L’iniziativa di Finriskalert.it “Il termometro dei mercati finanziari” vuole presentare un indicatore settimanale sul grado di turbolenza/tensione dei mercati finanziari, con particolare attenzione all’Italia.
Significato degli indicatori
Rendimento borsa italiana: rendimento settimanale dell’indice della borsa italiana FTSEMIB;
Volatilità implicita borsa italiana: volatilità implicita calcolata considerando le opzioni at-the-money sul FTSEMIB a 3 mesi;
Future borsa italiana: valore del future sul FTSEMIB;
CDS principali banche 10Ysub: CDS medio delle obbligazioni subordinate a 10 anni delle principali banche italiane (Unicredit, Intesa San Paolo, MPS, Banco BPM);
Tasso di interesse ITA 2Y: tasso di interesse costruito sulla curva dei BTP con scadenza a due anni;
Spread ITA 10Y/2Y : differenza del tasso di interesse dei BTP a 10 anni e a 2 anni;
Rendimento borsa europea: rendimento settimanale dell’indice delle borse europee Eurostoxx;
Volatilità implicita borsa europea: volatilità implicita calcolata sulle opzioni at-the-money sull’indice Eurostoxx a scadenza 3 mesi;
Rendimento borsa ITA/Europa: differenza tra il rendimento settimanale della borsa italiana e quello delle borse europee, calcolato sugli indici FTSEMIB e Eurostoxx;
Spread ITA/GER: differenza tra i tassi di interesse italiani e tedeschi a 10 anni;
Spread EU/GER: differenza media tra i tassi di interesse dei principali paesi europei (Francia, Belgio, Spagna, Italia, Olanda) e quelli tedeschi a 10 anni;
Euro/dollaro: tasso di cambio euro/dollaro;
Spread US/GER 10Y: spread tra i tassi di interesse degli Stati Uniti e quelli tedeschi con scadenza 10 anni;
Prezzo Oro: quotazione dell’oro (in USD)
Spread 10Y/2Y Euro Swap Curve: differenza del tasso della curva EURO ZONE IRS 3M a 10Y e 2Y;
Euribor 6M: tasso euribor a 6 mesi.
I colori sono assegnati in un’ottica VaR: se il valore riportato è superiore (inferiore) al quantile al 15%, il colore utilizzato è l’arancione. Se il valore riportato è superiore (inferiore) al quantile al 5% il colore utilizzato è il rosso. La banda (verso l’alto o verso il basso) viene selezionata, a seconda dell’indicatore, nella direzione dell’instabilità del mercato. I quantili vengono ricostruiti prendendo la serie storica di un anno di osservazioni: ad esempio, un valore in una casella rossa significa che appartiene al 5% dei valori meno positivi riscontrati nell’ultimo anno. Per le prime tre voci della sezione “Politica Monetaria”, le bande per definire il colore sono simmetriche (valori in positivo e in negativo). I dati riportati provengono dal database Thomson Reuters. Infine, la tendenza mostra la dinamica in atto e viene rappresentata dalle frecce: ↑,↓, ↔ indicano rispettivamente miglioramento, peggioramento, stabilità rispetto alla rilevazione precedente.
Disclaimer: Le informazioni contenute in questa pagina sono esclusivamente a scopo informativo e per uso personale. Le informazioni possono essere modificate da finriskalert.it in qualsiasi momento e senza preavviso. Finriskalert.it non può fornire alcuna garanzia in merito all’affidabilità, completezza, esattezza ed attualità dei dati riportati e, pertanto, non assume alcuna responsabilità per qualsiasi danno legato all’uso, proprio o improprio delle informazioni contenute in questa pagina. I contenuti presenti in questa pagina non devono in alcun modo essere intesi come consigli finanziari, economici, giuridici, fiscali o di altra natura e nessuna decisione d’investimento o qualsiasi altra decisione deve essere presa unicamente sulla base di questi dati.
In the first part of this
article, we sketched a general framework to calculate the bank’s value. In this
second part of the article, we will show how to apply the framework to the
evaluation of a contract that is inserted in the existing bank’s balance sheet
and how to properly compute the xVAs quantities. Finally, we will see how to
conciliate the apparently theoretical unsound market practices to evaluate
derivative contracts, and the nowadays standard results of the modern financial
theory, namely the Modigliani-Miller (MM) theorem (see Modigliani and Miller,
[3]).
