fair value disclosure, liquidity risk and stock returns.

Transcript

Oliviero Roggi
University of Florence
Via delle pandette, 9
50127 Firenze
[email protected]
Alessandro Giannozzi*
University of Florence
Via delle pandette, 9
50127 Firenze
[email protected]
*Corresponding author
Abstract
The paper aims to explore the role of the fair value hierarchy as useful information tool
in estimating the liquidity risk of an asset. We investigate the existence of a relationship
between the three levels of fair value and the investors’ reaction (313 financial and non
financial companies listed on the Eurostoxx Index) during an event of liquidity
expansion or liquidity contraction. The usefulness to investors of liquidity risk
information is analyzed by tracing investors’ reactions to 103 events during the
financial crisis (2008-2010) using fixed effects model and PLS regression. Our findings
demonstrate that investors’ firm-specific reaction to the crisis events is influenced by
the three-level of fair value hierarchy. It is also demonstrated that investors react
according to the level of liquidity risk in both financial and non-financial firms. During
liquidity-constraining events, investors’ negative reaction is stronger for the most
illiquid assets and liabilities (Level 3) than for the liquid ones. During liquidityexpanding events, investors react more positively to the most illiquid assets (Level 3)
than to the liquid ones (Level 1 and 2).
Keyword: Liquidity Risk, Fair value disclosure, stock returns
JEL CODES: G18, M40, G30
Fair value disclosure, liquiditiy risk and stock returns
1. Introduction
The 2007-2010 time frame has been the scene of major economic upheavals which have
profoundly marked the financial world. Events with high economic impact have
occurred, such as the collapse of Lehman Brothers, which experts considered highly
unlikely in the financial sector. These events have led to high volatility in the financial
markets which has caused losses and the spreading a fear of a depression amongst
investors of comparable to that of 1929. For the above mentioned reasons it is
interesting to deepen the understanding of the causes of this financial crisis, focusing on
the risk of corporate liquidity. In particular, it seems that there could be a relationship
between this type of risk and the information provided by the companies to the markets
on the toxic assets held in their balance sheet.
The value of financial instruments, as is known, is measured according to the fair value
principle. The international standard setters (IASB and FASB) have agreed that the
evaluation of such balance sheet items can be achieved through the use of different
methodologies and in accordance with a liquidity criterion of the evaluated financial
instruments.
As is known, the first form of assessment used for financial instruments is the price at
which it is listed in a liquid and active market (the so called mark-to-market or 1st
level). Securities assessed in this manner are classified in the first level of Fair Value
Hierarchy and according to standard setters their price represents the nearest concept to
that of fair value. If market prices are not available, the nearest approximation of a
security’s fair value is the price of a similar financial instrument listed in a liquid and
active market or the price of a recent and similar transaction between knowledgeable
and willing parties (2° level). In the event that such information is unavailable, a
security’s fair value can be estimated by using financial and statistical models of
common acceptance (the so called mark-to-model or 3rd level). This last technique may
require the imposition of unrealistic assumptions causing the generation of errors and /
or information asymmetry between the firm and the financial markets. By defining
liquidity risk as the inability to raise new funds (funding liquidity) or to liquidate assets
on the market at an "expected price” (asset liquidity risk) (Brunnermeier, 2007), Level
1 of the Fair Value Hierarchy appears to be the most liquid since it is made up of
assets/liabilities whose values are based on their market price. In contrast, the value of
securities included in Level 3 of the Fair Value Hierarchy is calculated through
“internal” models, resulting in assets/liabilities with a higher liquidity risk. The higher
the level 3 amounts are, the greater the assets’ liquidity risk will be and therefore the
higher the total liquidity risk of the company linked to the uncertainty of disinvesting
securities at a “predictable price” (Brunnermeier 2007). Assuming the existence of the
link described above and the presence of a contraction of liquidity on the financial
markets (as happened during the 2008 financial crisis) investors tend to penalize illiquid
companies (i.e. ones with large amounts of Level 3). In fact, low liquidity levels on the
financial markets lessen the possibility of disinvesting assets at a predictable price,
causing serious consequences for companies. The increased uncertainty should generate
a negative impact on company’s value. In an efficient financial market this would be
reflected in stock prices. Therefore, a high level of liquidity risk may cause a decline in
corporate stock prices. In particular, there may be situations in which the assumptions
on which the models are built result particularly unrealistic. This is what happened
during the recent financial crisis. Activities and / or liabilities may become illiquid, i.e.
investors may not trust most of the securities’ assessments and may decide to no longer
include theme in their portfolios.
The main goal of this paper is to explore the role of the fair value hierarchy as an
information tool in calculating the liquidity risk of a security/company. In particular, the
existence of a relationship between the three levels of fair value and the reaction of
investors when a liquidity-constraining or liquidity-expanding event occurs is
investigated. This will allow the understanding of whether fair value hierarchy properly
informed investors of firms'liquidity risk or whether, ultimately, its introduction by the
international standard setter has been useful for investors.
Lev & Zhou (2009) have contributed to the debate on fair value accounting by
analyzing the separation of financial assets and liabilities into three liquidity levels. In
particular, they investigated investors’ reaction to crisis events during the last months of
2008 (the peak of the financial crisis) based on the fair value disclosures of 3,929 U.S.
financial and nonfinancial companies under SFAS 157. They demonstrated a complex
reaction to the liquidity risk information conveyed by the three fair value levels.
Starting from Lev & Zhou’s (2009) hypotheses, investors’ reaction to crisis events in
European firms under IAS 39 and IFRS 7 are analyzed. Moreover, this analysis is
conducted between February 17th, 2008 and June 22nd, 2010. In addition, a non
parametric methodology (PLS regression) is applied to test the robustness of the
models
The paper is structured as follows. In Section 2, a survey of the most relevant fair value
literature is provided. Sections 3 and 4 illustrate our research design and the data
sample. Sections 5 and 6 are dedicated to the measurement of investors’ reaction to
crisis events. In particular, the group of crisis events and the cumulative abnormal
returns (CARs) are introduced. In Section 7, our hypotheses are stated. Section 8
provides the results of the empirical analysis. In Section 9, the final conclusions are
stated.
2. A Summary on Fair Value Literature
Starting in the early nineties, extensive research has been carried out on the use of
market prices for asset and liability pricing.
First of all it must be stated that researchers have focused primarily on the valuerelevance of fair value. For value-relevance we intend the ability of fair value data to
incrementally explain the behavior of the stock prices. Mary E. Barth1 (1994) supports
the existence of a strong relationship between these two variables and believes that
banks’ stock prices changes can be measured by the use of the securities at market
value. This important result was confirmed by Barth, Landsman and Wahlen2 (1996).
They demonstrate that when banks’ net profits are measured using Fair value
accounting, they result more volatile than those calculated with historical cost asset
valuations. Barth, Landsman and Wahlen (1996) also demonstrate that banks violate
regulatory capital requirements more frequently when using Fair Value Accounting than
when using Historical Cost Accounting. In 1996, Barth, Beaver and Landsman3 noted
1
Barth, M. E. (1994), “Fair value accounting: evidence from investment securities and the market valuation of
banks”, The Accounting Review, Vol. 69, January, pp. 1-25.
2
Barth, M. E. and Landsman W. R. and Wahlen J. M. (1995), “Fair Value Accounting: Effects on Banks'Earnings
Volatility, Regulatory Capital, and Value of Contractual Cash Flows”, Journal of Banking and Finance, Vol. 19, pp.
577-605.
3
Barth, M. E. and Beaver W. H. and Landsman W. R. (1996), “Value-relevance of banks’ fair value disclosures
under SFAS No. 107”, Accounting review, Vol. 1, pp. 513-537.
that bank stock prices are partly explained by the difference between estimated fair
value under SFAS 107 and the current book value.
Unlike previous researches, Barth, Beaver and Landsman (1996) noted for the first time
that the additional explanation required by SFAS 107 significantly affected bank stock
prices. By the contrary in the same year, Eccher, Ramesh and Thiagarajan4 (1996),
performed an analysis in which the historical cost seemed to have a higher explanatory
power over bank stock prices, both in absolute and in relative terms. Previously, Beaver
and Landsman5 (1983), Beaver and Ryan6 (1985) and Bernard and Ruland7 (1987) had
found that the estimated fair value calculated for certain types of assets according to
SFAS 33, had no incremental explanatory power over bank stock prices than had their
book value. In addition, other studies such as Murdoch8 (1986), In 1996 Cornett, Rezaee
andTehranian9, investigating the impact on stock prices of 23 fair value accounting
(FVA) statements issued by financial institutions demonstrated how the increases
(decreases) caused by the likelihood of a new emission of FVA standards are followed
by negative (positive) abnormal returns on bank stock prices.
During the following years numerous studies were conducted on the value-relevance of
Accounting standards. Holthausen and Watts10 (2001) are critical of all research
conducted thus far, stating that these studies offer little support to the standard setter,
since they fail to create a generalized descriptive theory.
4
Eccher, E. A. and Ramesh K. and Thiagarajan S. R. (1996), “Fair value disclosures by bank holding companies”,
Journal of Accounting and Economics, Vol. 22, pp. 79-117.
5
Beaver, W. H. and Landsman W. R. (1983), “Incremental information content of Statement 33 disclosures”, FASB:
Stamford, Connecticut.
6
Beaver, W. H. and Ryan S. (1985), “How well do Statement No. 33 earnings explain stock returns?”, Journal of
Financial Analysts, Vol. 41, September/October, pp. 66-71.
7
Bernard, V. L. and Ruland R. (1987), “The incremental information content of historical cost and current cost
income numbers: time series analyses for 1962-1980”, The Accounting Review, Vol. 62, October, pp. 707-722.
8
Murdoch, B. (1986), “The information content of FAS 33 returns on equity”, The Accounting Review, Vol. 61, No.
April, pp. 273-287.
9
Cornett, M. M. and Rezaee Z. and Tehranian H. (1996), “An investigation of capital market reactions to
pronouncements on fair value accounting”, Journal of Accounting and Economics, Vol. 22, pp. 119-154.
10
Holthausen, R. W. and Watts R. L. (2001), “The relevance of the value-relevance literature for financial accounting
standard setting”, Journal of Accounting and Economics Vol. 18, pp. 3-75.
Barlev and Haddad11 (2003) state the need to evaluate financial reports based on the
benefit investors gain by the reduction of agency costs and the improved efficiency in
corporate control that these reports are able to offer. In fact, they argue that Historical
Cost Accounting offers ample room for balance sheet manipulation, leading to an
incorrect display of the current situation and so reinforcing the relevance of Fair Value
Accounting.. Fair Value Accounting draws attention to equity and its variations and,
therefore, managers should be asked to better monitor the "health" of equity itself, its
maintenance and the profits it generates. With the application of FVA, Barlev and
Barlev and Haddad (2003) suggest that managers create an additional financial report,
which is to indicate the operations conducted by the firm in order to maintain equity.
Historical Cost Accounting induces managers to create hidden reserves of capital to
cover, if necessary, administrative errors, increasing agency costs. Morevoer, historical
Cost Accounting distorts the financial ratios on which creditors concentrate their
attention, such as the long term debt coverage ratio and the interest coverage ratio.
Barlev and Haddad (2003) claim that FVA has another important feature: it stimulates
management to better understand and study the market, making them face a global,
open and competitive environment, and therefore inducing them to be more competent.
Freixas and Tsomocos12 (2004), historical cost allows the distribution of a higher
amount of bank dividends over time. According to these scholars, in fact, the bank'
s role
as institutional intervenor of intertemporal smoothing may worsen with the use of fair
value accounting. Generally, it is believed that a sufficiently high level of criminal
manager prosecution incentives managers to report accurate and correct values in
balance sheets. If moral hazard and information asymmetry are very high, the current
value (fair value) could thus increase market discipline, inducing managers to make the
right decisions. According to these scholars, if this method of measurement is correctly
used it could prevent systemic crises since information on financial issues is obtained
prior
than with Historical Cost Accounting. Fair Value Accounting creates lower
bankruptcy costs for the environment because it promotes the bankruptcy of Distress
companies, preventing them from prolonging their existence and redistributing their
Barlev B. and Haddad J. R. (2003), “Fair value accounting and the management of the firm”, Critical Perspectives
on Acccouting Vol. 14, No.1, 383-415.
Freixas, X. and Tsomocos D. (2004), “Book vs. fair value accounting in banking, and intertemporal smoothing”,
Oxford Financial Research Centre working paper.
resources amongst healthy companies. This will also prevent banks from betting on the
survival of Distress companies and investing in their equity and supporting high risks.
Tsomocos and Freixas (2004) observe, however, that the use of fair value increases the
volatility of bank profits and lacks accuracy since it relies on subjective judgments for
the assessment of illiquid items. Banks insure themselves against unforeseen
contingencies through their dividend policy, building up reserves in times of economic
prosperity and using them in times of crisis, in order to equalize the amount of
dividends paid to shareholders over time. By using fair value, banks might be tempted
to shift their focus on stakeholders’ short-term interests, even though regulation could
prevent this from happening through the imposition of stricter rules. According to
Freixas and Tsomocos (2004), the adoption of fair value measurements induces bank
managers who expect temporary adverse shocks in bank stock prices to act in a
conservative way, such as not investing in risky assets, reducing interest rates on
deposits or choosing not to distribute dividends by reducing intertemporal smoothing.
Landsman (2006) identifies key issues that standard setters should seriously consider. In
particular a key issue is related to how to minimize management'
s manipulation on
economic and statistical models used to assess financial instruments classified in the 3rd
level of Fair Value Hierarchy. In addition, Landsman (2006) clarifies that the
institutional differences in the implementation of Fair Value Accounting will play an
important role towards an effective and efficient use of the above mentioned evaluation
system. Landsman also emphasizes the need to assess the incremental explanation that
the disclosure required by the standard setter offers shareholders. .
Allen and Carletti13 (2007) demonstrate that there is a possibility that Fair Value
Accounting can lead to a contagion effect between banks and insurance and that in
times of crisis this contagion is not desirable, since it could then lead non-Distress banks
to be insolvent. This is because markets can be illiquid even when prices are
continuous, since in some cases a further increase in the demand or in the offer can
cause a significant price change. Allen and Carletti (2007) argue that during an
economic crisis, relatively low prices could lead asset managers to aim towards
achieving liquidity objectives rather than to reflect on future cash flows that can be
generated from such assets. In this case, Historical Cost Accounting is certainly more
13
Allen, F. and Carletti E. (2007), “Mark-to-market accounting and liquidity pricing”, Journal of Accounting and
Economics Vol. 45, No. 1, pp. 358-378.
efficient. Therefore, when there is an economic crisis and the evaluation system is not
adjusted for illiquidity, the only way to mitigate a contagion effect is to temporarily
suspend the application of Fair Value Accounting. In their subsequent study, Allen and
Carletti14 (2008) add that Fair Value Accounting should be used particularly when asset
prices collapse due to fundamental reasons, i.e. the falling expectations on future cash
flows which are reflected in stock prices. Allen and Carletti (2008) also clarify that
there are more damaging effects when prices collapse and the historical cost accounting
method is being used. According to these authors, standard setters should rightly apply
Fair Value Accounting even in periods of illiquidity providing some corrections for Fair
Value Accountings’ aforementioned shortcomings. Allen and Carletti (2008) propose to
supplement market valuations with asset value estimated by financial models and by
Historical Cost Accounting. This in order to inform investors on the cash flows
generated by the associated securities and on the ability of banks to reclassify their
assets at historical cost (i.e. from Available For Sale to Held To Maturity). The
incremental disclosure requested by Allen and Carletti (2008) would prevent bank
managers’ moral hazard, which would then lead them to reclassify assets even in non
illiquid periods in order to park risky and volatile (but profitable) assets in bank balance
sheets, basically implementing arbitrage regulation.
