Giu 212016
 

Abstract

We applied the Johansen-Ledoit-Sornette (JLS) model to detect possible bubbles and crashes related to the Brexit/Bremain referendum scheduled for 23rd June 2016. Our implementation includes an enhanced model calibration using Genetic Algorithms. We selected a few historical financial series sensitive to the Brexit/Bremain scenario, representative of mutiple asset classes.

We found that equity and currency asset classes show no bubble signals, while rates, credit and real estate show super-exponential behaviour and instabilities typical of bubble regime. Out study suggests that, under the JLS model, equity and currency markets do not expect crashes or bursts following the referendum results, thus supporting a Bremain scenario. Instead, rates and credit markets consider the referendum a risky event, expecting either a Bremain scenario or a Brexit scenario edulcorated by central banks intervention. In the case of real estate, a crash is expected, but its relationship with the referendum results is questionable.

1.    Brexit or Bremain ?

On Dec. 17, 2015 the Parliament of the United Kingdom approved the European Union Referendum Act 2015 to hold a referendum on whether the United Kingdom should remain a member of the European Union (EU).

The referendum will be held* on Jun. 23, 2016, with the following Q&A:

  • Q: ”Should the United Kingdom remain a member of the European Union or leave the European Union?
    • A1: “Remain a member of the European Union”
    • A2: “Leave the European Union”

In case of Brexit decision, there is no immediate withdrawal. Instead, a negotiation period begins to establish the future relationship between UK and EU. The negotiation length is two years, extendible. For example, the agreements between EU and Switzerland took 10 years of negotiations.

Referendum campaigning has been suspended on 16th June 2016 following the shooting of Labour MP Jo Cox. This event has had a strong impact on the public opinion, rapidly changing the opinion polls and possibly the attitude of the country.

Forecasting the results of the 23rd June 2016 referendum is clearly a very challenging task. There exist at least three sources of forecast data:

  • Opinion polls [5] [7]
  • Bookmakers betting odds [6]
  • Market data [7]

In this paper we recur to a different forecasting approach, described in the next section.

2.    Methodology

We applied a forecasting methodology based on the Johansen-Ledoit-Sornette (JLS) model, developed since the 90s at ETHZ by D. Sornette and co-authors [1][2]. The JLS model is extensively applied to detect bubbles, crashes and crisis analysis in many fields. For applications in finance see e.g. the Financial Crisis Observatory [3].

The JLS model assumes that, during a bubble regime, the asset mean value follows a super-exponential path showing log-periodic instabilities, the so called Log-Periodic Power-Law function, up to a critical time tc, representing the most probable time for a possible crash event,

LPPL(t) = A + B (tc – t)m + C (tc – t)m cos(ω log(tc – t) + φ).

The seven JLS parameters (A, B, C, m, ω, φ, tc) must be calibrated to fit the asset’s historical series.

 Our implementation of the JLS model is based on JLS papers [1][2], enhanced with robust global optimization methods, i.e. Genetic Algorithms for model calibration [4].

 We applied the JLS model to a selection of historical financial series sensitive to the current Brexit/Bremain scenario. For each series, we have run multiple model calibrations with different calibration windows, to ensure the stability of the observed results.

 3.    Results

The results are reported in the following figures Figure 1Figure 8, and the comments are included in their corresponding captions.

Figure 1

  • Source: Brexit Equity Index (Bloomberg BBRXEQT Index), basket of 10 UK stocks designed to reflect British exposure to the EU across different sectors. Data up to Friday 17th June 2016.
  • Comments: the historical series shows a decreasing trend, but no super-exponential behaviour and instabilities typical of bubble regime. In fact, the JLS model (LPPL fit) does not propose valid bubble and crash signals.
  • Interpretation: market participants are currently suspicious about UK stock market, but do not actually fear either a crash following Brexit or a burst following Bremain.

 

Figure 2

  • Source: gold prices (Bloomberg XAU BGN Crncy). Data up to Friday 17th June 2016.
  • Comments: the historical series shows an increasing trend, but no super-exponential behaviour and instabilities typical of bubble regime. In fact, the JLS model (LPPL fit) does not propose valid bubble and crash signals.
  • Interpretation: market participants are currently refuging into gold, but do actually fear neither a burst following Brexit nor a crash following Bremain. This result is consistent with the BBRXEQT and GBPUSD FX rate observations.

 

Figure 3

  • Source: GBP/USD FX rate (Bloomberg GBPUSD BGN Crncy). Data up to Friday 17th June 2016.
  • Comments: the historical series shows an erratic trend, no super-exponential behaviour and instabilities typical of bubble regime. In fact, the JLS model (LPPL fit) does not propose valid bubble and crash signals.
  • Interpretation: market participants but do not actually fear either a crash following Brexit or a burst following Bremain. This result is consistent with the BBRXEQT and GBPUSD FX rate observations.

 

Figure 4

  • Source: GBP/EUR FX rate (Bloomberg GBPEUR BGN Crncy). Data up to Friday 17th June 2016.
  • Comments: as for GBP/USD
  • Interpretation: as for GBP/USD.

