian bank and insurance sector. In particular, data has been taken from the financial statements of the listed Italian banks and insurances that apply IFRS to present their annual results. There are 17 listed banks and 7 listed insurances in the sample and their names are given in the Appendix. To improve the significance of the intangibles disclosure ratios, the details existing in the financial statements are integrated with some data presented in the social and environment reports. This integration determines a relevant effect on the results of the model because, in some cases, companies give in their official financial statements very few data on unrecognized intangible assets: this choice – derived also by the IAS-IFRS prescriptions - determines lower values of the disclosure ratios with a different impact on the allocation of entity income in the three components of the formula (2).

To obtain the indexes on the disclosure level of unrecognised intangibles, used in the proposed formula, all the information on intangibles in financial statements and in social and environment accounts have been used according to a multi-stakeholder approach. The steps are: the creation of a stakeholders list and of KPI indicators, the definition of a score that should be assigned to every company referring to the existence or the absence of positive value to some KPIs defined, considering the GRI model principles; the composition of the final list that joins to every companies its score (the results are in Appendix).

Both Mediobanca data and historical amounts derived from the market and from financial statements have been used to define book value and market value.

3.2 Results

There are more levels of analysis that are used to validate the model proposed: the first refers to the application of the formula (3) to every bank and insurance and to the analysis of the correlation of the main variables of the model (tab. 3.2.1.a., tab.3.2.1.b., tab.3.2.2.), the second refers to the match of information of unrecognised intangibles and the performance of intangible proxy (tab. 3.2.3.a. and 3.2.3.b) and the last concerns the relationship between risk and intangibles.

Considering the first aspect there are two results that worth to remember. The application of formula (3) to every companies for the 2006 – 2011 period has shown that, in the years following the financial crisis (2010-2011), market evaluation has heavily penalized the bank sector and that it is very difficult to attribute this penalty to the information given in the

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financial statements referring to intangibles. The situation is a bit different in the previous period in which the increase of intangibles information could have determined a better market value. To complete this analysis it has been verified the level of correlation between the model variables: the results may be summarised in the following tables:

Tab.3.2.1.a. – bank sector

bmt bmt-1 rb(t-1,t) ri(t-1,t)

bmt 1 0.74139-

0.14213 -0.32919

bmt-1 1-

0.19805 0.343466rb(t-1,t) 1 0.016486ri(t-1,t) 1

Tab.3.2.1.b. – insurance sector

bmt bmt-1 rb(t-1,t) ri(t-1,t)

bmt 1 0.870013-

0.11238 -0.23114

bmt-1 1-

0.20001 0.256465rb(t-1,t) 1 0.103517

ri(t-1,t) 1

There are no relevant differences between the correlation index in the bank and in the insurance sector.

The results obtained are in line with what is generally known in financial literature. The negative correlation between the variables bmt, and rb (t-1, t) shows that increases in the distribution of earnings negatively affect the relationship between book value and market value. The negative correlation between detected bmt and ri (t-1, t) is clearly due to the fact that in correspondence to increases in market value, the ratio between book value and market value must necessarily decrease. It may be also noted that, since both the variable bmt-1 and rb

(t-1, t) are positively correlated with intangible information level, the increasing of transparency in in financial statements should be read positively by the market. The limited number of observations on which the analysis is based do not allow to use, at this stage, the results for forecasting purposes. The thing can be said with enough certainty is that, if some negative events do not intervene in the market, referring to Italian banks for which the B/M ratio 2011 is lower than the same ratio in 2010, it could be possible that, for the future, there will be a new rapprochement of the book value and the market value. It is also important to note that at the level of single entities the relationship existing for the whole sample is not necessary true (as it is possible to verify from Annex 2).

The results of the following analyses on the correlation between the proxy results of tangible and intangible assets are shown in Tab.3.2.2. It should be remembered that the component of equation (3) - that identifies the proxy of the return joined to intangibles information – is influenced both by some unpredictable events for the entire market and by the investor reactions on the information provided in financial statements. In this section, the correlation between the information relating to intangible assets not accounted for and the proxy performance information associated with intangibles is determined for each bank of the

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sample. The analysis was performed assuming as indicators of the level of information regarding unrecognised intangible assets, for each bank, the sum of the values assigned to the detailed information and general information contained in the banks' balance sheets for the years 2008, 2009 and 2010 determined applying the multi-stakeholders analysis and refers to the impact that this data has on the market in the following year. In practice, it is assumed that the information contained in the 2008 budget has an effect on stock prices of the year 2009 and so on.