While some sustain that the historical cost leads to some forms of inefficiencies, others
believe that the market value could inject artificial risks in the economic system,
degrading the value of the information included in prices and causing sub-optimal
choices. Plantin, Sapra and Shin15 (2008) found that the damage caused by the market
value reaches its maximum value when this method is used for the assessment of longterm illiquid and senior instruments which form a large portion of banks’ assets. In
reviewing previous literature, the abovementioned authors pointed out the inadequacy
of pricing certain asset categories below market value, particularly, for the asset
categories assessed on OTC markets. The IMF study16 of 2008 states that standard
setters are following the correct direction with the implementation of Fair Value
14
Allen, F. and Carletti E. (2008), “Should financial institutions mark to market?”, Banque de France Financial
Stability Review, October.
15
Plantin, G. and Sapra H. and Shin H. S. (2008), “Marking-to-market: panacea or Pandora’s box?”, Journal of
Accounting Research, Vol. 46, No. 21, pp. 435-460.
16
International Monetary Fund (2008), Global financial stability report. Chapter 3: Fair value accounting and
procyclicality, October.
Accounting, despite the difficulties caused by the measurement and the volatility that it
entails. This is explained by the better assessment of the company'
s financial situation
(especially for financial firms), which is obtained through the use of market prices, even
though, according to the IMF (2008) this accounting method, must be improved. For
the IMF (2008), Fair Value Accounting allows investors to have greater transparency on
the effects of the economic volatility on company’s perfomances, exacerbating cyclical
movements. According to this institution, if high profits result in poor incentives for
management in times of economic prosperity, it is also true that insecure evaluations
could damage corporate funding in times of crisis, resulting in lower levels of available
credit. All this to emphasize the need to apply specific crisis covenants and limitations
to short term gains during periods of economic prosperity. The IMF (2008) also points
out that the balance sheet of a highly capitalized company is more resistant to market
fluctuations, especially when there is a large amount of assets assessed at market value
rather than when are liabilities valued with the same method. Similarly, the cyclical
volatility of corporate financial statements is exacerbated when, with the use of market
prices as accounting method, there is a severe lack of liquidity in corporate balance
sheets. The IMF (2008) therefore suggests that, in addition to having sufficient
capitalization and liquidity, companies should counterbalance their total assets at fair
value with a similar set of liabilities, in order to alleviate the pro-cyclicality of corporate
balance sheets.
Laux and Leuze17 (2009) affirm that counter-cyclical capital requirements are a better
solution to the difficulties brought forth by Fair Value Accounting. According to these
authors, we must investigate the interrelationships between Fair Value Accounting and
financial crises: for example, implementation problems of this accounting method and,
particularly, the risks of litigation, which may have played a key role in the recent
financial crisis should be better explored. Laux and Leuze (2009), in fact, suggest that
the current crisis may have been exacerbated by transparency issues on the financial
markets (especially banks) rather than by the overreaction to Fair Value Accounting: in
times of economic prosperity banks are unable to increase their leverage ratio both with
Fair Value Accounting and Historical Cost Accounting. This may contrast the critics of
Fair Value Accounting, who see a high distortion for securities held to maturity (HTM)
Laux, C. and Leuz C. (2009), “The crisis of fair value accounting: making sense of the recent debate”, Accounting,
Organizations and Society, Vol. 34, pp. 826–834.
and consider this method as scarcely credible and reliable if obtained with the use of
models. By using Historical Cost Accounting, managers have an information advantage
over their controllers. This can lead to management issues , since it is difficult to give
managers flexibility without sustaining any risk of free riding. Laux and Leuze (2009)
argue, therefore, that it is correct to give more flexibility to business managers only if
the two parties (the controller and the agent) have the same set of information.
Otherwise, more stringent accounting standards or possible contagion effects on
financial companies are the price to pay for correct market signals to investors.
According to Penman18 (2006), the FAS 157 considers fair value as an exit value,
raising two main questions: the first consists of the pertinence of fair value in capturing
value for shareholders and the second relies on the possibility of applying it to the
aggregates of assets and liabilities. In his paper, Penman (2006) distinguishes what the
advantages and disadvantages of using the fair value are. In the event that shareholder
value is created only by the exposure to market prices, Fair Value Accounting leads to
favor the shareholders. The disadvantages, according to this author, reside in the
possible mismatch between asset and liability evaluations (i.e. when different types of
security assessments are used), in the possible introduction of financial bubbles in
corporate accounts, in the total replacement of information that can be derived from the
historical price (the price, in fact, also depends on the historical price and not only on
the information gathered with the market price) with that gathered from the market. In
his opinion, the primary issue is not to determine which between the historical cost and
the market price constitutes the best evaluation system,
since these two types of
accounting methods function differently . The historical cost, in fact, according to
Penman (2006) is able to better predict a company’s future earnings when compared to
the market price. It also concentrates investors’ attention on the income statement
rather than on equity as happens with the use of market price. With Historical Cost
Accounting the value of a company depends on its profitability and not on the
subsequent equity changes. Historical cost accounting also does not include the present
value of projected revenues, but exclusively recognizes the benefits of adding value to
18
Penman, S. (2006), “Financial Reporting Quality: Is Fair Value a Plus or a Minus?”, paper for presentation at the
Information for Better Markets Conference Institute of Chartered Accountants in England and Wales, December 18th19th.
traded goods and transactions. Penman also argues that Historical Cost Accounting
should be used in its natural frame-work, and only here can it be correctly judged.
3. Data sample
In the data sample reference is made to the European context as it represents the largest
geographical area which applies the accounting standards issued by the IASB. The
companies chosen for the sample are those listed in the Eurostoxx index. The Stoxx
indexes have a high level of liquidity. They are widely used in financial practice as
"underlying" financial instruments such as ETFs, futures, options and structured products
and as a benchmark for measuring risk and corporate performance. The Eurostoxx index
consists of a variable number of small, medium and largely capitalized companies located
in 12 Eurozone countries (Austria, Belgium, Finland, France, Germany, Greece, Ireland,
Italy, Luxembourg, Netherlands, Portugal and Spain).
The sample used for the analysis consisted of 313 companies listed in the Eurostoxx
index. The observation period is the 2008, 2009 and 2010 fiscal years.
Because the 2008 economic crisis started in the financial sector and subsequently
spilled over to the real sector, we study the two sectors separately. Two subsamples are
built based on the dataset, both for financial and non-financial firms since financial data
differs substantially between these two categories of firms, as can be seen from the
descriptive statistics shown in the Appendix. In fact, there is a relevant difference
between the values of financial firms’ balance sheet items measured at fair value and the
values of those that are not. Also a much stronger leverage is noticeable in all three
periods for financial firms. The latter achieve a lower ROA than non-financial firms,
while the values of operating activities vary in the three years considered. Further, the
values at fair value of financial firms weighed significantly on the total (55.1% and
28.9% for assets to liabilities) than weighed those made of non-financial firms. In
subsequent years a drastic drop of these percentages for both sub-samples is evident,
due to the financial crisis. In 2007 the EBIT of non financial enterprises is higher than
that of financial enterprises, who were profiting greatly due to the pre-crisis situation on
the credit markets. In the 2008 financial statements of non-financial companies a higher
average value of the statistics is noticeable, as is shown in the Appendix, since these
firms were slightly more affected by the financial crisis. In 2009, thanks to the
reclassification and stabilization of the financial markets, the financial companies’ are
back to recording a higher average EBIT.
Considering the medians of the various hierarchical levels of fair value, it is noticeable
that level 3 Assets has higher relevance for financial firms than that of the non-financial
companies.. The sum of the percentages of the medians of levels 2 and 3 of the financial
firms is always higher than when compared to non-financial corporations.
4. Research design
According to Fama, Fisher, Jensen e Roll (1969) and Ball e Brown (1968), our analysis
takes the form of a typical event study19. Here below a summary of our research design:
1. Sample selection and data collection (stock market prices, Fair value assets and
liabilities, ect…)
2. Identification of liquidity-contracting and liquidity-expanding events in the
period 2008-2009-2010 and aggregation in event groups
3. Estimation of the abnormal returns (dependent variable) after each crisis event.
4. Check of the statistical significance of each event by ANOVA (ANalysis Of
VAriance)
5. Regression analysis using fixed effects model and Partial Least Square (PLS) as
robustness check, separately for financial and non-financial companies.
To test our hypotheses an OLS regression was carried out for the group of financial
companies, for that of non-financial companies and for the full sample of companies:
CAR = α + β 1 ∗ fair _ value _ assets _ level1 + β 2 ∗ fair _ value _ assets _ level 2 +
+ β 3 ∗ fair _ value _ assets _ level 3 + .... + β n ∗ x n
19
MacKinlay, A. C. (1997), “Event studies in economics and finance”, Journal of Economic Literature,
Vol. 35, No. 1, pp. 1-39; Binder, J. J. (1998), “The event study methodology since 1969”, Review of
Quantitative Finance and Accounting, Vol. 11, pp. 111–137; Fama, E. F. and Fisher L. and Jensen M. C.
and Roll R. (1969), “The adjustment of stock prices to new information”, International Economic Review,
Vol. 10, No. 1, pp. 1-21; Ball, R. and Brown P. (1968), “An empirical evaluation of accounting income
numbers”, Journal of Accounting Research, Vol. 6, No. 2, pp. 159–78; Brown, S. J. and Warner J. B.
(1985), “Using daily stock returns: the case of event studies”, Journal of Financial Economics, Vol. 14,
No. 1, pp. 3–31.
For each event group three regressions are run: the aforementioned regression, the
aforementioned regression with fixed effect correction and, finally, a regression which
compounds the possibility to reclassify assets/liabilities at their historical cost
introduced by the IASB in mid-October 2008. Each regression is run with and without
the control variables.
5. Crisis events
In the period from February 2nd , 2008 to June 22nd , 20 we identified 103 crisis events.
Appendix (Table 13) provides a brief description of each event.
Furthermore, according to Lev & Zhou (2009) a two-day event window for stock return
computation is used. In particular, it is assumed that the effects of each individual event
terminate within a two day period (the same day and the next). The mean cumulative
event returns (MCRs) are calculated to measure the stock market reaction to the 103
crisis events. In general, the direction of investors’ reaction in both financial and Nonfinancial firms was identical—negative to alarming events, like the Fannie and Freddie
takeover or Lehman’s implosion. Nevertheless certain events were apparently perceived
as beneficial to financial firms yet harmful to non-financial firms and vice versa.
In order to identify the statistical significance of the above described events, we apply a
widely used techniques in social sciences, the ANalysis Of Variance (ANOVA), This
approach allow us to eliminate non-statistically significant events which could
adversely affect the results of the analysis. Four different one-way ANOVAs
(monofactorial) were conducted by using the following samples:
•
Fair Value and Non Fair Value samples for financial companies
•
Fair Value and Non Fair Value samples for non-financial companies
•
Fair Value and Non Fair Value samples for all the companies
•
Fair Value samples of financial firms and Fair Value samples of nonfinancial
corporations.
The crisis events that did not report any statistical significance are excluded from the
analysis. After this process, 54 events were considered in the analysis. Then, we
classified the 54 crisis events into three groups according to their nature:
•
Rescue;
•
Distress;
•
Capital injections.
The first group consists of events in which financial institutions have been financially
helped or bailed out. The second group classifies all financial adverse events that
occurred during the period (bank troubles, fraud, ect). The third group includes events in
which injections of capital were operated by Central Banks and by the American and
European governments. This group includes interest rate cuts from the major Central
Banks, liquidity injections, legislative actions and policy announcements, the TARP
program, ext.
6. Measuring investors' reaction to crisis events
The investors’ reaction to fair value hierarchy was measured through the concept of
mean cumulative abnormal returns (CARs). The use of abnormal returns as the
dependent variable is strongly supported by the main academic literature. In this case,
the abnormal returns were calculated as follows:
(1)
Where
CARsij = the mean cumulative returns at the event j for the i-th firm;
T = the number of trading days covered by the event;
Rit = the rate of return at day t of the i-th firm
REt = the return of the Eurostoxx index at the day t.
7. Our Hypotheses
Non-financial companies
The fair value assets of non-financial companies pertain generally to non-core
businesses and they are retained in balance sheets exclusively for liquidity and hedging
purposes. These assets are highly liquid and mainly classified in levels 1 and 2 of the
fair value hierarchy. When liquidity-restrictive events occur, investors tend to require
liquid securities, causing a consequent increase in the value of the assets held by nonfinancial companies, according to the phenomenon better known as flight to quality20.
By the contrary, the fair valued liabilities of non-financial companies consist mainly of
relatively illiquid instruments such as mortgage-backed securities, whose values tend to
decrease in constraining liquidity events. Investors’ reactions to fair-valued liabilities of
nonfinancial firms are more complex. For liquidity-constraining events, the value of
liabilities will decrease, due to heightened default risk of firms, benefiting shareholders.
On the other hand, in a liquidity crunch, firms will be less able to rollover (refinancing
risk) their short-term liabilities, thereby damaging investors. Thus, investors’ overall
reaction in liquidity-constraining events to the liabilities of nonfinancial firms primarily
depends on the maturity of the liabilities (Lev & Zhou 1999). If the firm’s fair-valued
liabilities are primarily short-term, investors will react negatively (rollover concerns),
whereas if most liabilities are long-term and of Levels 1 or 2 quality, investors will react
positively (credit risk or default concerns). Due to this ambiguous behavior, we will not
consider the impact of fair-valued liabilities of nonfinancial firms. Thus:
Proposition 1: when liquidity constraining events occur, investors will react21
positively to the levels 1 and 2 fair value assets and will not react (or only mildly
and negatively) to Level 3 fair value assets
20
Lev, B. and Zhou N. (2009), “Unintended Consequence: Fair Value Accounting Informs on Liquidity Risk”,
forthcoming; Acharya V.V. and Richardson M. (2009), “Causes of the financial crisis”, Critical Review Vol. 21, Nos.
2–3, pp. 195-210.
21
We have to remember that we assess the investors’ reaction over the abnormal returns on companies’ s share
prices.
According to this statement, the stock market prices of non-financial companies should
behave in the opposite way when positive events occur, i.e. they would diminish in
expansive liquidity-events.
Proposition 1-bis: when expansive liquidity-events occur, investors will react
negatively to levels 1 and 2 of fair value assets and do not react (or only mildly
and positively) to Level 3 assets.
Financial companies
In financial firms, there is a greater concentration of financial instruments classified in
levels 2 and 3 (such as CDOs, Mortgage-Backed Securities…) of the fair value
hierarchy than the latter, as shown in the descriptive statistics in the Appendix. Level 3
assets are more illiquid and present higher levels of information asymmetry than level 1
and level 2 assets. Liquidity constraining events would have, therefore, a negative effect
on the stock prices of financial firms. More illiquid the assets of financial firms, the
greater investors’ negative reaction is . The following hypothesis is reached:
Proposition 2: when liquidity-constraining events occur, investors will react
negatively to fair value assets and more strongly to those classified in level 3.
Clearly, the opposite is true for positive events.
Proposition 2-bis: when liquidity-expanding events occur, financial company
investors react positively to fair value assets and more strongly to those
classified in level 3.
Financial companies’ liabilities are less illiquid than their assets. Further, there is a large
government insurance on customers’ deposits. Because of these two considerations, the
following statement must be considered:
Proposition 3: when positive and negative liquidity events occur, investors do
not react to the level 1 and 2 fair value liabilities and react mildly to level 3
liabilities.
.
8. The relevance of Fair Value Hierarchy on European Companies’ stock
returns
8.1.
The behavior of financial firms
The results of the empirical analysis for financial companies are shown in the appendix
(tables 17, 20 and 23).
Rescue group
The hypothesis supporting the influence on stock prices of financial companies’ fair
value assets during rescue events (assumption 2-bis), appears to not be confirmed. In
fact a negative and highly significant (99%) pattern
22
in is reported in L3A for the
rescue group. This is confirmed by the result obtained by the control regressions which
show a large number of significant coefficients which present the same pattern. In
particular, the OLS calculated with the use of a dummy finds significant coefficients for
L1L and L3L with an F-statistic significant at 99%. This is the opposite of what one
might expect, given that the bank bailouts should be expansive liquidity events.