An extended version of this work, with the details of the analytical results, is available at www.iasonltd.com in the research section.
2 A Non-Trivial Set-Up to Evaluate Contracts
We can specify the general framework sketched in the first part to evaluate the incremental contribution of a contingent claim in the balance sheet of the bank. First, we outline how to calculate the value of the bank; then, we will assess how the insertion of a new contract in the bank’s balance sheet impacts the value.
3 Incremental Valuation of a New Contract
4 Reconciliation with the Modigliani&Miller
Theorem
Elsewhere,[1] we had to opportunity to stress that the incremental valuation framework that we introduced above is not in contrast with the main tenet of the Modigliani&Miller (MM) theorem, expounded by the two authors in their article of 1958 (see [3]).[2] On the contrary, when evaluating an investment that is included within the balance sheet of a company (bank) that has already started its operations, then the only way to keep the total value of the assets of the company equal to the total value of the liabilities, is to apply the principles of the incremental valuation stated in Castagna [2] to the non trivial framework sketched above.
In the recent work by Andersen et al. [1], the Modigliani&Miller theorem is proved to be correct when calculating the incremental value of a contract with respect to the total firm value, which is equal to the total value of the assets. In this case, the authors prove that the correct incremental value is given by the “pure” value, deducted of the CVA and incremented by the DVA, and it is independent from the way it is financed.
In our framework, we calculate
the value of a contract only with respect to the value of the bank to the
shareholders, because we think this is the only meaningful way the indifference
to inclusion of the contract in the balance sheet to all stakeholders. When
considering the total value of the firm, the evaluator allows for wealth
transfers from shareholders to claimants of higher order, such as bondholders
(see Andersen et al. [1], pag. 159). On the contrary, when considering
the incremental value with respect to the shareholders’ bank value, no wealth
transfer is allowed and the contract value is such that all claimants are
indifferent to it. Sure, such a value entails additional costs that have to be
paid by the counterparty, but here we enter in the market action, where the
price of the contract is determined. The price can be set at a level that
matches the internal incremental valuation of the bank, thus generating a nil
net contribution to the bank value; or it can be different, with a net positive
or negative contribution. In any case, the price setting is the result of the
bargaining process where the strengths of the bank and of the counterparty
clashes and, possibly, they eventually agree to close the deal.
We think that the approach
that we have detailed above and that relies on the simpler, but in any case
complete, setting in Castagna [2], is in line with Proposition III of
Modigliani and Miller [3], where the the optimal investment rule is derived:
basically, when the firm (i.e.: the manager) is acting in the shareholders’
best interest, it will undertake an investment only if its rate of return is at
least equal, or above the rate of return required by the market for a class of
risk corresponding to the riskiness of the firm. In our approach, we are
internally setting the rate of return of a new contract by adding all the
adjustments that make its rate of return equal to the appropriate rate of
return. The latter is determined by the current composition of the assets and
their related risks, and by the debt and equity capital financing it, whose
costs mirror the leverage and the risk premium above the risk-free rate
requested by the debt-holders and shareholders.
In our opinion, in Modigliani
and Miller [3] it is Proposition III that has a normative value and that should
be considered when designing a framework to evaluate new contracts. Proposition
I and II, in the same article, have a positive value describing the equilibrium
that can be retrieved ex post, equating the return of the assets to the
average cost of capital, whichever mix the firm chooses to finance them. But
both propositions are not including investments that produce a loss of wealth
of one of the stakeholders in favour of another stakeholder: these investments
are clearly excluded by Proposition III. Following the latter, we were able to
derive the rules that determine the hurdle rate at which the actual
contribution of contract to the (shareholders’ bank value) is nil. It is clear
that accepting only the investments that comply with Proposition III, also
Proposition I and II will be proved to be true, provided we are working in a
frictionless, perfect financial market.
5 Conclusion
In this work we have extended the approach of
Castagna [2] to a non-trivial setting to calculate the incremental value of a
contract that is included in the bank’s balance sheet. A similar approach has
been recently developed by see Andersen et al. [1]. To our knowledge,
our framework is richer than those appeared since now in literature, in that we
include a firm structural framework within a classical general equilibrium
framework.
The framework considers different financing policies and consistently derives all the adjustment to the “pure” value of a contract, including the CVA , the FVA and, implicitly, the LLVA . We are also able to derive, in a natural fashion, an adjustment that relates to the KVA. In our structural, general-equilibrium enhanced framework setting, we do not only flesh out the origin of the KVA, but we can also identify the cases in which its inclusion is admissible in the evaluation, which is the correct premium to consider and, moreover, we can spot potential double counting of the adjustment.