The results of the analysis on the correlation and covariance between the proxy results of intangibles and indicators for banks are shown in the following table:

Table 3.2.2. – bank sector

correlation covB.1 -0.67772 -0.07593B.2 - 0B.3 -0.99959 -0.28882B.4 - 0B.5 - 0B.6 - 0B.7 - 0B.8 - 0B.9 - 0B.10 - 0B.11 -0.95424 -0.21128B.12 - 0B.13 - 0B.14 -0.8207 -020318B.15 - 0B.16 - 0B.17 - 0

It is easy to deduct that if the ratio referring to unrecognised intangibles is stable, to define a relationship between the proxy of intangibles income and the level of the information existing in the financial statements for these assets is not possible. While a relevant negative correlation exists when the disclosure, presented in the financial statements, relating to intangibles increases. In different words, if you have more disclosure on intangibles, a lower influence on market return exists.

The results of the comparison between the intangibles ratio and the income relating to these assets, as determined using the proposed model, are shown in the following table referring the bank sector:

Tab.3.2.3.a bank sector

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Intangibles ratioIntangibles income proxy

2008 2009 2010 2009 2010 2011

B.1 20 18 20-0.07057

-0.00675

-0.28461

B.2 57 57 570.062622

-0.42265

0.129938

B.3 26 28 290.323513

-0.06007

-0.23045

B.4 53 53 53 0.12118 -0.1302-0.01578

B.5 22 22 220.374186

-0.13375

-0.49794

B.6 53 53 53 -0.0045

-0.33323

-0.28145

B.7 52 52 52-0.07444

-0.38142 -0.4594

B.8 49 49 490.006844

-0.25303

-1.00403

B.9 17 17 170.186362

-0.15916

-0.52982

B.10 63 63 630.216206

-0.40211

-0.09268

B.11 27 29 290.190677 -0.1987

-0.37071

B.12 51 51 51 -0.2037

-0.36673

-0.46813

B.13 57 57 570.196506

-0.61333

1.083433

B.14 29 29 330.086578

-0.09717

-0.23387

B.15 28 28 280.096321

-0.10647

0.045173

B.16. 58 58 580.021878

-0.38793

-0.28914

B.17 51 51 510.689264

-0.21096

-3.16337

Correlation index

-0.13835

-0.79664

0.028913

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It is also possible to argue that if, in the period 2009 -2011, the results referring to the intangibles income proxy are compared to the intangibles income proxy of the previous year, the sign of correlation changes in 2011 (the sign is negative in 2009-2010 and positive in 2011). However, it may be observed that a higher value of the 2011 ratios do not determine a lower value of the intangibles income proxy.

The results of the comparison between the intangibles ratio and the income relating to these assets, as determined using the proposed model, are shown in table 3.2.3.b referring to the insurance sector:

Tab.3.2.3.b insurance sector

Intangibles ratio Intangible income proxy2008 2009 2010 2009 2010 2011

I.1 61 61 61 0.040655 -0.22125 -0.27547I.2 67 67 67 -0.1416 -0.57287 -0.67764I.3 62 62 62 0.089485 -0.28097 -0.20036I.4 57 57 57 0.366268 -0.34204 -0.03578I.5 21 21 21 -0.07171 -0.54981 -0.01434I.6 44 44 44 -0.12292 -0.25353 -0.61496I.7 22 22 22 0.012019 -0.06436 -0.16834

correlation index0.22731 -0.18539 -0.42302

Relating to the insurance sector, it should be noted the substantial stability of the level of disclosure referring to intangibles assets. This stability does not permit to analyze from a statistical point of view the relationship between the amount of income referring to intangibles and the information given.

From the analysis of the data collected, it can be deducted that:

- the correlation is positive in 2009,

- the correlation is negative in 2010 and 2011. In these two years the ratio values move in a different manner from the intangibles income proxy. It can be deducted that the companies with a higher value in disclosure show a lower intangible income proxy.