The OLS regression thus confirm the negative signs of the coefficients and leads us to
state that the bank bailouts are events with specific characteristics. These features do
not allow us to assimilate them conceptually to the other expanding-liquidity events. A
possible explanation for the aforementioned results may reside in a negative perception
of the investor'
s "rescue risk/risk of nationalization" which is strongly felt in banks with
substantial exposure to Level 3 assets. In fact, the stock prices of these banks could
"include” the fact of being the next to be saved and have to undergo governmental
interference in their management. Attention must be brought to the fact that the
financial sector tends to be somewhat opaque and that a greater control by the savior
state is not the as good as a bank might expect. This is confirmed by the fact that in the
rescue group there are no significant values for non-financial firms.
Level 3 Liabilities shows a negative coefficient in each of the performed regressions. As
mentioned above, this result could be due to investors’ perception of a greater level of
22
We remember that negative pattern is defined as a decrease from level 1 to level 3 of the values of the coefficients
and, similarly, positive pattern is a growth between the two values.
"risk of nationalization" for banks with a liability of Level 3, often without insurance. In
the regression with the control variables the leverage coefficient is negative and highly
significant. Thus, the investors’ negative reaction, in the presence of bank bailouts, is
stronger for heavily indebted institutions. This supports the belief of the existence of a
"rescue risk" described above.
Distress group
The events that make up this group are all liquidity-constraining and hence, as
mentioned above, they have negative coefficients. Furthermore, lower levels in the fair
value hierarchy (levels 2 and 3) should correspond to lower values in the OLS
coefficients calculated above. However, the OLS regression shows positive coefficients
for levels 1 and 3 and negative sign for the second level of assets. Clearly, hypothesis 2bis is not verified and this could be given by the fact that the Distress group reported the
lower number of observations than any of the other event groups. In fact statistical
significance is not detected with the analysis carried out on this set of events. We can
ultimately recognize that there is a negative pattern in the levels of fair value (i.e., going
from level 1 to level 3) and this confirms that equity prices have been hampered by the
reaction of investors to companies liquidity risk.
The three coefficients of liabilities in the OLS regression (L1L, L2L and L3L) drive us
to confirm hypothesis 3. In fact, despite the different sign of the coefficients of L1L
(which is negative) and L2L (which is positive), the coefficients show absolute values
that are much lower than L3L, which as expected, has negative sign.
Capital injections group
The coefficients generated from the capital injections group confirm hypothesis 2-bis.
With the OLS regression a positive pattern between the asset levels show positive
values for levels 2 and 3. In particular, level 3 has a positive coefficient higher than the
level 1 and is significant at 90%. This is confirmed in the regression with control
variables. Morevoer, hypothesis 3 is not confirmed. The rescue group and the capital
injections group are the most significant (in the dummy-regression of the capital
injections group L2L and L3L are significant at 95% while in the rescue group L1L and
3 are significant at 90 % and 95% respectively).This leads to the rejection of the idea
that financial companies’ stock prices are not influenced by the levels of fair value
liabilities.
8.2.
The behavior of non-financial companies
The results of the empirical analysis for non-financial companies are shown in the
appendix (tables 18, 21 and 24).
Rescue group
The bank bailouts do not seem to have an impact on non-financial firms. In fact, there
were no significant factors except in the case of a level of liabilities that seems to have
some negative influence on stock prices.
Distress group
There were no significant coefficients in any of the performed regressions. However,
the coefficient of L3A is mostly negative and higher than that of L1A, partly supporting
proposition 1. investors’ reaction to liquidity constraining events is negative and the
stronger it is, the higher the level of the fair value hierarchy (i.e. level 3). The "flight to
quality" phenomenon in non-financial companies is not confirmed because the
coefficient of L1L is negative in the ordinary OLS and positive in that with fixed effects
for the distress group. We can notice a negative pattern (between L1A and L3A) for
both assets and liabilities in this group. Not being able to benefit from the comparison
with the dummy regression coefficients, we can only compare ordinary OLS
coefficients with OLS fixed effects coefficients. Even here we can see that investors are
not indifferent to the assets assessed at fair value because the coefficients of L3A are
relevant and negative. In the regression with control variables, the coefficients of L1A
and L2A, although not statistically significant, are positive and lead us to hypothesize a
positive reaction of investors to such assets, as proposed in Proposition 1.
As for liabilities, the signs of the regression coefficients lead to the belief that investors
have not experienced a refinancing risk for non-financial firms.
Capital injections group
The dummy-regression and the regression with fixed effects support hypothesis 1-bis
due to the negative sign of the coefficients of L1A and L2A. When liquidity-expanding
events occur, the fair value coefficients show an increasing trend from level 1 to level 3
of fair value assets. We cannot investigate liabilities due to their aforementioned
ambiguous behavior when events which restrict global liquidity occur. Similarly to Lev
and Zhou (2009), both the pattern and the positive coefficients of L2L and L3L for the
rescue group suggest that the positive reaction resulting from improved credit risk
(default) may have prevailed over the negative risk of refinancing (rollover). This is not
followed by a similar pattern of the levels of liabilities of the capital injections group,
which also contains expansionary liquidity events.
8.3. Robustness checks
Regressions with control variables
We replicate all the regression analysis reported above using control variables. We
believe important to determine what happens if control variables are included into the
analysis to anchor the strong negative trends in stock prices during the financial crisis to
some key financial information. This analysis is intended to strengthen what has been
previously found, although a lower statistical significance should be expected as some
information is “captured” by the control regressors.
According to the previous literature, the control variables used are:
1. EBIT;
2. ROA;
3. NET CASH FLOW FROM OPERATING ACTIVITIES;
4. LEVERAGE
By analyzing the results reported in the appendix (table 20 and 21), we can confirm the
previous considerations illustrated in section 8.2.
The PLS Regression
The PLS methodology is often used in the analysis of panel data which is here used as a
robustness check.Unlike the Multiple Linear Regression, the Multiple Logistic Analysis
and the Principal Components Analysis (PCA), PLS regression is not disturbed by the
collinearity amongst regressors. Unlike OLS regression, using the PLS regression the
number of observations can be less than the number of regressors since predictors are
correlated and redundant and therefore, the number of fully effective predictors is lower.
PLS points out, in fact, some pseudo-components from the X factors able to explain the
Y factors. These pseudo-components are extracted in descending order of importance
and are defined “pseudo” because they are bound. In particular, these pseudocomponents (also known as latent carriers or PLS factors or components) perform a
simultaneous decomposition of independent variables (X) and dependent (Y), with the
condition that they explain the covariance between X and Y. With such a constraint we
have therefore a generalization of the PCA23.
23
The number of PLS components to be extracted can be arbitrarily decided in accordance with the percentage of
explained variance or, preferably, determined through the method of cross validation. Using the variance, we can use
two measures for choosing the number of PLS components. These are:
1). The standard deviation of the residuals
n
RMSEa
Root Mean Square Errora
se , a
yi
2
yˆ i , a .
i 1
2). The square root of the Prediction Error Sum of Squares
n
PRESSa
yi
yˆ (
2
i ), a
i 1
where yˆ (
i ), a
is the prediction of the response obtained without using the ima observation in the model. The PLS
algorithm starts with a standardization of the columns of the X matrix of order n * Jx and the Y matrix of order n *
Jy, in order to allow a comparison between the variables. The following describes the PLS procedure when the
dependent variable is one.
An initial PLS component of order n*1 is constructed as follows:
t1
w11x1
w12 x 2
w1 j x j
w1 J x J
x
x
(1)
with t1 column vector of order n*1 and the coefficients w1j calculated to take into account the links of each variable X
with the dependent variable, ie
The PLS (Partial Least Square) regression methodology is applied to test the robustness
of our analysis. Two types of PLS regression for the calculation of coefficients are
performed:
one using the maximum number of vectors;
one employing a cross validation24 to decide the number of vectors that must be
used in the analysis.
cov x j , y
w1 j
Jx
j
2
cov x j , y
1
.
(2)
A simple ordinary regression without intercept is now calculated, as
y
c1t1
y1
(3)
where c1 is the slope and y1 the vector of the regression residuals. The third step is the replacement of (1) in (3) to
find the first equation of the PLS regression
y
c1 w11 x1
c1 w12 x 2
c1 w1 j x j
c1 w1 J x J
x
x
y1
(4)
whose coefficients are easily interpretable. If the fitting quality of the regression is low, a second component PLS t2
as a linear combination of residuals x1j of the Jx ordinary regressions without intercept of the individual variables on
PLS component t1 can be built. The new component t2 is not linked to the first component t1 and tries to explain the
residue of the previous regression y1 as much as possible. The result is
t2
w21 x11
w22 x12
w2 j x1 j
w2 J x1 J
x
(5)
x
In which the coefficients are:
w2 j
cov x1 j , y1
Jx
j 1
2
cov x1 j , y1
As one can easily guess it goes on to perform a similar regression to (3), or y
.
c1 t 1
c2t 2
y 2.
t1 and t2 are now replaced in this last formula by using the previous expressions, generating a second PLS
regression. We can understand that this iterative process can continue to be carried out on residues y2 and x21, …, x2j,
…, x2J of the regressions of the response y and that of the original variables x1, …, x2, …, xJ on t1 and t2.
Generalizing, we can describe the PLS regression methodology with
y
c1 t 1
c2t 2
.....
cAt A + y A.
(6)
i.e. the dependent variable is the weighted sum of A PLS components plus a residual yA.
24
The cross validation method verifies how the model reconstructs the observations kept aside and is not
used for the model construction. The observations are divided into two groups. The first and largest,
The results of the above analysis, which can be found in the Appendix, confirm our
previous results. PLS regression shows for non-financial companies the same pattern
previously discussed in sections 8.1 and 8.2. Finally, the full sample of firms confirms
the negative pattern for the rescue and Distress group and a positive pattern for the
capital injections group. The pattern still persists in both methods, indicating their
previously reported strength.
7. Conclusions and further considerations
The introduction of the fair value hierarchy was initially defined as a positive form of
investor intervention. In fact, IAS 39 and IFRS 7 allow the use of different methods for
the assessment of financial instruments. Some of them might be based on unrealistic
assumptions (as in the case of all financial instruments attributable to the Level 3 of Fair
Value Hierarchy), returning values that might not be suitable to study asset values in
years of high volatility such as those of the recent financial crisis. The fair value
hierarchy would provide a greater transparency in evaluating of financial instruments,
establishing first, the use of market prices and last, the so called mark-to-model, helping
investors understand the amount of information asymmetry contained in a balance
sheet.
In particular, with the arising of securities classified in the lower levels of the hierarchy
these fair value levels indicate the presence of an increased liquidity risk. This allow
investors to understand the overall liquidity risk of the company. We analyzed
investors’ reactions when liquidity expansive and liquidity restrictive events occurred.
We compared our results using OLS regression, fixed effects models and an OLS that
considers the possibility of reclassifications allowed by the IASB in mid-October 2008.
An additional robustness check both an OLS regression in which control variables were
called training set, is used to develop the model while the second, the test set, provides insight on how the
observations are reconstructed with a variable number of factors extracted from the training set. If there
are only a few number of observations, which is very frequent in a PLS regression, the test set can also be
constructed by using a single rotated observation in the sense that, one by one, each observation becomes
a test set. It must be emphasized that each PLS result obtained using the cross validation method is more
robust than those that arise from the simple use of a number of vectors equal to the number of regressors
included and a non-parametric method as the PLS (Partial Least Square) regression
were used.
Financial Companies
When liquidity-constraining events occur, investors react more negatively to L3A than
to L1A and L2A (proposition 2) and react negatively to L3L (proposition 3).
When liquidity-expansive events occur, investors react more positively to L3A than to
L1A and L2A (proposition 2-bis).
When bank bailouts occur, investors react in the following manner:
- more negatively to L3A than to L1A and L2A
- negatively to L3L
- more negatively to financial companies with higher leverage.
Non-financial companies
When liquidity-constraining events occur, investors’ reaction to L3A is negative.
However, when liquidity-expansive events occur, investors react positively to L3A and
negatively to L1A and L2A.
At both liquidity-constraining and liquidity-expansive events, investors seem not to
consider the higher/lower rollover risk (risk of refinancing) connected to the level 3
Liabilities (L3L).
Our findings could be affected by several limitations such as the number of
observations, the process of aggregation into groups of events and the approach used to
estimate the abnormal returns. This leads us to believe that further studies are needed to
understand the influence of fair value hierarchy on European companies’ stock prices.
Despite this, we can respond positively to the initial research question of whether fair
value hierarchy properly informed investors of the liquidity risk, and so improving their
investment decisions. This is because we believe that the above limitations are not
likely to affect the results, since the scope of our empirical analysis is the identification
of the relationship (and not the creation of a forecast model) between stock returns and
the three levels of fair value disclosure. In fact, it can be concluded that the introduction
of fair value hierarchy is useful for European company investors. Through the above
analysis we can document investors’ complex reaction to information on liquidity risk.
However, it is expected that further studies based on larger databases will support or
refute our findings.
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APPENDIX
Table 1: List of regression variables
Label
Variable
L1A
Assets classified as Level 1 of the fair value
L2A
Assets classified as Level 2 of the fair value
L3A:
Assets classified as Level 3 fair value
TOTFVA:
Total assets recorded at fair value
TOTNFVA
Total assets not at fair value
L1L
Liabilities classified in Level 1 of the fair value
L2L
L3L
TOTFVL
Total liabilities carried at fair value
TOTNFVL
Total liabilities not at fair value
EBIT
Earnings before interest and taxes
ROA
Return on Assets
OPACT
Cash flows generated by operating activities
LEV
Leverage
RECLASS:
Dummy allowed the reclassification by the IASB
IMP. RECLAS
Amount reclassified
Table 2: list of companies in the data sample
Company
AEGON GROUP
AIR LIQUID
ALCATEL LUCENT
ALLIANZ
ARCELORMITTAL
ASS. GENERALI
AXA
BANCO
SANTANDER
BASF
BAYER
BBVA
BNP PARIBAS
CARREFOUR
CREDIT AGRICOLE
DAIMLER
DEUTSCHE BANK
DEUTSCHE BORSE
DEUTSCHE
TELEKOM
E
ON
ENEL
ENI
FRANCE TELECOM
DANONE
SOCIETE
GENEREALE
IBERDROLA
ING GROUP
INTESA SANPAOLO
L'
OREAL
LVMH
MUNICH RE
NOKIA
PHILIPS
RENAULT
REPSOL YPF
RWE
SAINT GOBAIN
SANOFI AVENTIS
SAP
SCHNEIDER
ELECTRIC
SIEMENS
GDF SUEZ
TELECOM ITALIA
TELEFONICA
TOTAL
UNICREDIT GROUP
UNILEVER
VINCI
VIVENDI
VOLKSWAGEN
UNIBAIL-RODAMCO
CRH
ALSTOM
ANHEUSER BUSH
A2A
ABERTIS INFR.
ACCOR
ACERINOX
ACKERM. & VAN
HAAREN
ACS
ADIDAS
ADP
AGEAS
AHOLD
AIR FRANCE-KLM
Se
tto
F
N
F
N
F
N
F
N
F
F
N
F
N
F
F
N
F
N
F
F
N
F
N
F
N
F
N
F
N
F
N
F
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
Società
BCA CARIGE
BCA MPS
BCA POP. DI
MILANO
BCA
POP. DI
SONDRIO
BCA
POP. EMIL.
ROMAGNA
BCO COMERCIAL
PORTUG.
BCO
DE VALENCIA
BCO ESPIRITO
SANTO
BCO
POPOLARE
BCO POPULAR
ESPANOL
BCO
SABADELL
BEIERSDORF
BEKAERT
BELGACOM
BIC
BILFINGER BERGER
BIOMERIEUX
BMW
BOLSAS Y
MERCADOS ESP.