References
[1] L Andersen, D. Duffie, and Y.. Song. Funding value adjustmentss. Journal of Finance, LXXIV(1):145–191,
2019.
[2] A. Castagna.
Towards a theory of internal valuation and transfer pricing of products
in a bank: Funding, credit risk and economic capital. Iason research paper. Available at
http://www.iasonltd.com, 2013.
[3] F. Modigliani and M.H. Miller. The cost of capital, corporation finance and
the theory of investment. The
American Economic Review,
48(3):261–297, 1958.
[2] We would like to
recall here the MM theorem proves that the value of a project is independent
from the way it is financed, or from the capital structure of the company
undertaking it.
The European Banking Authority (EBA) published today the findings of its analysis on the regulatory framework applicable to FinTech firms when accessing the market…
ESMA, in its advice, has assessed the level of consideration of Environmental, Social and Governance (ESG) factors in both specific credit rating actions…
Consob ha pubblicato il nuovo Quaderno FinTech n. 5 del luglio 2019 sul tema “Marketplace lending: verso nuove forme di intermediazione finanziaria?” …
L’iniziativa di Finriskalert.it “Il termometro dei mercati finanziari” vuole presentare un indicatore settimanale sul grado di turbolenza/tensione dei mercati finanziari, con particolare attenzione all’Italia.
Significato degli indicatori
Rendimento borsa italiana: rendimento settimanale dell’indice della borsa italiana FTSEMIB;
Volatilità implicita borsa italiana: volatilità implicita calcolata considerando le opzioni at-the-money sul FTSEMIB a 3 mesi;
Future borsa italiana: valore del future sul FTSEMIB;
CDS principali banche 10Ysub: CDS medio delle obbligazioni subordinate a 10 anni delle principali banche italiane (Unicredit, Intesa San Paolo, MPS, Banco BPM);
Tasso di interesse ITA 2Y: tasso di interesse costruito sulla curva dei BTP con scadenza a due anni;
Spread ITA 10Y/2Y : differenza del tasso di interesse dei BTP a 10 anni e a 2 anni;
Rendimento borsa europea: rendimento settimanale dell’indice delle borse europee Eurostoxx;
Volatilità implicita borsa europea: volatilità implicita calcolata sulle opzioni at-the-money sull’indice Eurostoxx a scadenza 3 mesi;
Rendimento borsa ITA/Europa: differenza tra il rendimento settimanale della borsa italiana e quello delle borse europee, calcolato sugli indici FTSEMIB e Eurostoxx;
Spread ITA/GER: differenza tra i tassi di interesse italiani e tedeschi a 10 anni;
Spread EU/GER: differenza media tra i tassi di interesse dei principali paesi europei (Francia, Belgio, Spagna, Italia, Olanda) e quelli tedeschi a 10 anni;
Euro/dollaro: tasso di cambio euro/dollaro;
Spread US/GER 10Y: spread tra i tassi di interesse degli Stati Uniti e quelli tedeschi con scadenza 10 anni;
Prezzo Oro: quotazione dell’oro (in USD)
Spread 10Y/2Y Euro Swap Curve: differenza del tasso della curva EURO ZONE IRS 3M a 10Y e 2Y;
Euribor 6M: tasso euribor a 6 mesi.
I colori sono assegnati in un’ottica VaR: se il valore riportato è superiore (inferiore) al quantile al 15%, il colore utilizzato è l’arancione. Se il valore riportato è superiore (inferiore) al quantile al 5% il colore utilizzato è il rosso. La banda (verso l’alto o verso il basso) viene selezionata, a seconda dell’indicatore, nella direzione dell’instabilità del mercato. I quantili vengono ricostruiti prendendo la serie storica di un anno di osservazioni: ad esempio, un valore in una casella rossa significa che appartiene al 5% dei valori meno positivi riscontrati nell’ultimo anno. Per le prime tre voci della sezione “Politica Monetaria”, le bande per definire il colore sono simmetriche (valori in positivo e in negativo). I dati riportati provengono dal database Thomson Reuters. Infine, la tendenza mostra la dinamica in atto e viene rappresentata dalle frecce: ↑,↓, ↔ indicano rispettivamente miglioramento, peggioramento, stabilità rispetto alla rilevazione precedente.