3.3 Concerns on the impact of intangibles information on non-systemic risk

The risk joined with market return is generally measured in listed shares with the return variance. In the hypothesis of CAPM3, the variance may be classified in two components: the 3 F. Black, M. Jensen, M. Sholes, The capital asset pricing model: some empirical tests, Studies in the Theory of Capital Markets, New York, 1972 Black F.Campbell . y., Vuolteenaho T., Bad beta good beta, American Economics Review, vol. 94, n.5, 2004 pp.1249-1275; Cordazzo M., L’impatto borsistico dell’informativa sugli intangibili, Franco Angeli ed., Milano, 2007; Mossin J., Equilibrium in a Capital Asset Market, in Econometrica, vol.34, n.4, 1966, pp768-783; Ross S. A., The arbitrage theory of capital asset pricing , Journal of Economic Theory, vol 13, 1976 pp. 341-360; Sharpe W.F., Capital asset prices: a theory of market equilibrium under conditions of risk, Journal of Finance, vol. 19, 1964, pp. 425-442.

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systematic risk (that is referred to events that interest the whole market and all the entities that belong to that market) and the non-systematic risk (that measures the risk of a specific company and that is also dependent to the disclosure level offered by the company to market operators). Part of the developed analysis – that it should be further implemented - tries to verify if the data referring to unrecognized intangibles shown in financial statements have influence on banks and insurances companies un-systematic risk .

In this part of analysis, a dynamic model is used and this model is based on two stochastic processes: the first one refers to the time evolution of the performance of tangible assets and assets recognized in financial statements, the second is related to the evolution of the market return which also incorporates information relating to unrecognized intangible assets. Using a hypothesis in the consolidated financial practice, it is assumed that both the book value and the market value will follow a stochastic process of multiplicative Brownian type.

The results obtained, at this first stage, show a difference between insurance and bank sector. For the banks, the correlation between past information and return index is always negative: this evidence suggests that an increase in the information level on intangibles in financial statements determines a decrease in the unsystematic risk. It is also interesting to notice that the correlation value decreases in the period examined and this seems to suggest an increasing attention of the investors in information on intangibles that is not accounted for in the financial statements. The results obtained for the insurance companies are not satisfactory at this stage because they show an increase of the correlation between the variables and a transition from negative values to positive values: this is probably connected with constancy of the level of information offered by the sector in relation to intangibles.

From this first step analysis, it can be also inferred that the information relating to unrecognized intangible do not produce certain effects on the variability of the valuation ratio: for companies for which the intangible information ratios are negatively correlated with the market yield, a greater disclosure could produce a decrease in the expected market return but also a decrease in variance; for companies for which the information ratios relating to unrecognized intangibles are positively correlated with the market yield on the market, a greater disclosure could cause an increase in the expected market return expected.

4. Limitation of the analysis and possible evolutions

The limits of the model and of the practical application – which could be removed with a further level of analysis - may be summarized as follows:

- the lack of analysis of the links and possible interrelations between existing information on recorded and unrecorded intangibles and the contents of the notes of banks in terms of risks and their management;

- the absence of a specific analysis referring to the existence and to the effects of any impairment operated by companies during the reporting period.

On the basis of what has been reported, this analysis could be further improved both from the theoretical and practical points of view. Theoretically, the analysis of the valuation of intangible assets could be expanded to verify whether and how the adoption of different valuation models 'flips' the existing level of disclosure. It could also implement the evaluation choice solution, considering a larger number of indicators, especially those related to the financial sector.

From the practical point of view, improvements could include: increasing the number of banks and insurance in the sample, to include foreign entities that adopt IAS-IFRS to check for any

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differences in approach within the financial sector itself; improving the comparison between the relevance of the data provided in financial statements at the end of the year and those reported in the environmental and social budgets; increasing the numbers of companies considered including industrial sector; developing a more detailed mathematical model to assess the relationship between book value and market value in view of the existence of a certain level of information on intangibles.

References

C.A.ADAMS, A commentary on corporate social responsibility reporting and reputational risk management, Accounting, Auditing & Accountability Journal, vol.21, 3, 2008

W.BEAVER, C.EGER, S.RYAN, M.WOLFSON, Financial Reporting, Supplemental Disclosures and Bank Share Prices, Journal of Accounting Research, n.32, 1989, pag. 157-178

A.DAMODARAN, Invisible Value? Valuing companies with Intangible assets, 2009

A.DAMODARAN, Valuing financial service Firms, 2009 version, available on www. people.stern.nyu.edu/adamodar

K.DANIEL, S.TITMAN, Market reaction to tangible and intangible information, in Journal of Finance, n. 4, 2006, pp.1605-1643

W.F.M. DE BONDT, R.H. THALER R.H., Does the stock market overreact?, Journal of Finance, n.40, 1985

DE BONDT, R.H. THALER R.H, Further evidence on investor overreaction and stock market seasonality, in Journal of Finance, n. 42, 1987, pp.557-581