 

Figure 5

  • Source: FTSE ORB Total Return GBP Index (Bloomberg TFTSEORB Index), includes GBP fixed coupon Corporate bonds trading on LSE across different industry sectors and maturity bands. Data up to Friday 17th June 2016.
  • Comments: the historical series shows an upward trend (due to the overall lowering discount rates, driven by lowering GBPLibor w.r.t. increasing GBP credit spreads) and super-exponential growth and instabilities typical of bubble regime. In fact, the JLS model (LPPL fit) propose several valid crash signals around 23th June.
  • Interpretation: market participants consider the referendum a risky event for corporate bonds, expecting either a Bremain scenario or the BoE intervention in case of Brexit.

 

Figure 6

  • Source: GBPLibor3M vs GBP OIS 3M (Bloomberg BP003M Index – BPSWSC Crncy). Measures the London interbank credit and liquidity risk on 3M time horizon relative to overnight horizon. Data up to Friday 17th June 2016.
  • Comments: the historical series shows super-exponential behaviour and instabilities typical of bubble regime. In fact, the JLS model (LPPL fit) does propose valid bubble and crash signals around 24th June.
  • Interpretation: market participants expect that the basis spread will crash back to lower values, corresponding to lower credit and liquidity risk in the London interbank market. This result is consistent with the FTSE ORB observations.

 

Figure 7

  • Source: Euribor3M vs EUR OIS 3M (Bloomberg EUR003M Index – EUSWEC Crncy). Measures the EUR interbank credit and liquidity risk on 3M time horizon relative to overnight horizon. Data up to Thursday 16th June 2016.
  • Comments: the historical series shows a decreasing trend but no super-exponential behaviour and instabilities typical of bubble regime. In fact, the JLS model (LPPL fit) does not propose valid bubble and crash signals.
  • Interpretation: market participants but do not actually fear either a crash following Brexit, also because the expected ECB intervention, or a burst following Bremain.

 

Figure 8

  • Source: UK house price index 8. Data up to April 2016 (this data is updated with delay).
  • Comments: the historical series shows an increasing trend with super-exponential behaviour and instabilities typical of bubble regime. In fact, the JLS model (LPPL fit) does propose valid bubble and crash signals around June.
  • Interpretation: the trend remembers those observed during the 2008 subprime crisis. Market participants expect a crash, but its relationship with the referendum is questionable, since the growth regime started before the current Brexit/Bremain context, and more recent UK HPI data would be needed to to establish a relationship.

 

Table 1: summary of JLS bubble signals (col. 4) from figures Figure 1Figure 8.

4.    Conclusions

We applied a forecasting methodology based on the Johansen-Ledoit-Sornette (JLS) model, developed since the 90s by D. Sornette at ETHZ and co-authors [1][2], and extensively applied to detect bubbles, crashes and crisis analysis in many fields [3]. Our implementation includes an enhanced model calibration using robust global optimization methods, i.e. Genetic Algorithms [4].

We applied the JLS model to a selection of historical financial series sensitive to the current Brexit/Bremain scenario, representative of equity (BBRXEQT), currency (Gold, GBPUSD and GBPEUR fx), rates and credit (FTSE ORB, GBP and EUR Libor – OIS basis), and real estate (UK HPI) asset classes.

We found the following evidence:

  • equity and currency asset classes show no bubble signals,
  • rates, credit and real estate show super-exponential behaviour and instabilities typical of bubble regime, with the exception of Euribor-EUR OIS basis.

Out study suggests that, under the JLS model, the following interpretations can be drawn:

  • equity and currency: market participants coherently do not expect crashes or bursts following the referendum results, thus supporting a Bremain scenario.
  • Rates and credit: market participants coherently consider the referendum a risky event for the London market, expecting either a Bremain scenario or a Brexit scenario edulcorated by central banks intervention.
  • In the case of real estate, market participants expect a crash, but its relationship with the referendum results is questionable.

 


* We stress that this paper was delivered on 21st June 2016, before the referendum scheduled for 23rd June 2016.


[1]      D. Sornette, “Dragon-kings, black swans and the prediction of crises”, Swiss Finance Institute Research Paper, no. 09-36, 2009.

[2]      A. Johansen, O. Ledoit, and D. Sornette, “Crashes as critical points”, International Journal of Theoretical and Applied Finance, vol. 3, no. 02, pp. 219-255, 2000.

[3]      ETHZ Financial Crisis Observatory

[4]      A. Salvatori, “Stochastic Models for Self-Organized Criticality in Financial Markets“, Msci Physics Thesis, Università degli Studi di Milano, Mar. 2016.

[5]      Opinion polls: see e.g. Wikipedia

[6]      Bookmakers betting odds: see e.g. Oddschecker

[7]      Bloomberg, Brexit watch indicators

[8]      UK house price index

 

6.    Disclaimer and acknowledgments

Disclaimer

The views and the opinions expressed in this document are those of the authors and do not represent the opinions of their employers. They are not responsible for any use that may be made of these contents.