BOSKALIS
WESTMINSTER
BOURBON
BOUYGUES
BRISA
BUREAU VERITAS
BWIN INT. ENT.
C&C GRP
CHRISTIAN DIOR
CIMPOR
CNP ASSURANCES
COCA-COLA HBC
COFINIMMO
COMMERZBANK
COMP NAT. A
PORTEFEU
CONTINENTAL
CORIO
CAP GEMINI
CASINO GUICHARD
CATTOLICA ASS.
CELESIO
CGG VERITAS
CREDITO
VALTELLINES
CRITERIA
CAIXACORP
CRUCELL
CSM
DASSAULT
SYSTEMS
DCC
DELHAIZE GRP
DELTA LLOYD
DEUTSCHE POST
DEUTSCHE
POSTBANK
DEXIA
DRAGON OIL PLC
EADS
EBRO FOODS
EDENRED
EDF
EDP
EDP RENOVAVEIS
EFG EUROBANK
ERGASIAS
EIFFAGE
ELAN
CORPORATION
ELISA
CORPORATION
ENAGAS
ENDESA
Se
tto
F
F
F
F
F
F
F
F
F
F
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
F
N
F
N
F
F
N
F
N
F
N
F
N
F
N
F
N
F
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
Se
Se
Company
Company
tto
tto
N PERNOD RICARD
N
FRESENIUS PREF
F PEUGEOT
F
N
N
FUGRO
F PIRELLI & C.
F
N
N
GALP ENERGIA
F POHJOLA BANK
N
GAMESA
F
F PORSCHE PREF
N
N
GAS NATURAL SDG
F PORTUGAL
F
GRP BRUX.
N
LAMBERT
TELECOM
F
N PPR
N
GEA
GRP
F PRYSMIAN
F
N
N
GECINA
F PUBLIC POWER
F
N
N
GEMALTO
F CORP.
F
GESTEVISION
N
N
PUBLICIS GRP
TELECINCO
F PUMA
F
N
N
GRIFOLS
F QIAGEN
F
N
N
GRP EUROTUNNEL
F RAIFFEISEN INT.
N
GRUPO ACCIONA
F
F BANK
N
HANNOVER RUECK
RANDSTAD
F
HEIDELBERGCEME
N RAUTARUUKKI K
N
NT
F RED ELECTRICA
F
N
N
HEINEKEN
F REED
CORP.ELSEVIER NV
F
N
N
HEINEKEN HLDG
F RHEINMETALL
F
N
N
HENKEL PREF
F RHODIA
F
HERMES
N
N
INTERNATIONAL
F RHOEN KLINIKUM
F
N
N
HOCHTIEF
F RYANAIR
F
N
N
IBERDROLA REN.
F SAFRAN
F
N
N
IBERIA
F SAIPEM
F
N
N
ICADE
F SALZGITTER
F
N
N
ILIAD
F SAMPO
F
N
IMERYS
F SANOMA
N
N
IMMOFINANZ
F SBM OFFSHORE
F
N
N
IMTECH
F SCOR
F
N
INDITEX
F SEB
N
N
INDRA SISTEMAS
F SES
F
N
INFINEON
N
TECHNOLOGIES
F SGL CARBON
F
N
N
JCDECAUX
F SNAM RETE GAS
F
N
JERONIMO
N
MARTINS
F SODEXO
F
N
N
K+S
F SOFINA
KBC GRP
F
N SOFTWARE
N
KEMIRA
F SOLARWORLD
F
N
N
KERRY GRP
F SOLVAY
F
N
N
KESKO
F STADA
F
N
N
KLEPIERRE
F STMICROELECTRON
ARZNEIMITTEL
F
N
N
KLOECKNER & CO
F STORA
ICS
F
N
N
KONE B
ENSO R
F SUEDZUCKER
F
N
N
KONECRANES
F SUEZ
F
N
N
KONINKLIJKE DSM
F SYMRISE
ENVIRONNEMENT
F
N
N
KPN
F TECHNIP
F
N
N
LAFARGE
F TECNICAS
F
N
N
LAGARDERE
F REUNIDAS
F
N
N
LANXESS
TELEKOM AUSTRIA
F TELENET GRP HLDG N
F
N
LEGRAND
F TELEPERFORMANC
F
N
N
LINDE
F TENARIS
E
F
N
N
LUFTHANSA
F TERNA
F
N
N
LUXOTTICA
F TF1
F
N
N
M6 METROPOLE TV
F THALES
F
MAN
N
N
F THYSSENKRUPP
F
N
MAPFRE
F
MARFIN INV. GRP
F TITAN CEMENT
N
F
N TNT
N
MAUREL ET PROM
F TOGNUM
F
MEDIASET
N
N
F UBI BCA
MEDIOBANCA
F
MERCK
N UCB
N
F UMICORE
F
N
N
METRO
F UNITED INTERNET
F
METSO
N
N
F UPM KYMMENE
F
N
N
MICHELIN
F VALEO
F
MOBISTAR
N
N
F VALLOUREC
F
MTU AERO ENGINES N
N
HLDGBANK OF
F
NAT.
F VEOLIA ENV.
N
GREECE
F
AIXTRON
AKZO NOBEL
ALLIED IRISH
BANKS BANK
ALPHA
ANDRITZ
ARKEMA
ASML HLDG
ATLANTIA
ATOS ORIGIN
ATRIUM EUR.RE
AURUBIS
AZIMUT HLDG
BANK OF IRELAND
BANKINTER
N
F
N
F
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
F
F
ERAMET
ERSTE GROUP
BANK
ESSILOR
INTERNATIONAL
ETS
COLRUYT
EURAZEO
EUTELSAT
COMMUNIC.
FERROVIAL
FIAT
FINMECCANICA
FOM. DE CONSTR.
CONTRA
FONCIERE DES
REGIONS
FORTUM
FRAPORT
FRESENIUS MEDIC.
CARE
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
NATIXIS
NEOPOST
NESTE OIL
NEXANS
NOKIAN RENKAAT
NUTRECO
OMV
OPAP
ORION B
OTE
OUTOKUMPU
OUTOTEC
PAGESJAUNES
PARMALAT
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
VERBUND
VIENNA
INSURANCE
VOESTALPINE
VOPAK
WACKER CHEMIE
WARTSILA
WENDEL
WERELDHAVE
WIENERBERGER
WINCOR NIXDORF
WOLTERS KLUWER
YIT
ZARDOYA OTIS
ZODIAC
AEROSPACE
Table 3: Descriptive statistics full sample year 2007
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
LEV
2007 FULL SAMPLE
Mean
Median
142.831,69
3.207,14
81.084,68
4.337,50
6.546,50
192,10
230.462,87
18.856,55
204.358,59
78.882,50
434.821,46
86.687,00
44.046,32
412,82
65.949,26
2.364,39
5.486,80
0
124.251,24
24.636,00
282.939,19
44.990,80
407.190,43
57.917,85
5.341,72
3.391,00
0,06
0,06
13.137,35
4.928,30
0,77
0,85
1Q
660,75
38,55
0
1.350,25
22.368,95
29.791,00
0
29,27
0
1.430,32
-2.109,50
19.423,50
1.366,25
0,01
739,33
0,60
3Q
111.866,00
44.405,87
4.072,75
201.527,25
378.838,75
685.420,75
15.052,23
21.604,67
525,50
118.868,03
618.574,00
630.256,00
8.599,75
0,10
16.471,75
0,94
Table 4: Descriptive statistics financial companies year 2007
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
LEV
2007 FINANCIAL SAMPLE
Mean
Median
1Q
306.193,63
187.749,50
62.183,13
172.024,35
56.001,41
24.395,78
12.171,92
3.929,50
536,15
490.389,91
302.416,50
111.244,75
399.705,66
424.477,00
198.723,00
890.095,57
817.921,00
454.824,50
93.122,88
19.366,82
1.858,89
137.635,34
38.799,00
199,76
9.723,43
441,00
57,00
245.674,66
158.318,50
16.364,00
604.824,84
686.875,00
301.190,25
850.499,50
764.424,50
428.876,75
6.252,62
7.383,60
2.451,50
0,02
0,01
0,01
22.980,66
14.249,00
4.779,79
0,95
0,95
0,94
3Q
342.716,50
175.194,25
11.737,75
685.196,75
547.325,50
1.369.598,25
107.578,50
203.136,94
11.637,75
334.874,75
882.162,75
1.322.449,50
9.078,06
0,01
22.466,50
0,97
Table 5: Descriptive statistics non-financial companies year 2007.
Variable
L1A
2007 NON FINANCIAL SAMPLE
Mean
Median
1Q
2.807,17
689,50
0
3Q
2.009,25
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
N
F
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
LEV
3.136,38
1.724,71
7.668,26
36.918,24
44.586,50
1.980,69
4.504,05
1.855,41
20.174,03
7.037,20
27.211,23
4.560,96
0,09
4.700,23
0,62
119,59
0
1.503,50
26.363,11
31.274,00
0
450,00
0
5.426,25
-1.591,48
19.747,00
2.744,30
0,08
2.560,00
0,60
16,66
0
217,64
5.794,57
5.850,17
0
18,29
0
1.430,32
-7.402,64
3.412,56
519,18
0,06
739,33
0,56
1.519,00
123,84
6.788,50
60.808,03
66.321,63
15,75
5.695,25
0
34.940,75
25.128,75
40.040,28
5.306,50
0,11
6.238,15
0,64
Table 6: Descriptive statistics full sample year 2008.
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
IMP. RECLASS.
RECLASS.
LEV
2008 FULL SAMPLE
Mean
Median
31.531,80
291,66
31.860,01
294,37
4.346,43
0,18
67.740,47
1.139,00
1.971.245,91
15.756,50
2.038.986,38
19.521,50
11.307,98
0
26.646,94
254,23
3.880,83
0
41.833,30
358,00
1.998.000,74
10.057,29
2.039.834,04
13.704,65
1.088,88
572,62
0,06
0,06
82.638,25
799,90
795,77
0
0,17
0
0,71
0,71
1Q
0
16,34
0
74,45
3.992,52
4.275,52
0
13,44
0,00
22,24
2.094,60
2.512,75
198,75
0,01
253,81
0
0
0,57
3Q
2.782,01
174,35
7.944,22
49.098,63
58.163,50
8,41
2.245,00
0
3.021,75
46.317,33
53.597,77
1.850,93
0,09
2.340,68
0
0
0,91
-
Table 7: Descriptive statistics financial companies year 2008
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
IMP. RECLASS.
RECLASS.
LEV
Mean
Median
102.494,36
9.695
106.494,37
5.052,78
14.104,82
707,73
223.093,52
23.639
6.912.410,43
103.952,15
7.135.503,95
121.327,23
36.292,18
179,53
89.500,46
1.424,13
12.111,24
5,13
137.903,88
2.520
6.505.246,09
90.188,87
6.643.149,97
109.283,77
-177,88
426,08
0,01
0
287.368,03
1203,03
2.492,04
20,88
0,51
1
0,89
0,93
1Q
3.082
1.307,69
83,07
5.846,798
21.442,13
44.270,11
0
31,95
0
569,38
32.690,01
39.218,67
27,32
0
297,89
0
0
0,89
3Q
92.013,50
14.224,84
215.286
488.770,50
859.563,78
4.757
48.914,50
5.439,34
85.430,50
654.851
816.301,36
1.685,23
0,01
10.253,5
1.422,5
1
0,95
1
Table 8: Descriptive statistics non-financial companies year 2008
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
IMP. RECLASS.
RECLASS.
LEV
Mean
Median
1Q
3.625,18
18,00
0
2.509,43
75,00
11,70
508,87
0
0
6.646,57
474,00
29,70
28.091,33
7.273,83
3.007,61
34.737,90
8.131,90
3.196,10
1.482,73
0
0
1.929,27
158,00
11,78
644,16
0
0
4.052,74
213,00
14,00
225.488,52
4.197,90
1.680,80
229.541,26
5.428,00
1.915,10
1.587,04
642,80
214,00
0,08
0,08
0,05
2.126,54
578,90
225,80
128,70
0
0
0,03
0
0
0,67
0,65
0,53
3Q
929,00
28,00
1.719,00
25.596,00
26.865,00
0
855,71
0
1.088,00
15.355,00
22.821,00
1.833,00
0,10
1.757,60
0
0
0,77
0,00
Table 9: Descriptive statistics full sample and financial sample year 2009
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
IMP. RECLASS.
RECLASS.
LEV
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
IMP. RECLASS.
2009 FULL SAMPLE
Mean
Median
13.948,55
141,00
15.649,93
197,40
1.350,13
0
30.948,60
796,00
1.187.297,33
15.859,00
1.218.245,93
18.542,57
2.552,46
0
12.821,44
178,70
1.015,66
0
16.389,56
225,00
1.098.777,84
9.415,00
1.115.167,40
10.635,00
6.696,63
508,00
0,03
0,04
1.532,21
770,00
498,53
0
0,16
0
0,67
0,69
Mean
Median
52.153,30
8.862,97
62.993,66
5.172,74
5.419,66
365,00
120.566,63
17.767,00
5.036.400,88
68.974,55
5.156.967,51
122.313,22
9.580,93
68,78
51.738,94
1.670,11
3.221,96
2,20
64.541,83
1.989,89
4.699.834,32
87.257,29
4.764.376,15
109.963,63
8.204,93
637,80
0,01
0,01
-38.808,71
183,82
1.980,04
0
1Q
2,65
21,00
0
86,62
4.324,89
4.715,75
0
22,28
0
26,58
2.303,00
2.729,87
157,53
0,01
238,98
0
0
0,55
3Q
2.427,90
1.901,63
114,00
5.271,32
56.812,80
64.979,00
16,00
1.400,46
0
2.158,45
44.397,50
51.240,84
1.699,00
0,08
2.496,95
0
0
0,81
1Q
2.723,52
1.324,50
67,87
4.814,50
21.853,45
42.685,01
0
163,05
0
276,42
31.019,37
35.862,52
119,73
0
-3.263,50
0
3Q
72.922,40
36.766,85
3.175,50
136.645,00
315.312,00
492.141,50
4.857,00
24.390,00
715,28
33.157,42
375.170,60
466.301,00
2.630,00
0,02
2.143,58
229,90
RECLASS.
LEV
0,45
0,85
0
0,92
0
0,87
1,00
0,95
Table 10: Descriptive statistics non-financial sample year 2009
Mean
Median
1Q
3.242,82
42,50
0,14
2.383,27
82,50
8,90
209,76
0
0
5.835,86
354,67
48,78
108.702,38
9.841,95
3.126,28
114.538,24
11.209,41
3.803,45
582,95
0
0
1.915,99
109,00
21,24
397,41
0
0
2.896,35
116,70
24,14
89.690,58
5.474,45
1.819,71
92.586,93
6.020,18
1.954,05
6.273,98
485,45
167,23
0,04
0,06
0,03
12.836,54
923,27
329,50
83,38
0
0
0,08
0
0
0,62
0,63
0,54
Variable
L1A
L2A
L3A
TOT FVA
TOT NFVA
TOT ASSETS
L1L
L2L
L3L
TOT FVL
TOT NFVL
TOT LIABIL
EBIT
ROA
OPACT
IMP. RECLASS.
RECLASS.
LEV
3Q
537,25
876,33
35,75
1.623,43
26.414,87
31.702,15
0
915,25
0
1.151,25
18.763,00
22.075,75
1.629,75
0,09
2.496,95
0
0
0,75
Table 11: % of Fair value items (FVA and FVL) for financial and non-financial
companies.