O. DEEV, Methods of Bank Valuation, A Critical Overview, Financial Assets and Banking, n.3, 2011

EUROPEAN ON FINANCIAL ANALYSTS SOCIETIES, Key Performance Indicators for Environmental, Social & Governance Issues: A Guideline for the Integration of ESG into Financial Analysis and Corporate Evaluation, 2009

GLOBAL REPORTING INITIATIVE, G3 Guideline Reporting Framework, 2009

IASB, IAS 38

IASB, IFRS 3

B.LEV, Intangibles: Management, Measurement and Reporting, Brookings Institution Press, 2001

B.LEV, J.H.DAUM, The dominance of intangibles assets: consequences for enterprises management and corporate reporting, Measuring Business Excellence, vol. 8, 2004

H.ISIDRO, D.GRILO, Value driving activities in Euro-zone banks, ……..

M.KALECHI, The Principle of Increasing risk, Economica, New Series Vol.4, N.16, Nov 1937, pp.440-447

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E.F. FAMA, K.R. KENNET, The cross-section of expected stock returns, Journal of Finance, n. 47, 1992, pp.427-465

E.F. FAMA, K.R. KENNET, Common risk factors in the returns on stocks and bonds, Journal of Financial Economics, n. 33, 1993, pp.3-56

E.F. FAMA, K.R. KENNET, Size and book-to-market factors in earnings and returns, in Journal of Finance, n. 50, 1995, pp.131-156

E.F. FAMA, K.R. KENNET, Market efficiency, long-term returns and behavioral finance, Journal of Financial Economics n. 49, 1998, pp.283-306

F.FIORDELISI, P.MOLYNEUX, Shareholder value in banking, Palgrave MacMillian, London, 2006

J.M.KOLBECK, Investor Valuations and Measuring Bank Intangibles Assets, Journal of Accounting, Audit and Finance, vol.19, 29, 2004, pp. 29- 60

J.M.KOLBECK, T.D.WARFIELD, Unrecorded Intangibles Assets: Abnormal Earnings and Valuation, Accounting Horizon, vol.21, n.1, pagg.23-41, 2007

Z.MATOLCSY, A.WYATT, Capitalized Intangibles and Financial Analysts, Intellectual Property Research Institute of Australia, Working Paper, n.4/2005

D. ZEGHAL, A. MAALOUD, The accounting treatments of intangibles – A critical review of the literature, Accounting Forum, val.35, n.4, 2011

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Appendix 1 – List of the banks and insurances in the sample

B.1 BANCO DESIO BRIANZAB.2 BANCO POPOLARE B.3 BANCO DI SARDEGNAB.4 CARIGEB.5 CREDEMB.6 CREDITO ARTIGIANOB.7 CREDITO VALTELLINESEB.8 BANCA ETRURIAB.9 FINNATB.10 BANCA INTESAB.11 MEDIOBANCAB.12 MONTE DEI PASCHI DI SIENAB.13 BANCO POPOLARE DI MILANOB.14 BANCO POPOLARE EMILIA ROMAGNAB.15BANCA POPOLARE DI SONDRIOB.16 UBI BANCAB.17UNICREDIT

I.1 CATTOLICA ASSICURAZIONII.2 FONSAII.3 ASSICURAZIONI GENERALI I.4 MEDIOLANUMI.5 MILANO ASSICURAZIONII.6 UNIPOL ASSICURAZIONI (UGF)I.7 VITTORIA ASSICURAZIONI

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Appendix 2 –-Statistichal data