Disclaimer: Le informazioni contenute in questa pagina sono esclusivamente a scopo informativo e per uso personale. Le informazioni possono essere modificate da finriskalert.it in qualsiasi momento e senza preavviso. Finriskalert.it non può fornire alcuna garanzia in merito all’affidabilità, completezza, esattezza ed attualità dei dati riportati e, pertanto, non assume alcuna responsabilità per qualsiasi danno legato all’uso, proprio o improprio delle informazioni contenute in questa pagina. I contenuti presenti in questa pagina non devono in alcun modo essere intesi come consigli finanziari, economici, giuridici, fiscali o di altra natura e nessuna decisione d’investimento o qualsiasi altra decisione deve essere presa unicamente sulla base di questi dati.
European banks are still experiencing a difficult situation, also dictated by the political-economic tone we are experiencing recently, the CER has focused on the problem in its Banking Report N.1 2018, based on 2014-2016 data, however in this article the analysis compared to the report it was also extended to 2017.
Analyzing a
sample proposed by Mediobanca, consisting of about 20 larger European banks, we
can see which are the business models that characterize the banks of the old
continent and the composition of their assets in the portfolio. The analysis
was carried out over the 2014-2017 four-year period. The total average assets
of the sample amounted to 1,070 billion euros in 2017. The largest banking
group is HSBC, with total assets of 2,192 billion euros. Overall, the 21
banking institutions hold assets of 1,900 trillion euros. The average ROE in
the four-year period considered was 4.2%.
The German
banks (25%), Nordea (24%) and Barclays (22%) are the ones that show the highest
values (chart 1). The heaviest incidences are observed for Unicredit, Groupe
BPCE and ING Group. The two Italian groups considered in the number, namely
Unicredit and Intesa-San Paolo, have taken an incidence of 6% and 7%.
Even more interesting and third level. These financial instruments are illiquid and opaque, having complex structures and prices that are difficult to recognize. These parameters are not compatible with the standards. To take account of these valuation uncertainties, the accounting rules impose greater provisions and deductions from capital (additional valuation adjustments, AVA) for these instruments. However, adjustments are not calculated at the individual instrument level. Furthermore, the L3 instruments are more disadvantaged than the L2 ones, it is an incentive to hold this second form of activity.
Chart 1. Incidence of active derivatives Source: CER calculations on Mediobanca Data
Deutsche
Bank is the bank with the greatest presence of L2 and L3 in its portfolio: in
2014, around 51% of total assets, to then decrease in 2017 to 44%, a level that
is still on the increase compared to the previous year (chart2). Barclays and
RBS follow. Italian banks are not particularly inclined to invest in L2 and L3
instruments. Both Unicredit and Intesa-San Paolo hold a percentage of the total
assets among the lowest in the sample.
From the Mediobanca data relating to 2016 it appears that the L3 instruments consist almost 30% of derivative securities, 24.5% of equity securities and mutual funds, 20% of debt securities, 13.7% of loans and 12 .1% from other assets.
Chart 2. Incidence of 2nd and 3rd level assets Source: CER calculations on Mediobanca Data Chart 3. Incidence of Loans Source: CER calculations on Mediobanca Data
Ultimately,
analyzing the incidence of riskier assets shows a particularly heterogeneous
situation. German and French banks have invested heavily in L2 and L3
instruments. Another group of banks, including the Italian ones, seems to
suffer due to non-performing loans. Anglo-Saxon banks, on the other hand,
operate in a framework in which both impaired loans and more complex financial
assets are present in their financial statements. Finally, the remaining part
of the institutions appears to have particularly prudent asset management, as
evidenced by the low incidence of riskier assets.
Possible impacts of business
choices on systemic risk
The
economic and financial debate today is very focused on the possible systemic
impacts, in this regard the Mediobanca database has been integrated with the
information provided by the New York University Ster Volatility Lab.
Specifically, the SRISK has been considered, indicator expresses the quantity
of systemic risk connected with each listed company. The percentage share of
SRISK with respect to the total of the sample was therefore calculated for each
bank.
From the
data of the NYU Stern Volatility Lab emerges as the banks with the greatest
systemic impact, in 2017, are Bnp Paribas, with a share of systemic risk of
14%, and Deutsche Bank (13% chart.4).
This is followed by Barclays, Crédit Agricole and Société Generale. Unicredit and Intesa San Paolo account for 3.9% and 3% of the largest banks respectively.