2007
Variabile
fin
2008
non fin
fin
2009
non fin
fin
non fin
FVA
490389,91
7668,26
223093,51
6646,57
120566,63
5835,86
NFVA
890095,57
44586,50
7135503,95
34737,90
5156967,51
114538,24
%
55,1%
17,2%
3,1%
19,1%
2,3%
5,1%
FVL
245674,66
20174,03
137903,88
4052,74
64541,83
2896,35
NFVL
850499,50
27211,23
6643149,97
229541,26
4764376,15
92586,93
%
28,9%
74,1%
2,1%
1,8%
1,4%
3,1%
Table 12: Fair value hierarchy in the financial and non-financial companies
Variabile
2007
2008
2009
fin
non fin
fin
non fin
fin
non fin
L1A/TOT FVA
62,08%
45,86%
41,01%
3,80%
49,88%
11,98%
L2A/TOT FVA
18,52%
7,95%
21,37%
15,82%
29,11%
23,26%
L3A/TOT FVA
1,30%
0,00%
2,99%
0,00%
2,05%
0,00%
L1L/TOT FVL
12,23%
45,86%
26,32%
36,59%
3,46%
0,00%
L2L/TOT FVL
24,51%
7,95%
64,90%
47,60%
83,93%
93,40%
L3L/TOT FVL
0,28%
0,00%
8,78%
15,89%
0,11%
0,00%
Table 13: List of selected crisis events
ID
Date of
the event
1.
17/02/08
2.
16/03/08
3.
11/07/08
4.
13/07/08
5.
07/09/08
Description
Regno Unito: il governo nazionalizza Northern Rock.
acquisizione di Bear
Stati Uniti: JPMorgan Chase annuncia l'
Stearns; la FED istituisce il Primary Dealer Credit Facility.
Stati Uniti: fallisce IndyMac, cassa di risparmio specializzata
nell’erogazione di mutui.
Stati Uniti: la Federal Reserve autorizza la Federal Reserve
Bank di New York a concedere credito a Fannie Mae e Freddie
Mac in caso di necessità, al fine di preservare la capacità delle
due istituzioni di erogare mutui.
Stati Uniti: la Federal Housing Finance Agency sottopone
Fannie Mae e Freddie Mac alla “conservatorship”, una
procedura finalizzata alla stabilizzazione delle istituzioni in
crisi e a un loro ritorno alla normale operatività.
Stati Uniti: fallisce Lehman Brothers (totale attivo a Novembre
2007 di $691 miliardi). È il più grande fallimento bancario
nella storia americana; Bank of America annuncia
l’acquisizione di Merrill Lynch per $50 miliardi in azioni.
Stati Uniti: il governo nazionalizza AIG, ricevendo il 79,9%
delle azioni della compagnia in cambio di un prestito garantito.
Il prestito è concesso dalla Federal Reserve Bank of New York
e ha un limite massimo di $85 miliardi.
Regno Unito: HBOS è costretta a una fusione mediata dal
governo britannico con una sua concorrente; il governo
britannico sospende la vendita allo scoperto dei titoli finanziari.
Source
Assonime
Assonime
Assonime
Assonime
BIS
Assonime
BIS
Assonime
www.milanofinanza.it
www.ilcorriere.it
FED
Assonime
www.ilsole24ore.com
6.
15/09/08
7.
16/09/08
8.
18/09/08
9.
19/09/08
Stati Uniti: Iniezione di capitali da parte de Tesoro USA di $50
miliardi; divieto di vendita allo scoperto imposto dalla SEC;
primi dettagli del piano TARP di aiuti USA.
BIS
FED
22/09/08
Stati Uniti: la FED approva la richiesta di Goldman Sachs e
Morgan Stanley di diventare bank holding companies;
Danimarca: intervento della Banca danese in aiuto di Ebh bank.
FED
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10.
11.
12.
13.
14.
25-09/08
29/09/08
30/09/08
03/10/08
Stati Uniti: l’Office of Thrift Supervision chiude Washington
Mutual e ne affida le attività alla FDIC. JPMorgan Chase
acquista per $1.9 miliardi dalla FDIC tutti i depositi, gli attivi e
alcune passività di Washington Mutual.
Regno Unito: il Tesoro nazionalizza Bradford & Bingley plc e
ne trasferisce i depositi e i network di filiali a Abbey National
plc;
Germania: Hypo RE aiutata da un pool di banche;
Stati Uniti: Citi annuncia l'
acquisto delle attività bancarie di
Wachovia; il TARP non è approvato dal parlamento USA;
Benelux: i governi di Belgio, Lussemburgo e Olanda
annunciano di aver stipulato un accordo per un'
azione
concertata di supporto al gruppo finanziario Fortis. È prevista
un'
iniezione di capitale pari a € 11.2 miliardi.
Belgio-Francia: i governi di Belgio e Francia e gli azionisti
sottoscrivono un aumento di capitale di Dexia pari a €6
miliardi. Il governo del Lussemburgo investe €376 milioni in
obbligazioni convertibili di Dexia Banque Internationale a
Luxembourg S.A.;
Irlanda: garanzia statale su tutti i depositi, covered bond e
debiti per 6 banche irlandesi.
Stati Uniti: il Congresso approva l’Emergency Economic
Stabilization Act of 2008. La legge contiene il Troubled Assets
Relief Program (TARP), che prevede l’acquisto e la garanzia
dei cosiddetti “attivi tossici” delle istituzioni finanziarie. Si
riconosce alla SEC il potere di sospendere nei bilanci la
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15.
06/10/08
16.
07/10/08
17.
08/10/08
18.
09/10/08
19.
10/10/08
20.
13/10/08
21.
14/10/08
22.
15/10/08
23.
16/10/08
24.
17/10/08
valutazione al fair value; Wells Fargo e Wachovia annunciano
la fusione. L'
operazione non richiede l'
assistenza finanziaria
della Federal Deposit Insurance Corporation (FDIC);
Islanda: nazionalizzata la banca islandese Glitnir;
Belgio-Olanda: il governo olandese acquisisce Fortis Bank
Nederland Holding N.V.(compresa la partecipazione in ABN
AMRO Holding N.V.), Fortis Verzekeringen Nederland N.V. e
Fortis Corporate Insurance N.V. La transazione sostituisce
l'
investimento in Fortis Bank Nederland Holding N.V.
annunciato il 29 settembre
Belgio-Francia: il governo belga completa l'
acquisizione di
Fortis Bank SA/NV e ne cede il 75% a BNP Paribas. BNP
Paribas acquista anche il 100% di Fortis Insurance Belgium.
Un portafoglio di prodotti strutturati di Fortis Bank è trasferito
ad un nuovo veicolo controllato da Fortis Group (66%), dal
governo belga (24%) e da BNP Paribas (10%);
Germania: Hypo Real Estate riceve una linea di credito
garantita di $50 miliardi, di cui 35 garantiti dal governo;
Islanda: crollo delle azioni delle banche islandesi.
Stati Uniti:$1,3 trilioni disponibili con il Commercial Paper
Funding Facility (CPFF);
Europa: l’ECOFIN garantisce i depositi correnti fino a 50.000
euro;
Islanda: nazionalizzata la banca islandese Landsbanki.
Stati Uniti: la Federal Reserve Bank di New York concede ad
AIG un prestito, fino a $37.8 miliardi, in cambio di titoli a
tasso fisso di alta qualità;
Banche centrali: la BCE, la Banca nazionale svizzera, la Bank
of Canada, la Bank of England, la FED e la Sveriges Riksbank
riducono i tassi di interesse ufficiali di 50 punti base. La Banca
del Giappone esprime forte sostegno nei confronti di tali
interventi;
Regno Unito: il governo annuncia il piano per garantire la
stabilità del sistema finanziario.
Islanda: il governo islandese prende il controllo della maggiore
banca islandese, Kaupthing;
Italia: il Consiglio dei Ministri approva il decreto legge
contenente le misure per garantire la stabilità del sistema
creditizio e la continuità nell'
erogazione del credito alle
imprese e ai consumatori.
Spagna: il governo approva un decreto legge che istituisce un
fondo per l'
acquisizione di attivi finanziari di alta qualità.
Regno Unito: Royal Bank of Scotland, HBOS, Lloyds TSB
aiutate dal governo britannico;
Spagna: il governo approva il secondo decreto per mantenere la
stabilità finanziaria e sostenere le erogazioni dei crediti;
Unione Europea: lo IASB modifica lo IAS 39 al fine di
consentire, in determinate circostanze, la deroga al criterio del
fair value;
Italia: il Consiglio dei Ministri approva il secondo decreto
legge contenente ulteriori misure per garantire la stabilità del
sistema creditizio.
Stati Uniti: 185 miliardi di dollari in aiuto dal governo USA
per Citigroup, Bank of America, JP Morgan Chase, Goldman
Sachs, Merrill Lynch, Morgan Stanley, Wells Fargo, Bank of
New York-Mellon, State street.
Unione Europea: l’Unione europea adotta, con regolamento
pubblicato in gazzetta ufficiale, le modifiche apportate allo IAS
39 dallo IASB.
Svizzera: la Confederazione Svizzera acquisisce il 9% del
capitale sociale di UBS;
Francia: il Parlamento approva il piano per ristabilire la fiducia
nei settori bancario e finanziario e sostenere l'
economia.
Germania: il Parlamento approva il piano per la stabilizzazione
dei mercati finanziari
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25.
19/10/08
26.
21/10/08
27.
24/10/08
28.
28/10/08
29.
29/10/08
30.
30/10/08
31.
03/11/08
32.
05/11/08
33.
09/11/08
34.
10/11/08
35.
12/11/08
36.
14/11/08
37.
20/11/08
38.
21/11/08
39.
24/11/08
40.
25/11/08
41.
26/11/08
42.
02/12/08
43.
03/12/08
Olanda: il governo sottoscrive €10 miliardi di capitale (core
capital) della compagnia ING
Stati Uniti: $540 miliardi dalla FED per acquisire il debito a
breve da fondi monetari (money market mutual funds);
Grecia: le 7 maggiori banche greche accettano di partecipare al
piano da 28 miliardi di euro varato dal governo greco.
Stati Uniti: l’acquisizione di National City Corp da parte di
PNC, crea la 5° banca statunitense per ampiezza.
Stati Uniti: 1° utilizzo degli aiuti TARP di $125 miliardi da
parte di 9 banche;
Ungheria: il governo riceve $25 miliardi dall’Ue e dall’FMI;
Olanda: il governo ricapitalizza per 3 miliardi (core capital) la
compagnia di assicurazione AEGON.
Stati Uniti: la FED taglia i tassi di interesse dello 0,5% (ora
all’1%). Inoltre, la FED annuncia l’apertura di linee di credito
dell’ammontare di $30 miliardi a favore di Brasile, Corea del
Sud, Messico e Singapore.
Stati Uniti: la FED aggiunge $21 miliardi d’aiuti per AIG.
Regno Unito: il governo crea una società di proprietà pubblica,
UK Financial Investments Limited, per gestire le partecipazioni
del governo nelle banche che aderiscono al piano di
ricapitalizzazione.
BCE-Banca d’Inghilterra: la BCE riduce i tassi di interesse
dello 0,5% (al 3,25%) e la Banca d’Inghilterra dell’1,5% (al
3%);
Ucraina: il FMI concede all'
Ucraina un prestito stand-by di
$16.4 miliardi per contribuire a stabilizzare il sistema
finanziario ed economico.
Cina: il governo annuncia un piano di stimolo all’economia da
$586 miliardi.
Stati Uniti: il Tesoro annuncia la sottoscrizione di azioni
privilegiate AIG per $40 miliardi. La Fed annuncia l’istituzione
per AIG di una residential mortgage-backed securities facility
(fino a $ 22.5 miliardi) e di una collateralized debt obligations
facility (fino a $30 miliardi);
Spagna: Santander vara un aumento di capitale pari a € 7.2
miliardi per rafforzare il core capital ratio;
Lettonia: nazionalizzata Parex Banka, la più grande banca
indipendente lettone.
Stati Uniti: Paulson, segretario al Tesoro, annuncia un nuovo
approccio nella gestione del Troubled Assets Relief Program,
focalizzato non più sull’acquisto degli “attivi tossici”, ma sulle
ricapitalizzazioni e sul sostegno al credito al consumo.
Stati Uniti: 2° utilizzo del TARP di $33,5 miliardi da parte di
banche.
Stati Uniti: sospeso il pignoramento mutui da Fannie Mae and
Freddie Mac.
Stati Uniti: 3° utilizzo del TARP di $3 miliardi da parte di 23
banche.
Stati Uniti: salvataggio di Citigroup da parte del Tesoro USA,
del Federal Reserve Board e della FDIC.
Stati Uniti: $800 miliardi d’aiuto per resuscitare il sistema
finanziario erogati dal governo USA.
Unione Europea: La Commissione presenta un piano di ripresa
a favore della crescita e dell'
occupazione, volto a rilanciare la
domanda e a far rinascere la fiducia nell'
economia europea. Il
piano prevede l'
erogazione di un sostegno di bilancio pari a
circa 200 miliardi di euro.
Stati Uniti: la FED annuncia che estenderà 3 sostegni alla
liquidità fino al 30 aprile 2009.
Banche centrali: la BCE taglia i tassi di 75 bp e la BoE di
100bp.
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Stati Uniti: 4° utilizzo del TARP per $4 miliardi da parte di 35
banche.
Stati Uniti: $14 miliardi per salvare il settore auto americano
dal governo USA.
banche.
New York Times
15/12/08
Stati Uniti: le banche rivelano esposizioni alla frode Mardoff;
Times Online
48.
16/12/08
49.
19/12/08
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50.
23/12/08
51.
29/12/08
52.
31/12/08
53.
08/01/09
Stati Uniti: la FED taglia i tassi di 75 bp.
Stati Uniti: 6° utilizzo del TARP per $28 miliardi da parte di
28 banche;
Irlanda: il governo irlandese da il via libera al piano di 5,5
miliardi per salvare le prime 3 banche del paese.
Stati Uniti: 7° utilizzo del TARP per $15 miliardi da parte di
43 banche.
Stati Uniti: salvataggio GMAC da parte del governo USA.
banche.
Regno Unito: BoE taglia i tassi d’interesse di 50 bp;
Germania: il governo annuncia la sottoscrizione attraverso
SoFFin (fondo governativo per la stabilizzazione dei mercati
finanziari) di un aumento di capitale di Commerzbank per € 10
mld, che lo farà diventare il principale azionista con una quota
del 25% più 1 azione.
Unione Europea: la Banca centrale europea riduce i tassi di
interesse dello 0,5% (al 2%);
Irlanda: il governo annuncia la nazionalizzazione di Anglo
Irish Bank.
44.
05/12/08
45.
09/12/08
46.
12/12/08
47.
54.
15/01/09
55.
16/01/09
Italia: approvato dl anticrisi;
Stati Uniti: Bank of America è aiutata dal governo USA.
Regno Unito: il governo annuncia la conversione in azioni
ordinarie della sua partecipazione di £5 mld di azioni
privilegiate nel gruppo Royal Bank of Scotland; annunciato un
secondo piano a sostegno del settore finanziario che prevede il
potenziamento delle garanzie statali sulle passività e delle
misure di supporto alla liquidità e la creazione di uno schema
di garanzia degli attivi. Il governo e la Financial Services
Authority affermano inoltre che sarebbe preferibile introdurre
misure anticicliche nella regolamentazione del capitale.
Norvegia: più grande piano di stimoli all’economia degli ultimi
30 anni;
Olanda: annunciata una garanzia dello Stato su un portafoglio
di ING di € 27.7 mld di titoli garantiti da mutui residenziali. Lo
Stato riceverà in cambio l’80% dei proventi del portafoglio e
una commissione annuale per la garanzia;
Germania: emissione di oltre $36,8 miliardi di obbligazioni
statali;
Italia: dibattito chiuso nel Senato sul dl anticrisi.
Unione Europea-Svizzera: la BCE e la banca centrale svizzera
aumentano la loro offerta di swap;
Belgio-Francia: BNP Paribas, il governo belga e Fortis Holding
modificano gli accordi del 6 ottobre 2008. BNP Paribas
acquisirà una partecipazione del 10% in Fortis Insurance
Belgium (invece che del 100%). Inoltre, la quota di BNP nel
veicolo dei prodotti strutturati di Fortis sale dal 10% all’11,6%
(58.8% per il governo belga e 29,6% per Fortis Holding).