B.1 IM EQUITY

2006 480.888.000 937.805.945 -0.668

2007 634.162.000 808.593.481 -0.243 -0.668 0.516 -0.148

2008 671.794.000 533.671.958 0.230 -0.243 0.132 -0.416

2009 731.263.000 497.306.539 0.386 0.230 0.143 -0.071

2010 754.360.000 493.960.348 0.423 0.386 0.077 -0.007

2011 745.679.000 371.609.528 0.696 0.423 0.027 -0.285

2012 776.469.066 254.675.112 1.115 0.696 0.046 -0.378

Statistical data for , , ,

Expectation from 2007 to 2012 0.435 0.137 0.157 -0.217

Standard deviation 0.455 0.502 0.182 0.167

Correlation

1 0.939069 -0.83634 -0.37451

1 -0.87665 -0.05562

1 0.246026

1

14

B.2 IM EQUITY

2006

2007 9.635.661.851 6.503.191.182 0.393

2008 8.681.348.000 2.220.038.871 1.364 0.393 -0.104 -1.075

2009 10.355.274.000 2.363.507.418 1.477 1.364 0.181 0.063

2010 10.476.505.000 1.548.818.423 1.912 1.477 0.034 -0.423

2011 7.755.998.008 1.763.729.753 1.481 1.912 -0.301 0.130

2012 7.016.670.373 2.218.773.346 1.151 1.481 -0.100 0.230


Expectation from 2008 to 20124 1.477 1.325 -0.058 -0.215

Standard deviation 0.277 0.562 0.179 0.542

Correlation

1 0.198027 0.291516 -0.22617

1 -0.20531 0.863691

1 -0.03953

1

4 listed since 200715

B.3- IM EQUITY

2006 1.039.194.253 766.427.142 0,304

2007 1.133.065.982 720.830.884 0,452 0,304 0,135 -0,061

2008 1.164.987.349 361.375.391 1,171 0,452 0,057 -0,690

2009 1.188.224.688 499.411.351 0,867 1,171 0,041 0,324

2010 1.156.663.226 470.297.220 0,900 0,867 -0,023 -0,060

2011 1.164.180.575 373.500.241 1,137 0,900 0,019 -0,230

2012 1.127.402.667 363.797.256 1,131 1,137 -0,032 -0,026


Expectation from 2007 to 2012 0,943 0,805 0,033 -0,124

Standard deviation 0,273 0,355 0,061 0,332

Correlation

1 0,444219 -0,6918 -0,43873

1 -0,76507 0,607905

1 -0,11981

1

16

B.4 IM EQUITY

2006 2.758.605.204 3.571.118.496 -0,258

2007 2.921.663.105 3.577.417.134 -0,202 -0,258 0,079 0,002

2008 3.725.809.868 2.450.023.971 0,419 -0,202 0,264 -0,379

2009 3.929.599.671 2.765.656.066 0,351 0,419 0,067 0,121

2010 3.813.226.598 2.428.016.687 0,451 0,351 -0,017 -0,130

2011 3.200.374.266 2.389.994.848 0,292 0,451 -0,168 -0,016

2012 3.985.253.763 1.678.635.551 0,865 0,292 0,219 -0,353




Correlation

1 0,502837 0,333824 -0,60954

1 -0,56133 0,319732

1 -0,67956

1

17

B.5 IM EQUITY

2006 1.171.394.069 2.588.563.974 -0,793

2007 1.348.304.588 2.349.358.328 -0,555 -0,793 0,257 -0,097

2008 1.589.602.350 1.143.063.217 0,330 -0,555 0,259 -0,720

2009 1.615.035.420 1.661.794.339 -0,029 0,330 0,032 0,374

2010 1.592.122.725 1.453.750.119 0,091 -0,029 0,011 -0,134

2011 1.524.513.811 883.564.699 0,545 0,091 -0,002 -0,498

2012 1.715.329.053 1.373.444.186 0,222 0,545 0,130 0,441


Expectation from 2007 to 2012 0,101 -0,068 0,114 -0,106


Correlation

1 0,470961 -0,43347 -0,36367

1 -0,70993 0,6376

1 -0,25458

1

18

B.6 IM EQUITY

2006 446.082.799 295.770.067 0,411

2007 463.811.054 301.750.685 0,430 0,411 0,061 0,020

2008 779.905.476 443.761.897 0,564 0,430 0,545 0,386

2009 759.040.440 441.768.358 0,541 0,564 -0,004 -0,005

2010 759.556.299 316.574.076 0,875 0,541 0,027 -0,333

2011 891.276.715 238.915.153 1,317 0,875 0,194 -0,281

2012




Correlation

1 0,923625 -0,01036 -0,67599