Chart 4. Incidence of systemic risk in systemically important European banks Source: CER calculations on Mediobanca Data
Overall, the systemic risk of European banks attributable to French banks is 39%, 19% for the British, 16% for the German, 8% for the Spanish 7% for the Italian, 5% for the Swiss.
The same percentage share of the total of the sample was calculated for the most risk activities that characterize the business model based on credit and finance, or NPL, on the one hand, and L2 and L3 instruments, on the other. By relating this information to that relating to systemic risk, for the period 2014-2017, there are important indications (chart 5).
Chart.5 Systemic risk, complex financial assets and NPL (data for the 2014-2017 period) Notes: sample of the top 20 significant banks in Europe. RISK expressed in% of the total sample. Source: CER calculations on Mediobanca Data
The relationship
between the share of the L2 and L3 instruments and that of systemic risk is
strictly positive, which confirms that the impact of an eventual collapse of an
institution, caused by problems deriving from excessive financial risks
assumed, can have a serious impact on the whole market, jeopardizing its
stability.
On the
other hand, the relationship between the share of NPLs and that of systemic
risk is slightly negative, highlighting that credit risk has no significant
impact on global financial stability.
The undervaluation of market risk could have significant effects on the financial system. In fact, there does not appear to be a relationship between the SRISK share and the CET 1 ratio, a sign that the greater systemic risk does not push bank managers to hold more capital for the purposes of complying with the Basel requirements (chart 6). The fact that systemic risk is not adequately computed among the risks managed by European banks can be observed by looking at the relationship with the ratio between CET1 and total assets (an improper leverage ratio). In this case the relationship is even negative: those with more systemic risk have a lower proportion of good quality capital than the total assets. This implies that if the financial markets slow down significantly, the banks most exposed to the L2 and L3 instruments would quickly exhaust their capital endowment.
Chart.6 Systemic risk and capital endowment (data for the period 2014-2017) Notes: sample of the top 20 significant banks in Europe. RISK expressed in% of the total sample. Source: CER calculations on Mediobanca Data
This theme
is strongly in line with the modern economic debate and recently the hypothesis
of a possible merger between Unicredit and Commerzbank was born (the first
hypothesis that the merger between Deutsche Bank and Commerzbank was avoided),
but the merger between high banks impact (in Italy for Unicredit and on a large
scale for Commerzbank) and with different business models (Commerzbank has a
strong presence on its balance sheet levels 2 and fully concentrates its
business model on finance, Unicredit instead on credit) is a solution to be
adopted?
However,
the regulatory authorities do not seem to worry about this, taking advantage of
the concept “too big to fail”
At 2017,
for Commerzbank the percentage of derivatives on total assets stood at 20%,
while for Unicredit the share was much lower (6%). For second and third level
activities (highly opaque and with a very high degree of risk), the percentage
of total assets at 2017 was 16% for Commerzbank and 8% for Unicredit. The
dynamics is completely reversed, while if we consider the NPLs, on the total
loans the Unicredit share at 2017 was 4% (down compared to 2014 8%), for the
German group instead, the value barely touched the 1%.
Can be seen
from the previous analysis, the 2 and 3 level activities have a very different
systemic impact, compared to the NPL
Concluding:
The
regulatory authorities should have a very strong role in the hypothetical
merger between these two groups, and in particular to understand if the merger
will have positive returns or if instead we only risk creating a “systemic
giant”.
The
following analysis shows how the potential stresses facing the banks should not
be underestimated, in fact in this regard the EBA introduced the benchmark
models for the 2018 stress test to verify the consistency of the results
obtained by the institutes from their assessments internal. The EBA has not
gone as the Federal Reserve to establish homogeneous parameters for all banks,
but uses these models only to highlight anomalies. However, the benchmark
models will be used to estimate credit risk, thus leaving open the possibility
of manipulating market risk.
References:
Banca d’Italia,
Relazione annuale per il 2017, maggio 2018;
Banca d’Italia, “Risks and challenges of
complex financial instruments: an analysis of SSM banks”;
ESMA still has serious concerns about firms’ marketing, distribution or sale of CFDs to retail clients and considers it necessary to remind CFD providers about some of the requirements connected with the offering of CFDs…
Why are interest rates so low today? Many believe that the worldwide abundance of savings is due to the retirement of OECD baby-boomers and the Chinese one-child policy…
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