56.
19/01/09
57.
26/01/09
58.
02/02/09
59.
05/02/09
Regno Unito: BoE taglia I tassi d’interesse di 50 bp.
60.
10/02/09
61.
18/02/09
Stati Uniti: nuovo piano USA di aiuti di circa $1 trilione.
Stati Uniti: annunciato un piano mutui da $ 275 mld.
L’intervento si articola in uno stanziamento di $ 75 mld a
sostegno dei mutuatari e per evitare i pignoramenti e
nell’innalzamento da $ 100 a $ 200 mld del limite massimo per
la sottoscrizione da parte del Tesoro di azioni privilegiate di
Fannie Mae e Freddie Mac nell’ambito del programma di
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sostegno adottato nel settembre 2008. Sono inoltre previste
misure per facilitare il rifinanziamento a basso costo dei mutui.
62.
25/02/09
Italia: via libera ai Tremonti Bond in Italia
Regno Unito: il governo britannico lancia l’Asset Protection
Scheme per circa $500 miliardi; il gruppo Royal Bank of
Scotland partecipa allo schema governativo di protezione degli
attivi per £325 mld. Il governo annuncia la sottoscrizione di
£13 mld di capitale Core Tier 1 in RBS;
Unione Europea: approvazione dei piani economici di Regno
Unito, Francia e Germania.
Stati Uniti: annunciata una ristrutturazione del programma di
supporto pubblico per AIG, che include la conversione da parte
del Tesoro di $40 mld di azioni privilegiate cumulative e
perpetue in nuove azioni privilegiate con caratteristiche più
vicine alle azioni ordinarie; la sottoscrizione da parte del
Tesoro di azioni privilegiate non cumulative di AIG per un
ammontare massimo di $30 mld e di azioni privilegiate di due
sussidiarie assicurative di AIG per un ammontare massimo di
$26 mld; un prestito della Federal Reserve di circa $8.5 mld a
due veicoli creati da due sussidiarie assicurative del ramo vita
di AIG. A seguito del piano di ristrutturazione l’ammontare del
credito messo a disposizione di AIG dalla Fed diminuirà da un
massimo di $60 mld a un minimo di $25 mld.
63.
26/02/09
64.
02/03/09
65.
03/03/09
Unione Europea: approvazione del piano economico dell’Italia;
05/03/09
Banche centrali: la BoE e la BCE tagliano i tassi d’interesse di
50 bp e annuncio della BCE di un piano di acquisto di titoli di
75 miliardi di euro.
66.
67.
07/03/09
68.
09/03/09
69.
18/03/09
70.
20/03/09
71.
25/03/09
72.
29/03/09
73.
01/04/09
74.
02/04/09
Regno Unito: annunciata la nazionalizzazione del gruppo
bancario Lloyds attraverso la conversione da parte del Tesoro
di £4 mld di azioni privilegiate in azioni ordinarie. Inoltre
Lloyds parteciperà allo schema governativo di garanzia degli
attivi per £260 mld.
Islanda: Straumur Investment Bank è nazionalizzata dal
governo islandese.
Stati Uniti: la Federal Reserve annuncia l’acquisto di titoli del
Tesoro americano a lungo termine per un ammontare massimo
di $300 mld. Inoltre la Fed innalza i limiti massimi per i suoi
programmi di acquisto di debiti di Fannie Mae, Freddie Mac e
Federal Home Loan Banks (fino a $200 mld) e di titoli
mortgage-backed garantiti da Fannie Mae, Freddie Mac e
Ginnie Mae (fino a $1250 mld).
Austria: fallisce Bank Medici.
Italia: firmato l’accordo quadro tra l’Associazione Bancaria
Italiana e il Ministero dell’Economia e delle Finanze sulla
sottoscrizione da parte del Ministero degli strumenti finanziari
per la ricapitalizzazione delle banche previsti dall’art.12 del
decreto legge n. 185/08.
Spagna: la banca centrale spagnola sostituisce gli
amministratori della Caja de Ahorros de Castilla-La Mancha
con amministratori nominati dalla banca centrale. Il governo
offre una garanzia fino a €9 mld sui finanziamenti erogati dalla
banca centrale alla Caja Castilla-La Mancha
Messico: il governo richiede al Fondo Monetario
Internazionale una “linea di credito flessibile” di $47 mld.
Unione Europea: la Banca Centrale Europea riduce il tasso di
interesse di riferimento dall'
1,5% all'
1,25% (minimo storico);
G-20: si svolge a Londra la seconda riunione del G-20 sulla
crisi finanziaria ed economica. Viene raggiunto un accordo per
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75.
06/04/09
rilanciare la fiducia, la crescita e l’occupazione; rafforzare la
regolamentazione e la supervisione finanziaria e le istituzioni
finanziarie internazionali; evitare il protezionismo e
promuovere il commercio e gli investimenti globali;
Stati Uniti: il Financial Accounting Standards Board (FASB)
modifica il principio contabile che regola la valutazione delle
attività finanziarie sulla base del valore di mercato (“fair
value”): viene introdotta una maggiore flessibilità per la
valutazione delle attività finanziarie i cui mercati siano
“inattivi”, con la possibilità di valutare tali attivi a prezzi
superiori a quelli correnti di mercato.
Banche centrali: la Banca Centrale Europea, la Banca
d’Inghilterra, la Federal Reserve, la Banca del Giappone e la
Banca nazionale svizzera annunciano swap valutari finalizzati
a mettere a disposizione della Federal Reserve valuta estera da
fornire alle istituzioni finanziarie statunitensi.
BIS
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76.
09/04/09
Germania: Hypo RE è nazionalizzata;
Regno Unito: la BoE continua nel suo piano d’acquisti.
77.
14/04/09
Polonia: il governo annuncia la richiesta al Fondo Monetario
Internazionale di una “linea di credito flessibile” di $ 20.5 mld.
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17/04/09
Messico: il Fondo Monetario Internazionale approva la
concessione al Messico di una “linea di credito flessibile” di
$47 mld.
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79.
21/04/09
Colombia: la Colombia richiede al Fondo Monetario
Internazionale una “linea di credito flessibile” di $10.4 mld.
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80.
06/05/09
Unione Europea: è approvata la riforma dei requisiti di capital
bancari dal parlamento europeo; la BCE taglia i tassi di 25 bp
and 50 bp;
Regno Unito: la BoE incrementa il suo piano d’acquisti fino a
125 miliardi.
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81.
14/05/09
Belgio: annunciata una garanzia dello Stato su un portafoglio
di KBC di €20 mld di attivi tossici. KBC coprirà le perdite fino
a €3.2 mld; ulteriori perdite saranno coperte per il 90% dallo
Stato e per il 10% da KBC. Lo Stato riceverà un premio per la
garanzia di €1.2 mld più €30 mln a trimestre per sei anni.
82.
20/05/09
Stati Uniti: concluso l’aumento di capitale di Bank of America
da $13,5 miliardi.
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83.
21/05/09
Spagna: emissione di bond per $2,6 miliardi.
84.
28/05/09
85.
02/06/09
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86.
10/06/09
87.
17/06/09
Austria: a Bank Medici è revocata la licenza bancaria austriaca.
Unione Europea: la BCE lancia un piano di swap a 7 giorni for
massimi $25 miliardi.
Svezia: la banca centrale svedese prende a prestito dalla Banca
Centrale Europea €3 mld in cambio di corone svedesi
nell’ambito dello swap agreement tra i due istituti firmato il 20
dicembre 2007 (tetto massimo: €10 mld).
Stati Uniti: il Tesoro presenta un piano di riforma della
regolamentazione e vigilanza finanziaria. Sono previste, tra le
altre misure, l’istituzione di un Consiglio per la vigilanza sui
servizi finanziari, incaricato di individuare i rischi sistemici; la
creazione di un’autorità federale per la protezione dei
consumatori e di una nuova autorità di vigilanza delle banche
di deposito federali; l’attribuzione alla Federal Reserve delle
funzioni di vigilanza consolidata su tutte le istituzioni
finanziarie che per dimensione, livello di indebitamento e
interconnessione potrebbero compromettere la stabilità
finanziaria in caso di fallimento (Tier 1 Financial Holding
Companies, FHCs); requisiti di capitale e regole prudenziali
più stringenti per le Tier 1 FHCs rispetto alle altre imprese
finanziare; JPMorgan e Morgan Stanley sono le prime banche a
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restituire i finanziamenti ricevuti dal fondo di salvataggio Tarp.
88.
26/06/09
Spagna: lancio di un fondo di 9 miliardi di euro per il sistema
finanziario.
89.
29/06/09
Regno Unito: la BoE acquista bond statali per 3,5 miliardi.
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90.
02/07/09
91.
08/07/09
92.
20/07/09
93.
06/08/09
94.
23/09/09
95.
05/10/09
96.
17/12/09
Olanda: Fortis Bank Nederland rimborsa al governo olandese
un prestito a breve termine di €34 mld concesso nell’ambito
dell’acquisizione da parte del governo delle attività bancarie e
assicurative di Fortis SA/NV nell’ottobre 2008.
Regno Unito: il Tesoro pubblica un documento che contiene
un’analisi della crisi finanziaria e un progetto di riforma dei
mercati finanziari e della regolamentazione. Vengono proposti
la creazione di un Consiglio per la stabilità finanziaria,
composto dal Tesoro, dalla Banca d’Inghilterra e dalla
Financial Services Authority (FSA), e il rafforzamento dei
poteri della FSA, inclusa l’attribuzione a quest’ultima di un
esplicito obiettivo di stabilità finanziaria. Il Tesoro esprime
inoltre il suo sostegno alle proposte della FSA (“Turner
Review”) in relazione ad un aumento del livello e della qualità
del capitale delle banche, all’introduzione di un livello
massimo di indebitamento delle banche (“leverage ratio”) e ad
un rafforzamento delle regole sulla liquidità;
G-8: i leader del G-8 riuniti a L’Aquila sottoscrivono una
dichiarazione comune in cui si impegnano ad adottare le
misure necessarie per riportare l’economia mondiale su un
sentiero di crescita forte, stabile e sostenibile, fornendo stimoli
macroeconomici coerenti con la stabilità dei prezzi e la
sostenibilità fiscale a medio termine. La priorità urgente è il
risanamento e la stabilizzazione dei mercati finanziari; è inoltre
necessario rafforzare il quadro globale per la regolamentazione
e la supervisione finanziaria, garantendo una vigilanza efficace
su tutte le istituzioni e le attività con rilevanza sistemica.
Occorre promuovere la coerenza tra norme contabili e
prudenziali, creare strumenti adeguati per affrontare la prociclicità e rispettare le norme fondamentali di correttezza,
integrità e trasparenza nelle interazioni economiche (“Lecce
Framework”).
Islanda: il governo annuncia un piano di ricapitalizzazione
delle tre nuove principali banche commerciali islandesi
(Islandsbanki, New Kaupthing e New Landsbanki), istituite
dopo la crisi delle maggiori banche commerciali del paese
nell’ottobre 2008. L’ammontare complessivo del piano di
ricapitalizzazione è di circa €1.5 mld.
Regno Unito: la Banca d’Inghilterra aumenta di £50 mld, fino a
£175 mld, il suo programma di acquisto di titoli di stato e
obbligazioni societarie (“quantitative easing”).
Unione Europea: la Commissione adotta un pacchetto di
proposte legislative per la riforma dell’architettura europea di
vigilanza sui mercati finanziari. È prevista l’istituzione di un
organismo con compiti di supervisione macro-prudenziale, lo
European Systemic Risk Board (ESRB), e la creazione di un
sistema europeo di autorità di vigilanza finanziaria (ESFS), con
funzioni di supervisione micro-prudenziale.
Germania: completata la nazionalizzazione di Hypo Real
Estate attraverso il fondo tedesco di stabilizzazione dei mercati
finanziari (SoFFin).
Banca dei Regolamenti Internazionali: il Comitato di Basilea
per la supervisione bancaria adotta un pacchetto di proposte per
rafforzare il capitale e la liquidità del settore bancario. Le
proposte prevedono il miglioramento della qualità e della
trasparenza del capitale; il rafforzamento dei requisiti di
capitale per i rischi di controparte; l’introduzione di un
leverage ratio, come misura supplementare ai requisiti di
capitale ponderati per il rischio; la creazione di un sistema di
requisiti di capitale anticiclici; l’introduzione di standard
Assonime
Assonime
Assonime
Assonime
Assonime
Assonime
Assonime
97.
11/04/10
98.
02/05/10
99.
03/05/10
100.
10/05/10
101.
18/05/10
102.
07/06/10
103.
22/06/10
minimi per la liquidità.
Area euro: i capi di stato e di governo adottano un piano
triennale di sostegno finanziario per la Grecia sotto forma di
prestiti bilaterali, per un ammontare massimo di €30 mld nel
primo anno; il piano prevede anche la partecipazione e un
contributo finanziario del Fondo Monetario Internazionale.
Area euro e Fondo Monetario Internazionale: adottato un piano
di sostegno finanziario alla Grecia per un ammontare
complessivo di €110 mld, di cui €80 mld a carico dei paesi
dell’area euro e €30 mld a carico del FMI.
Grecia: la BCE sospende l’applicazione della soglia minima di
rating per il collaterale nelle operazioni di credito
nell'
Eurosistema per i titoli di debito emessi o garantiti dal
governo greco.
Unione Europea: l’Ecofin adotta un pacchetto di misure per
preservare la stabilità finanziaria in Europa; tra le misure è
inclusa la creazione di un meccanismo europeo di
stabilizzazione finanziaria per un valore massimo di € 500 mld.
Germania: l’autorità di vigilanza sui mercati finanziari (BaFin)
proibisce le vendite allo scoperto e i credit default swaps
“nudi” sui titoli di stato dei paesi dell’area euro, nonché le
vendite allo scoperto “nude” delle azioni di alcune società del
settore finanziario.
Area euro: raggiunto l’accordo per la creazione di una
European Financial Stability Facility (EFSF), uno special
purpose vehicle incaricato di raccogliere fondi e concedere
prestiti agli stati membri dell’area euro in crisi. Gli stati
membri dell'
area euro garantiranno i debiti dell’EFSF per un
ammontare massimo di €440 mld.
Francia, Germania, Regno Unito: i governi dei tre paesi
pubblicano un comunicato congiunto in cui si annuncia
l’introduzione di una tassa sulle banche basata sui rischi che
esse pongono al sistema finanziario ed economico.
Assonime
Assonime
Assonime
Assonime
Assonime
Assonime
Assonime
Table 14: summary of the events, dates and observation window.