1 -0,13734 -0,62939

1 0,705998

1

5 There is a merger with B.7 in 201219

B.7 IM EQUITY

2006 870.459.433 761.311.443 0,134

2007 1.549.240.404 1.187.088.202 0,266 0,134 0,581 0,444

2008 1.690.594.000 1.125.545.748 0,407 0,266 0,099 -0,053

2009 1.965.009.000 1.044.805.595 0,632 0,407 0,167 -0,074

2010 2.083.414.000 713.487.642 1,072 0,632 0,061 -0,381

2011 1.900.165.946 450.683.420 1,439 1,072 -0,086 -0,459

2012 1.944.780.727 516.384.953 1,326 1,439 0,023 0,136




Correlation

1 0,922824 -0,79436 -0,61916

1 -0,69321 -0,3173

1 0,815045

1

20

B.8 IM EQUITY

2006 469.204.000 717.205.556 -0,424

2007 523.567.066 437.065.255 0,181 -0,424 0,161 -0,495

2008 677.013.974 277.098.486 0,893 0,181 0,275 -0,456

2009 685.130.538 279.001.573 0,898 0,893 0,012 0,007

2010 691.121.267 216.628.463 1,160 0,898 0,020 -0,253

2011 668.869.160 79.373.018 2,131 1,160 0,003 -1,004

2012 595.614.937 1.645.386.263 -1,016 2,131 -0,116 3,032


Expectation from 2007 to 2012 0,708 0,807 0,059 0,138


Correlation

1 -0,25892 0,250229 -0,8593

1 -0,86721 0,714021

1 -0,61273

1

21

B.9 IM EQUITY

2006 115.883.000 322.999.488 -1,025

2007 185.636.000 279.671.616 -0,410 -1,025 0,804 -0,144

2008 194.672.000 165.799.872 0,161 -0,410 0,048 -0,523

2009 174.494.000 199.765.440 -0,135 0,161 -0,027 0,186

2010 176.395.000 170.372.160 0,035 -0,135 0,012 -0,159

2011 199.425.044 100.300.032 0,687 0,035 0,125 -0,530

2012 204.593.285 97.542.144 0,741 0,687 0,048 -0,028




Correlation

1 0,749597 -0,52513 -0,3506

1 -0,76715 0,294212

1 -0,03093

1

22

B.10 IM EQUITY

2006 15.323.151.911 28.875.522.443 -0,634

2007 48.441.995.036 52.393.970.364 -0,078 -0,634 1,170 0,596

2008 45.718.734.618 26.770.249.940 0,535 -0,078 -0,035 -0,672

2009 47.785.009.966 33.231.461.431 0,363 0,535 0,061 0,216

2010 48.849.207.808 22.228.868.254 0,787 0,363 0,048 -0,402

2011 44.270.913.231 20.261.197.913 0,782 0,787 -0,098 -0,093

2012 44.290.051.639 21.364.203.531 0,729 0,782 -6,320 0,053


Expectation from 2007 to 2012 0,520 0,293 -0,863 -0,050


Correlation

1 0,813985 -0,44768 -0,68911

1 -0,55574 -0,23909

1 0,0211

1

23

B.11 IM EQUITY

2006 5.479.374.900 11.670.710.612 -0,756

2007 6.098.880.236 9.613.181.794 -0,455 -0,756 0,116 -0,194

2008 5.249.990.089 5.591.369.138 -0,063 -0,455 -0,133 -0,542

2009 4.641.229.696 6.765.938.967 -0,377 -0,063 -0,119 0,191

2010 4.919.643.871 5.546.708.607 -0,120 -0,377 0,079 -0,199

2011 4.938.669.517 3.828.580.477 0,255 -0,120 0,006 -0,371

2012 4.421.588.075 4.014.584.386 0,097 0,255 -0,111 0,047


Expectation from 2007 to 2012 -0,111 -0,253 -0,027 -0,178


Correlation

1 0,560505 -0,2437 -0,36821

1 -0,62052 0,516109

1 -0,17186

1

24

B.12 IM EQUITY

2006 7.674.526.000 8.619.861.975 -0,116

2007 7.661.460.000 6.695.758.206 0,135 -0,116 0,047 -0,253

2008 14.239.323.417 8.313.278.511 0,538 0,135 0,670 0,216

2009 16.589.926.595 6.781.167.298 0,895 0,538 0,163 -0,204

2010 15.621.429.263 4.699.306.601 1,201 0,895 -0,049 -0,367

2011 9.408.929.459 2.942.579.852 1,162 1,201 -0,507 -0,468

2012 9.408.929.459 2.636.523.512 1,272 1,162 -0,604 -0,110




Correlation

1 0,96239 -0,63099 -0,36801