ID
Date of the
event
Obversation
window
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
17/02/08
16/03/08
11/07/08
13/07/08
07/09/08
15/09/08
16/09/08
18/09/08
19/09/08
22/09/08
25-09/08
29/09/08
30/09/08
03/10/08
06/10/08
07/10/08
08/10/08
09/10/08
10/10/08
13/10/08
14/10/08
18/02/08
17/03/08
11-14/07/08
14/07/08
08-09/09/08
15-16/09/08
16-17/09/08
18-19/09/08
19-22/09/08
22-23/09/08
25-26/09/08
29-30/09/08
30/0901/10/08
03-06/10/08
06-07/10/08
07-08/10/08
08-09/10/08
09-10/10/08
10-13/10/08
13-14/10/08
14-15/10/08
ID
Date of the
event
Obversation
window
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
14/11/08
20/11/08
21/11/08
24/11/08
25/11/08
26/11/08
02/12/08
03/12/08
05/12/08
09/12/08
12/12/08
15/12/08
16/12/08
19/12/08
23/12/08
29/12/08
31/12/08
8/01/09
15/01/09
16/01/09
19/01/09
14-17/11/08
20-21/11/08
21-24/11/08
24-25/11/08
25-26/11/08
26-27/11/08
02-03/12/08
03-04/12/08
05-08/12/08
09-10/12/08
12-15/12/08
15-16/12/08
16-17/12/08
19-22/12/08
23-24/12/08
29-30/12/08
31/12/0801/01/09
08-09/01/09
15-16/01/09
16-19/01/09
19-20/01/09
ID
Date of the
event
Obversation
window
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
25/03/09
29/03/09
01/04/09
02/04/09
06/04/09
09/04/09
14/04/09
17/04/09
21/04/09
06/05/09
14/05/09
20/05/09
21/05/09
28/05/09
02/06/09
10/06/09
17/06/09
26/06/09
29/06/09
02/07/09
08/07/09
25-26/03/09
30/03/09
01-02/04/09
02-03/04/09
06-07/04/09
09-10/04/09
14-15/04/09
17-20/04/09
21-22/04/09
06-07/05/09
14-15/05/09
20-21/05/09
21-22/05/09
28-29/05/09
02-03/06/09
10-11/06/09
17-18/06/09
26-29/06/09
29-30/06/09
02-03/07/09
08-09/07/09
22
23
24
25
26
27
28
29
30
31
32
33
34
35
15/10/08
16/10/08
17/10/08
19/10/08
21/10/08
24/10/08
28/10/08
29/10/08
30/10/08
03/11/08
05/11/08
09/11/08
10/11/08
12/11/08
15-16/10/0/8
16-17/10/08
17-20/10/08
20/10/08
21-22/10/08
24-27/10/08
28-29/10/08
29-30/10/08
30-31/10/08
03-04/11/08
05-06/11/08
10/11/08
10-11/11/08
12-13/11/08
57
58
59
60
61
62
63
64
65
66
67
68
69
70
26/01/09
02/02/09
5/02/09
10/02/09
18/02/09
25/02/09
26/02/09
02/03/09
03/03/09
05/03/09
07/03/09
09/03/09
18/03/09
20/03/09
26-27/01/09
02-03/02/09
05-06/02/09
10-11/01/09
18-19/02/09
25-26/02/09
26-27/02/09
02-03/09
03-04/03/09
05-06/03/09
09/03/09
09-10/03/09
18-19/03/09
20-23/03/09
92
93
94
95
96
97
98
99
100
101
102
103
20/07/09
06/08/09
23/09/09
05/10/09
17/12/09
11/04/10
02/05/10
03/05/10
10/05/10
18/05/10
07/06/10
22/06/10
20-21/07/09
06-07/08/09
23-24/09/09
05-06/10/09
17-18/12/09
12/04/10
02-03/05/10
03-04/05/10
10-11/05/10
18-19/05/10
07-08/06/10
22-23/06/10
Table 15: Results of ANOVAs
DATE
FINANCIAL
NON FINANCIAL
MAR FV
Vs
MAR
NFV
17/02/08
-0,01598
-
-0,01101
-0,02568
-
16/03/08
-0,01084
-
-0,00764
-0,00915
-
MAR FV
Vs
MAR NFV
-0,01845
-0,02127
***
-0,01233
-0,00305
-0,01032
*
-0,00386
MAR FV
Vs
MAR
NFV
11/07/08
-0,0315
-
-0,02431
-0,03335
*
-0,0246
-0,03379
***
13/07/08
-0,04728
-
-0,03513
-0,03414
-
-0,02685
-0,04181
***
07/09/08
0,018718
**
0,01024
-0,00342
-
0,001114
0,00707
-
15/09/08
-0,02491
-
-0,01625
-0,00527
-
-0,00614
-0,01490
**
16/09/08
-0,05147
-
-0,03546
-0,01846
-
-0,01888
-0,03503
***
18/09/08
-0,0154
-
-0,01552
-0,02653
-
-0,01795
-0,02224
-
19/09/08
0,082776
**
0,05634
0,02151
-
0,02611
0,05178
***
22/09/08
0,069023
*
0,05085
0,02258
-
0,02523
0,04578
***
25/09/08
0,025935
***
0,00911
0,00517
-
0,00199
0,01534
***
29/09/08
-0,04864
-
-0,04867
-0,04045
-
-0,03733
-0,04599
-
30/09/08
-0,02982
-
-0,03059
-0,01602
-
-0,01839
-0,02328
-
03/10/08
0,028446
-
0,01528
-0,00708
-
-0,00668
0,00969
***
06/10/08
-0,02005
-
-0,02705
-0,04049
-
-0,03531
0,032296612
-
07/10/08
-0,06232
-
-0,05844
-0,04963
-
-0,04824
-0,05770158
-
08/10/08
-0,04371
-
-0,04709
-0,03031
-
-0,0333
09/10/08
-0,03788
-
-0,02917
-0,02732
-
-0,0294
10/10/08
0,017713
-
0,004122
0,035686
-
0,023993
0,028486606
-
13/10/08
-0,00021
-
0,004917
0,03586
-
0,021803
0,019978578
-
14/10/08
0,079893
-
0,053551
0,075618
-
0,065694
0,080694613
-
15/10/08
-0,01756
-
-0,01736
-0,02577
-
-0,01703
16/10/08
-0,07693
*
-0,05115
-0,06337
-
-0,05496
17/10/08
-0,03706
-
-0,02444
-0,00726
-
-0,01496
0,037953725
0,033483119
0,022858528
0,072409526
0,021855866
-
**
-
19/10/08
-0,00065
-
-0,00497
0,04316
**
0,017656
0,023858496
-
21/10/08
0,032043
**
0,00839
0,020086
-
0,017844
0,026628764
*
0,034648309
0,044433235
24/10/08
-0,04171
-
-0,03304
-0,02612
-
-0,02988
28/10/08
-0,07967
***
-0,0301
-0,01106
-
-0,01662
29/10/08
0,012865
*
0,035999
0,051839
-
0,043049
0,035204584
-
30/10/08
0,082053
-
0,066492
0,058458
-
0,050462
0,072122241
**
03/11/08
0,02458
-
0,027462
0,029935
-
0,024952
0,028561831
-
***
0,02454819
0,02832177
0,00273187
5
0,00793078
0,02181694
0,01751834
0,03147082
0,02977564
7
0,00325653
8
0,03933863
0,02055526
0,00278826
0,03384895
0,05004571
0,03574702
0,02936161
0,02046952
5
0,01880891
1
0,06354110
8
0,01708504
0,05428304
0,01663986
0,01364443
1
0,01616781
7
0,03044346
0,01900880
0,04179869
7
0,05330437
8
0,02539671
3
MAR FIN
FV
0,0280124
0,0118275
0,0343622
0,0515733
0,0204199
46
0,0271722
0,0561467
0,0168041
0,0903007
55
0,0752976
57
0,0282925
96
0,0530590
0,0325314
0,0310323
94
0,0218735
0,0679807
0,0476788
0,0413255
0,0193236
87
0,0002342
0,0871557
13
0,0191564
0,0839199
0,0404310
0,0007074
0,0349555
47
0,0455022
0,0869131
0,0140341
31
0,0895128
17
0,0268144
42
Vs
MAR NON
FIN FV
**
-0,015984975
-
-0,009145902
-
-0,033346309
**
-0,034139326
***
-0,003417904
***
-0,005271214
***
-0,018455609
-
-0,0265281
***
0,021517771
***
0,022588908
***
0,005175259
-
-0,040451073
-
-0,01601907
***
-0,007077602
-
-0,040486158
-
-0,049625127
-
-0,030312589
-
-0,027321238
-
0,035686042
**
0,035860061
-
0,075618035
-
-0,025767282
-
-0,063365648
-
-0,007261104
-
0,043160311
-
0,020086292
*
-0,026120234
***
-0,011056124
***
0,051838511
**
0,058458217
-
0,029934779
05/11/08
0,04917
**
0,025139
0,012279
-
0,015582
09/11/08
0,023919
-
0,013728
0,013236
-
10/11/08
0,00923
-
0,009942
0,022018
-
0,030477496
**
0,016841
0,01889375
-
0,01614
0,016760441
***
**
-0,03868
-0,03502
-
-0,0317
0,051514662
-0,00017
-
-0,00494
0,009936
-
0,001751
0,005482149
-
-0,0632
***
-0,0347
-0,03934
-
-0,03737
0,052367698
***
21/11/08
-0,04404
***
-0,01964
-0,02344
-
-0,02542
-0,03426518
**
24/11/08
0,04488
*
0,026201
0,04712
*
0,028792
0,047930471
***
25/11/08
0,07592
***
0,034237
0,06429
**
0,043353
0,07244843
***
26/11/08
0,008548
-
0,005837
0,005336
-
0,005247
0,007091072
-
12/11/08
-0,06646
14/11/08
20/11/08
02/12/08
-0,01963
-
-0,01929
-0,01909
-
-0,01457
0,020113021
03/12/08
0,01985
**
-0,0012
0,013946
-
0,011492
0,017341502
***
05/12/08
-0,02182
-
-0,01975
0,018800248
0,029867
0,04721
**
0,032761
0,061029843
-0,01378
-0,01988
-
-0,01251
-0,01256
-0,0134
-
-0,00804
-1,4E-05
0,006578
-
0,00584
0,006678794
-
-0,00902
-0,00499
-
-0,00152
0,000568957
-
**
0,005516
-0,00896
-
-0,00487
0,013390889
**
-
0,006515
0,004915
-
0,005934
0,003152484
-
-
0,007702
0,013227
-
0,00947
0,013695604
-
-0,01371
-
-0,01668
09/12/08
0,07206
***
12/12/08
-0,02683
*
15/12/08
-0,03023
***
16/12/08
0,00624
-
19/12/08
0,007006
23/12/08
-0,01744
29/12/08
0,000833
31/12/08
0,013101
08/01/09
-0,00425
-
-0,00078
-0,00876
-
-0,01074
15/01/09
-0,03702
-
-0,04231
-0,03046
-
-0,03185
16/01/09
-0,00834
-
-0,02386
-0,0028
-
-0,0066
19/01/09
-0,02111
-
-0,05028
-0,00091
-
-0,00989
26/01/09
0,019944
-
0,034453
0,007232
-
0,014197
02/02/09
-0,01667
-
-0,01459
-0,01178
-
05/02/09
0,021729
-
0,023362
0,019414
-
-
0,001482
0,017509
-
0,010129
-0,01765
-0,01864
-
-0,01924
25/02/09
-0,00389
**
-0,01442
-0,00486
-
-0,00656
26/02/09
0,026555
-
0,010538
0,008028
***
0,009695
-0,04259
-
-0,0219
**
07/03/09
-0,03094
*
0,011205
09/03/09
-0,02225
-
0,005374
-
-0,01332145
-
05/03/09
-
0,020856597
-
03/03/09
**
-0,01238
-0,02713
-0,03564
-
0,019995
-0,00027
-
***
-
18/02/09
-0,04317
0,006833871
0,032320292
0,004483313
0,006736552
***
0,010776485
10/02/09
02/03/09
0,024010363
0,022010309
-0,02055
***
-0,03025
-0,03561
-0,02255
**
-0,02974
-0,03476
0,003844
-
-0,00582
-0,0111
-
-0,01129
-0,00822
*
-0,00902
0,012393635
0,020931926
0,004839379
0,013156088
0,027017404
0,028285054
0,003313389
0,017184082
-0,01248511
***
-
18/03/09
0,013681
*
0,005305
-0,00446
-
-0,0004
0,000596784
*
20/03/09
0,016426
-
0,034306
0,00627
-
0,010217
0,009168199
-
25/03/09
0,005316
-
0,005929
0,004969
-
0,007693
0,00526166
-
29/03/09
-0,0147
-
-0,00878
-0,01369
**
-0,0136
0,013986753
-
01/04/09
0,032214
-
0,040311
0,020597
*
0,026605
0,023907694
-
02/04/09
0,047772
-
0,054598
0,032206
-
0,03898
0,036749061
-
06/04/09
0,002747
-
0,015717
0,001806
-
0,001165
0,001929982
-
09/04/09
0,03539
-
0,022633
0,019834
*
0,019663
0,024155824
*
14/04/09
0,02397
-
0,018186
0,005738
-
0,009519
0,010907395
-
17/04/09
0,021573
-
0,020634
0,020262
-
0,016924
0,020714932
-
21/04/09
-0,02754
-
-0,02315
-0,01904
-
-0,01878
0,021311877
-
06/05/09
0,019444
-
0,025756
0,010033
-
0,011845
0,012529106
-
0,01727656
7
0,01628898
4
0,01504138
5
0,03293697
0,00056369
2
0,03689411
0,02439138
0,02833298
1
0,04173648
8
0,00535140
1
0,01540488
0,00924156
6
0,01908476
0,03224780
4
0,01273464
0,00883809
0,00480168
6
0,00285200
0,00303108
0,00603691
5
0,00915668
9
0,00957227
0,02590344
0,00283001
0,00660155
0,01092923
9
0,01252253
0,02083432
0,01348616
3
0,02078938
0,00728996
0,00648428
4
0,02599868
0,02861124
0,00449185
0,01194040
-0,009647
0,00356948
0,01060724
6
0,00604687
5
0,01007679
0,02428587
1
0,03596909
6
0,00469579
4
0,01897556
4
0,00916102
0,01890590
4
0,01856318
0,01073330
9
0,0536395
76
0,0260939
76
0,0100692
56
0,0725025
0,0001857
0,0689421
0,0480431
0,0489623
76
0,0828317
26
0,0093248
77
0,0214154
0,0216630
11
0,0149545
0,0786183
01
0,0292639
0,0329739
0,0068076
64
0,0076434
28
0,0190254
0,0009088
97
0,0142918
28
0,0014021
0,0369666
0,0086882
0,0213053
0,0196388
61
0,0171768
0,0223575
74
-9,96955E05
0,0266515
0,0047830
0,0259758
2
0,0431887
0,0426264
0,0212059
0,0323882
0,0231494
0,0132363
5
0,0164135
35
0,0059941
93
0,0147224
0,0321834
84
0,0481075
63
0,0022408
61
0,0349614
11
0,0238318
12
0,0218467
94
0,0269851
0,0187692
22
**
0,012278718
-
0,013236428
-
0,022017801
***
-0,03502415
-
0,009935522
***
-0,039344943
*
-0,023439633
-
0,047119689
-
0,064290125
-
0,00533594
-
-0,019089696
-
0,01394603
-
-0,021821882
**
0,047210339
-
-0,019882508
**
-0,013396018
-
0,006577538
-
-0,004989556
*
-0,008963722
-
0,004915302
-
0,013227142
-
-0,00900657
-
-0,03046173
-
-0,002801348
***
-0,000909026
**
0,007231535
*
-0,011779303
-
0,020256206
***
0,017168173
**
-0,018644066
-
-0,004861914
***
0,008028195
***
-0,020548861
***
-0,022548494
***
0,003843623
***
-0,011102403
***
-0,008219354
***
-0,004459043
**
0,006270065
-
0,004968646
-
-0,013692482
***
0,020597378
***
0,03220566
-
0,00180563
***
0,019833589
***
0,005737629
-
0,020262187
**
-0,019042553
**
0,010033059
-0,02939
-0,01371
-
-0,01454
0,019014795
-
0,03418
0,015351
-
0,016952
0,015515832
***
-0,00419
-0,0033
-
-0,0033
-
0,002347
6,03E-05
-
-0,00123
0,014256
-
0,021639
0,018615
-
0,016227
0,017322991
-
0,01232
-
0,00827
0,007362
-
0,006146
0,008733786
**
14/05/09
-0,03236
20/05/09
0,016005
21/05/09
-0,0055
28/05/09
-0,00824
02/06/09
10/06/09
**
0,003988427
0,002405632
0,018196659
0,000215412
***
*
**
17/06/09
-0,02593
-
-0,03475
-0,01501
-
-0,0158
26/06/09
0,000859
-
-0,00545
-0,00059
-
-0,001
29/06/09
0,008856
-
0,010318
0,009718
-
0,008264
02/07/09
-0,0073
-
-0,00587
0,00084
-
-0,00115
08/07/09
-0,01265
-
-0,01601
-0,0098
-
-0,01118
20/07/09
0,00751
-
0,008104
0,010311
-
0,008448
0,009518973
-
06/08/09
0,011293
-
0,011906
0,001275
-
0,002732
0,004033059
-
23/09/09
0,005325
-
0,010205
0,004789
-
0,004546
0,00500483
-
05/10/09
-0,0096
-
-0,01161
-0,00536
-
-0,00636
0,006571388
-
17/12/09
-0,00086
-
0,00018
9,13E-05
-
-0,00043
-0,00010156
-
11/04/10
0,018785
-
0,021305
0,013526
-
0,015512
0,014709752
-
02/05/10
0,001541
-
0,001127
-0,0019
-
8,92E-05
0,001128431
-
03/05/10
-0,00049
-
-0,0003
0,00116
-
0,001781
0,000788316
-
10/05/10
0,025555
-
0,024627
0,020946
-
0,020874
0,021983308
-
18/05/10
0,006155
-
0,002689
0,004209
-
0,002779
0,004646952
-
07/06/10
-0,02528
-
-0,02816
-0,01599
-
-0,0179
-0,01807859
-
22/06/10
-0,00409
*
0,002726
0,002358
-
0,002158
0,000907333
-
0,009459283
0,001558443
0,010579761
-
0,01143888
0,01895335
4
0,00047879
0,00143467
9
0,01648547
4
0,00564322
9
0,01639966
0,00100691
0,00758699
6
0,00069651
0,01034705
0,00775135
3
0,00233919
5
0,00364881
6
0,00569349
0,00095908
4
0,01624510
6
0,00022053
9
0,00151779
1
0,02134947
3
0,00276777
3
0,01919740
0,00222949
1
0,0322723
0,0159289
21
0,0057000
0,0085704
0,0140920
65
0,0121643
97
0,0261735
0,0007189
59
0,0088119
49
0,0075556
0,0125221
0,0075394
24
0,0109293
72
0,0055445
58
0,0095891
0,0005837
0,0187845
28
0,0015407
27
0,0004928
0,0255553
54
0,0061546
15
0,0252777
0,0040850
***
-0,013711779
-
0,015350597
-
-0,003303774
***
6,02753E-05
-
0,018615361
**
0,007361541
***
-0,015005909
-
-0,000589161
-
0,009718216
***
0,000840427
-
-0,009802817
-
0,010310792
***
0,001274534
-
0,004788939
**
-0,005364265
-
9,13184E-05
***
0,013526018
-
-0,001903829
-
0,001160493
***
0,020945619
-
0,004208972
***
-0,015987219
***
0,002357628
In this table, the events marked with * reported a coefficient statistically significant at 90%,
while those with ** and *** were found significant respectively at 95% and 99%.
Table 16: group of events
Table 17: OLS results for financial companies
FINANCIAL SAMPLE
Rescue
Variables
Capital Infusion
Distress
OLS
OLS with Dummy
OLS + F.E.
OLS
OLS with
Dummy
INTERCEPT
-0.000865
-0.026665
-0.035154
-0.003731***
-0.009302
0.017652
-0.002415
-
-0.330612
L1A
-1.13E-08
5.01E-08
-3.17E-08
-3.20E-10
-1.68E-07
6.08E-08
1.13E-08
-
9.11e-07
3.07e-07
OLS + F.E.
OLS
OLS with
Dummy
OLS + F.E.
L2A
8.13E-09
-1.01E-07
-2.97E-07*
8.39E-09
2.39E-07
1.065E-07
-6.13E-09
-
L3A
-7.36E-08***
-2.32E-07**
-1.61E-07
3.96E-09*
2.03E-07
9.67E-09
2.38E-09
-
1.12e-07
TOTNFA
1.32E-08
-3.43E-08
-8.78E-08
-2.40E-09
-4.27E-08
6.70E-08
2.26E-08
-
1.01e-06
L1L
1.27E-08
7.70E-08*
4.28E-08
4.27E-08
5.25E-08
3.64E-08
-2.74E-08
-
-2.76e-08
L2L
4.97E-08
4.70E-07
5.38E-07**
-4.56E-08
-8.09E-07**
-1.53E-07
2.44E-08
-
-5.78e-07
L3L
-1.48E-07**
-5.62E-07**
-4.08E-07
-6.73E-09
6.28E-07**
9.88E-08
-9.64E-08
-
-9.67e-07
TOTNFVL
-1.43E-08
4.75E-08
1.15E-07
2.54E-09
5.39E-08
-8.66E-08
-2.44E-08
-
-7.49e-07
DUMMY
-
0.001366
-
-
-0.006753
-
-
-
-
IMP. DUMMY
-
8.34E-07
-
-
1.12E-07
-
-
-
-
F stat
0.000069
0.999984
0.999982
0.144867
0.881092
0.99998
0.956071
-
1
Adj R2
0.018996
-0.070933
-0.070088
0.002108
-0.015682
-0.047908
-0.021129
-
-0.676447
Table 18: OLS results for non-financial companies
NON FINANCIAL SAMPLE
Variables
Rescue
Capital Infusion
Distress
OLS
OLS with
Dummy
OLS + F.E.
INTERCEPT
-0.001620
0.011169
-0.003245
-0.003992*** 0.014385
0.029405
-0.002673
-
-0.309033
L1A
-4.19E-08
9.30E-07
5.21E-08
2.51E-08
-2.38E-06
-2.05E-06
-1.90E-09
-
3.83E-06
L2A
-6.02E-09
-6.87E-07
1.37E-06
-1.06E-07
-1.23E-06
-2.82E-06*
5.76E-07
-
-4.10E-07
L3A
3.26E-08
3.74E-08
2.88E-07
7.23E-08
1.17E-06
8.31E-07*
-3.57E-07
-
-3.65E-06
OLS
with Dummy
OLS + F.E.
OLS
OLS with
Dummy
OLS + F.E.
TOTNFA
1.72E-09
-3.82E-07
-7.50E-08
-2.77E-10
-5.08E-08
-4.18E-07
-1.50E-08
-
1.64E-06
L1L
-3.08E-07
-1.91E-06
-2.03E-06
3.40E-08
1.56E-06**
-9.54E-09
2.09E-07
-
-8.87E-06
L2L
2.42E-07
1.29E-06
1.29E-06
7.14E-08
1.14E-07
1.16E-06
-4.76E-07
-
5.15E-06
-4.20E-08
L3L
3.19E-07
-1.10E-06
-1.81E-06
-3.05E-06
-1.59E-07
9.07E-08
-
-8.43E-06
TOTNFVL
-1.29E-09*
-4.01E-09***
-4.05E-09*** 5.04E-10
1.09E-09
1.10E-09
-1.61E-09
-
3.20E-06
DUMMY
-
0.019207***
-
-
-0.005012
-
-
-
-
IMP. DUMMY
-
6.40E-05
-
-
-0.000104
-
-
-
-
F stat
0.432796
1
1
0.629155
0.988732
0.579904
0.991829
-
1
0.000010
-0.092071
-0.091655
-0.0000934
-0.029189
-0.053201
-0.025389
-
-0.685782
Adj R
2
Table 19: OLS results for full sample
Table 20: OLS with control variables for financial companies
FINANCIAL SAMPLE
Variables
Rescue
Capital Infusion
OLS
OLS
Dummy
INTERCEPT
-0.00092
L1A
L2A
with
OLS
Dummy
Distress
with
OLS + F.E.
OLS
OLS
with
OLS + F.E.
Dummy
-0.093392
-0.002458
-
OLS + F.E.
OLS
-0.039302
0.109531
-0.002022*** 0.669518
-3.3E-08
2.70E-07
1.92E-08
2.19E-08
-4.12E-07**
7.27E-08
5.47E-09
-
5.47E-09
-4.42E-08
1.67E-07
-2.06E-07
5.09E-08
-2.50E-07
7.27E-08
-1.53E-08
-
-1.53E-08
L3A
-8.83E-08***
-3.13E-07***
-1.48E-07
1.50E-08
4.87E-07*
-1.15E-08
1.41E-08
-
1.41E-08
TOTNFA
-2,85E-08
2.56E-07
7.83E-09
2.69E-08
-5.70E-07**
6.56E-08
1.79E-08
-
1.79E-08
L1L
3.43E-08
1.25E-07**
4.89E-08
2.27E-08
-3.17E-07
3.44E-08
-3.67E-08
-
-3.67E-08
L2L
1.08E-07
3.11E-07
4.07E-07
-8.40E-08
-6.51E-08
-6.81E-08
3.25E-08
-
3.25E-08
L3L
-1.16E-07*
-3.14E-07*
-1.26E-07
1.17E-09
-5.51E-07
-8.87E-08
-1.08E-07
-
-1.08E-07
TOTNFVL
3.09E-08
-1.12E-07
6.76E-08
-2.92E-08
1.85E-07
-7.43E-08
-2.07E-08
-
-2.07E-08
EBIT
3.61E-08
-7.01E-07
-2.50E-07
-1.63E-08
-0.318520**
-0.204826*** 3.95E-07
-
3.95E-07
ROA
0.216805***
0.164542***
0.171029**
-0.163587*** 0.523640**
0.366249
-0.004358
-
-0.004358
OPACT
-5.93E-09
1.46E-07
5.18E-08
4.49E-09
2.08E-06
-6.80E-08
3.27E-08
-
3.27E-08
LEV
-0.008754***
-0868957***
-0.857364*** -0.001817
-3.71E-07*
6.92E-09
0.000355
-
0.000355
DUMMY
-
0.006174
-
-
0.002011
-
-
-
-
IMP. DUMMY
-
1.37E-06
-
-
9.11E-07
-
-
-
-
F stat
0.000020***
0.998144
0.998513
0,001768
0.66154
0.9999971
0.995392
-
0.995392
Adj R2
0.025229
-0.051021
-0.051021
0,010369
-0.005942
-0.043075
-0.036674
-
-0.036674
-0.002458
Table 21: OLS with control variables for non-financial companies
Variables
Rescue
Capital Infusion
OLS
OLS
Dummy
INTERCEPT
-0.05653***
L1A
1.27E-07
L2A
L3A
with
OLS + F.E.
OLS
0.016602
0.002330
1.51E-06
-7.05E-07
3.22E-07
-1.35E-06
1.64E-07
-2.86E-07
TOTNFA
1.91E-07**
L1L
with Dummy
Distress
OLS
with
OLS + F.E.
Dummy
OLS + F.E.
OLS
-0.005283*** 0.036045
0.049048*
-0.003117 -
-3.241329
1.13E-07**
-2.53E-06
-1.22E-06
4.90E-08
-
8.29E-05
8.92E-07
2.74E-08
-2.45E-06
-5.49E-06*** 7.99E-07
-
2.59E-05
7.75E-07
1.55E-07
2.63E-06*
1.46E-06**
-2.54E-07
-
8.81E-06
-6.90E-07
-8.68E-08
8.29E-08
5.11E-07
-1.53E-07
-8.88E-08
-
2.69E-05
-4.59E-07
-2.30E-06***
-2.13E-06*
-1.03E-07
1.04E-06
1.31E-06
1.52E-07
-
-2.51E-05
L2L
-1.86E-07
2.11E-06
1.32E-06
-5.81E-08
-5.65E-07
3.17E-07
-5.9E-07
-
7.53E-06
L3L
-5.30E-08
-6.05E-07
-1.45E-06
-2.37E-07
-7.4E-06
1.61E-06
1.03E-07
-
2.16E-05
TOTNFVL
-2.20E-07***
3.09E-07
1.03E-09
-1.00E-07*
-1.27E-06
-8.80E-07*** 6.27E-09
-
3.43E-07
EBIT
7.21E-07
4.36E-06**
3.99E-06*
4.73E-07
0.015217
0.021837
-9.02E-08
-
0.281114
ROA
-0.009286
-0.026704**
-0.024886** 0.003799
0.033534
0.023160*** 0.017326
-
0.688492
OPACT
-3.86E-07
-3.81E-06**
-3.25E-06*
-2.14E-07
1.80E-06
7.94E-07
4.78E-07
-
4.55E-05
LEV
0.005748***
-0.008223
-0.000138
0.002648**
-3.40E-08
-1.41E-07
-0.000206 -
-5.13E-05
DUMMY
-
0.006284
-
-
-0.011165
-
-
-
-
IMP. DUMMY
-
0.000125
-
-
-0.000131
-
-
-
-
-
F stat
0.036011**
0.999999
0.99999
0.295057
0.994978
0.99999
0.998000
Adj R2
0.008242
-0.079703
-0.079673
0.001130
-0.049220
-0.050610
-0.038676 -
Table 22: OLS with control variables for full sample
1
-0.764158
Table 23: PLS results for financial companies.
FINANCIAL SAMPLE
Variables
Rescue
Capital Injections
Suffering
PLS
-0,0112855
PLS cross-val
PLS
PLS cross-val
PLS
PLS cross-val
-0,0122181
-0,0074661
-0,0081766
-0,0112855
-0,0122181
L1A
-1,4517e-8
8,66235e-9
4,40396e-9
2,9827e-10
-1,4517e-8
8,66235e-9
L2A
5,76497e-9
1,06687e-8
1,14035e-8
1,5503e-9
5,76497e-9
1,06687e-8
L3A
-7,1609e-8
-1,9546e-8
2,82719e-8
4,41437e-9
-7,1609e-8
-1,9546e-8
TOTNFVA
-1,4184e-8
-3,732e-11
5,58167e-9
-8,265e-12
-1,4184e-8
-3,732e-11
L1L
4,92755e-8
2,01814e-9
7,83695e-9
4,22598e-9
4,92755e-8
2,01814e-9
L2L
1,71311e-8
9,99768e-9
-3,679e-8
2,11681e-9
1,71311e-8
9,99768e-9
L3L
-9,1529e-8
-9,9572e-8
1,77072e-8
1,03574e-8
-9,1529e-8
-9,9572e-8
TOTNFVL
1,52088e-8
-3,908e-11
-6,042e-9
-8,912e-12
1,52088e-8
-3,908e-11
DUMMY
-
-
-
-
-
-
INTERCEPT
IMP. RICLAS.
-
-
-
-
-
-
N° VECTORS
8
2
8
1
8
2
Table 24: PLS results for non-financial companies.
Variables
Rescue
Capital Infusion
Distress
PLS
-0,0057968
PLS cross-val
PLS
PLS cross-val
PLS
PLS cross-val
-0,0055973
-0,0032537
-0,0033473
-0,0014155
-0,002465
L1A
-3,4799e-8
-1,5952e-8
9,30976e-9
6,43157e-9
1,26763e-8
-3,5051e-9
L2A
-7,0743e-8
-7,2969e-9
-5,6372e-8
6,25341e-9
6,53445e-7
6,90408e-9
L3A
4,82277e-8
-6,1108e-9
9,51978e-8
7,99924e-9
-3,3914e-7
3,66556e-9
TOTNFVA
1,19801e-9
-9,863e-11
-2,83e-10
1,6338e-10
-2,9832e-8
-7,585e-10
L1L
-7,2185e-8
-1,0372e-8
-2,2075e-9
1,33233e-8
2,24147e-7
4,02021e-9
L2L
1,07847e-7
-9,9008e-9
-1,4977e-8
1,0586e-8
-5,7984e-7
5,16103e-9
L3L
2,4933e-7
9,73074e-8
-6,4954e-8
-1,0899e-8
6,80224e-8
-9,5358e-8
TOTNFVL
-1,0582e-9
-4,423e-10
4,6672e-10
1,2381e-10
-1,6539e-9
-1,6389e-9
DUMMY
-
-
-
-
-
-
IMP. RICLAS.
-
-
-
-
-
-
N° VETTORI
8
1
7
1
8
2
INTERCETTA
Table 25: PLS results for full sample.

fair value disclosure, liquidity risk and stock returns.

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