1 -0,78856 -0,48583

1 0,658759

1

25

B.13 IM EQUITY

2006 3.058.298.502 1.473.786.554 0,730

2007 3.247.164.004 1.074.897.155 1,106 0,730 0,112 -0,316

2008 3.052.313.711 508.416.933 1,792 1,106 -0,050 -0,749

2009 3.667.245.246 618.816.038 1,779 1,792 0,194 0,197

2010 3.653.520.252 335.115.564 2,389 1,779 0,007 -0,613

2011 4.012.600.697 990.201.915 1,399 2,389 0,094 1,083

2012 3.928.874.660 1.459.788.863 0,990 1,399 -0,021 0,388




Correlation

1 0,307253 -0,09176 -0,49601

1 0,246683 0,666651

1 0,402871

1

26

B.14 IM EQUITY

2006 2.532.898.000 4.047.837.293 -0,469

2007 2.449.519.000 3.595.777.261 -0,384 -0,469 0,000 -0,118

2008 2.398.890.000 2.293.354.424 0,045 -0,384 -0,011 -0,450

2009 2.488.757.000 2.500.757.814 -0,005 0,045 0,079 0,087

2010 2.684.627.000 2.269.194.924 0,168 -0,005 0,124 -0,097

2011 3.254.457.000 1.795.990.669 0,594 0,168 0,227 -0,234

2012 3.254.457.000 1.740.134.256 0,626 0,594 0,000 -0,032




Correlation

1 0,861562 0,45452 -0,00931

1 0,269145 0,468488

1 0,064195

1

27

B.15 IM EQUITY

2006 1.338.125.000 2.151.049.014 -0,475

2007 1.592.236.000 2.769.510.830 -0,554 -0,475 0,212 0,253

2008 1.492.021.195 1.814.837.558 -0,196 -0,554 -0,062 -0,423

2009 1.683.715.881 1.998.339.683 -0,171 -0,196 0,172 0,096

2010 1.722.830.035 1.796.502.753 -0,042 -0,171 0,062 -0,106

2011 1.676.472.699 1.879.517.820 -0,114 -0,042 -0,010 0,045

2012 1.711.323.846 1.349.688.174 0,237 -0,114 0,030 -0,331


Expectation from 2007 to 2012 -0,140 -0,259 0,067 -0,078


Correlation

1 0,652578 -0,53605 -0,65469

1 -0,08458 0,10729

1 0,804769

1

28

B.16 IM EQUITY

2006 4.166.564.401 5.343.133.118 -0,249

2007 10.962.140.301 9.285.959.066 0,166 -0,249 0,986 0,553

2008 10.358.681.650 5.371.637.819 0,657 0,166 -0,056 -0,547

2009 10.662.230.000 5.490.455.042 0,664 0,657 0,046 0,022

2010 10.328.266.000 3.725.070.146 1,020 0,664 -0,011 -0,388

2011 7.609.828.759 2.789.733.948 1,003 1,020 -0,305 -0,289

2012 8.607.720.373 3.161.525.000 1,002 1,003 -3,740 0,125




Correlation

1 0,91197 -0,58017 -0,62385

1 -0,64253 -0,35546

1 -0,02059

1

29

B.17 IM EQUITY

2006 31.433.443.503 325.026.697.298 -2,336

2007 50.619.820.930 367.685.250.628 -1,983 -2,336 0,481 0,123

2008 50.989.663.132 119.620.671.562 -0,853 -1,983 0,070 -1,123

2009 54.091.949.125 238.314.243.545 -1,483 -0,853 0,060 0,689

2010 57.771.134.386 192.989.327.537 -1,206 -1,483 0,070 -0,211

2011 49.649.325.295 8.160.173.803 1,806 -1,206 -0,152 -3,163

2012 57.989.269.191 21.456.020.527 0,994 1,806 0,155 0,967




Correlation

1 0,561464 -0,63941 -0,52912

1 -0,17179 0,399846

1 0,604135

1

30

I.1 Equity

2006 1.114.890.578 1.930.898.715 -0,549

2007 1.286.854.938 1.621.289.957 -0,231 -0,549 0,154 -0,175

2008 1.140.864.505 1.173.684.963 -0,028 -0,231 -0,120 -0,323

2009 1.265.436.081 1.222.384.619 0,035 -0,028 0,164 0,041

2010 1.286.934.645 979.762.907 0,273 0,035 0,031 -0,221

2011 1.243.890.697 743.848.269 0,514 0,273 -0,033 -0,275

2012 1.302.713.822 663.342.777 0,675 0,514 0,066 -0,115




Correlation

1 0,974036 -0,23392 -0,036

1 -0,17515 0,12425

1 0,841649

1

31

I.2 Equity

2006 2.819.446.743 9.534.908.384 -1,218

2007 2.791.071.414 7.069.222.604 -0,929 -1,218 0,038 -0,299

2008 2.600.544.385 3.180.361.937 -0,201 -0,929 -0,060 -0,799

2009 2.526.281.767 2.760.447.454 -0,089 -0,201 -0,027 -0,142

2010 1.822.481.345 1.556.630.239 0,158 -0,089 -0,327 -0,573

2011 1.251.352.709 790.481.409 0,459 0,158 -0,376 -0,678

2012 1.627.332.680 1.180.181.553 0,321 0,459 0,263 0,401


Expectation from 2007 to 2012 -0,047 -0,303 -0,081 -0,348


Correlation

1 0,908601 -0,31034 0,073736

1 -0,0564 0,443569

1 0,797283

1

32

I.3 Equity

2006 10.435.443.839 38.612.601.358 -1,308

2007 10.914.701.412 43.690.867.575 -1,387 -1,308 0,057 0,124

2008 10.627.238.218 26.792.161.193 -0,925 -1,387 0,048 -0,489

2009 13.803.124.676 29.300.189.570 -0,753 -0,925 0,269 0,089

2010 14.958.588.614 22.123.169.351 -0,391 -0,753 0,083 -0,281

2011 14.585.033.002 18.106.436.281 -0,216 -0,391 -0,021 -0,200

2012 14.405.470.595 21.391.438.908 -0,395 -0,216 -0,011 0,167




Correlation

1 0,856214 -0,26872 -0,17283

1 -0,35791 0,314472

1 0,203267

1

33

I.4 Equity

2006 548.196.502 4.515.355.741 -2,109

2007 509.011.975 4.001.904.946 -2,062 -2,109 0,078 -0,121

2008 592.027.069 2.212.191.210 -1,318 -2,062 0,352 -0,593

2009 599.722.419 3.190.735.026 -1,672 -1,318 0,117 0,366

2010 584.909.791 2.266.431.276 -1,355 -1,672 0,156 -0,342

2011 642.897.146 2.186.781.711 -1,224 -1,355 0,279 -0,036

2012 675.064.906 2.815.451.581 -1,428 -1,224 0,132 0,253




Correlation

1 0,392751 0,729117 -0,2674

1 -0,17718 0,771234

1 -0,6154

1

34

I.5 Equity

2006 1.605.664.622 1.838.243.746 -0,135

2007 1.761.805.034 1.645.764.253 0,068 -0,135 0,127 -0,111

2008 2.044.557.029 825.328.080 0,907 0,068 0,152 -0,690

2009 1.977.064.874 768.216.224 0,945 0,907 -0,033 -0,072

2010 1.411.262.296 443.307.992 1,158 0,945 -0,337 -0,550

2011 977.710.929 436.996.749 0,805 1,158 -0,367 -0,014

2012 894.788.866 610.667.464 0,382 0,805 -0,089 0,335




Correlation

1 0,542462 -0,47852 -0,57488

1 -0,87213 0,328007

1 -0,1342

1

35

I.6 IM Equity

2006 5.280.319.434 113.927.238.858 -3,072

2007 5.333.578.426 99.739.208.353 -2,929 -3,072 0,028 -0,133

2008 4.330.892.720 45.946.230.517 -2,362 -2,929 -0,208 -0,775

2009 4.459.712.023 40.631.764.295 -2,209 -2,362 0,036 -0,123

2010 4.696.085.378 31.532.661.262 -1,904 -2,209 0,052 -0,254

2011 4.337.909.170 17.048.536.676 -1,369 -1,904 -0,079 -0,615

2012 5.632.554.401 1.090.559.696 1,642 -1,369 0,276 -2,749




Correlation

1 0,890376 0,725791 -0,94874

1 0,6612 -0,70891

1 -0,60712

1

36

I.7 Equity

2006 173.110.130 183.466.344 -0,058

2007 215.362.367 204.163.050 0,053 -0,058 0,353 0,107

2008 259.677.382 252.049.000 0,030 0,053 0,285 0,211

2009 272.893.102 255.096.646 0,067 0,030 0,097 0,012

2010 294.780.600 239.195.180 0,209 0,067 0,136 -0,064

2011 318.655.451 202.136.772 0,455 0,209 0,212 -0,168

2012 364.683.049 328.674.391 0,104 0,455 0,136 0,486


Expectation from 2007 to 2012 0,153 0,126 0,203 0,097


correlation

1 0,15901 0,07274 -0,63414

1 -0,339 0,66093

1 -0,34674

1

37

paper draft (to be further implemented) - aidea 2013 · web viewthis affects the valuation ratio...

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