The opinions, forecasts or estimates included in this document strictly refer to the document date, and there is no guarantee that future results or events will be consistent with the present observations and considerations.

This document is written for informative purposes only, it is not intended to influence any investment decisions or promote any product or service.

Acknowledgments
The authors gratefully acknowledge Luca Lopez for fruitful discussion and analysis at the early stage of this project.

Giu 212016
 

L’IVASS ha pubblicato il Documento di consultazione n. 11/2016 riguardante le proposte di modifica alla disciplina di bilancio delle imprese di assicurazione in recepimento della disciplina Solvency II. In particolare, il documento propone la modifica ai seguenti Regolamenti:

– Regolamento ISVAP n. 22 del 4 aprile 2008 concernente le disposizioni e gli schemi per la redazione del bilancio di esercizio e della relazione semestrale delle imprese di assicurazione e di riassicurazione;

– Regolamento ISVAP n. 7 del 13 luglio 2007 concernente gli schemi per il bilancio delle imprese di assicurazione e di riassicurazione che sono tenute all’adozione dei principi contabili internazionali.

La consultazione avrà termine il 31 agosto 2016.

Documento di consultazione IVASS n. 11/2016

Giu 212016
 

Il Comitato di Basilea per la vigilanza bancaria ha pubblicato le valutazioni sullo stato dei lavori di recepimento delle normative riguardanti le banche di rilevanza sistemica globale e domestica (rispettivamente G-SIB e D-SIB). In particolare, il Comitato ha esaminato l’attività svolta nelle 5 giurisdizioni di appartenenza delle istituzioni G-SIB: Cina, Unione Europea, Giappone, Svizzera e Stati Uniti.

Per quanto riguarda la normativa G-SIB, in generale il responso dell’analisi è stato positivo. L’implementazione del quadro normativo è ritenuta “compliant” (si tratta del più alto tra i 4 possibili livelli di valutazione) in tutte le giurisdizioni oggetto di studio.

Per la disciplina sulle D-SIB, le evidenze mostrano che gli impianti normativi istituiti dalle singole giurisdizioni sono in gran parte allineati ai principi dettati dal Comitato. Alcune differenze, però, sono state riscontrate nelle previsioni riguardanti i requisiti addizionali e le politiche da adottare nei confronti delle istituzioni D-SIB. Data la natura “principles-based” della disciplina D-SIB, non è stata attribuita alcuna valutazione in merito all’applicazione da parte delle giurisdizioni membri.

L’analisi rientra nelle attività svolte dal Comitato ai sensi del programma RCAP (Regulatory Consistency Assessment Programme), volto a valutare l’applicazione da parte delle giurisdizioni membri degli standard regolamentari approvati.

Comunicato stampa
Report Cina
Report Unione Europea
Report Giappone
Report Svizzera
Report Stati Uniti

Giu 212016
 

L’ESMA ha pubblicato un Parere in seguito alla proposta della Commissione Europea di modifica delle disposizioni tecniche (Implementing Technical Standards o ITS) in materia di comunicazione delle informazioni privilegiate (inside information) ai sensi della disciplina MAR (Market Abuse Regulation).

Gli ITS in questione specificano le metodologie tecniche per la diffusione delle informazioni privilegiate da parte degli emittenti di strumenti finanziari e dei partecipanti al mercato delle quote di emissione (EAMP). In particolare, le disposizioni richiedono che le informazioni siano esplicitamente identificate come privilegiate e attivamente diffuse tramite i mezzi di comunicazione.

La proposta di modifica della Commissione prevede di considerare sufficiente, per gli intermediari rientranti nel perimetro REMIT (Regulation on Energy Markets Integrity and Transparency), il rispetto degli obblighi di informativa previsti dalla normativa REMIF e di esentarli, dunque, dalle misure previste dagli ITS.

È opinione dell’ESMA, però, che tale previsione possa ridurre significativamente il livello di protezione degli investitori  fronte di una riduzione modesta dei costi sostenuti dagli emittenti.

Comunicato stampa
Parere ESMA

Giu 212016
 

L’IVASS ha pubblicato la relazione sull’attività svolta nell’anno 2015. Il documento è accompagnato dalle Considerazioni del Presidente dell’Istituto (e Direttore Generale della Banca d’Italia), Salvatore Rossi.

Grande attenzione, come prevedibile, è stata posta sull’analisi dell’attuale condizione di persistenza di tassi di interesse bassi (o negativi) e sull’attività di adeguamento alla disciplina Solvency II.

Per quanto riguarda il mercato assicurativo italiano, la domanda complessiva di polizze assicurative è aumentata lo scorso anno raggiungendo i 150 miliardi di euro (e segnando un +2.5% rispetto all’anno precedente). Di questi, oltre il 75% è attribuibile al comparto delle assicurazioni sulla vita. La redditività delle imprese assicurative è considerato soddisfacente e si attesta, per il quarto anno consecutivo, sui livelli – in termini di ROE – del 10% per il comparto vita e 7% per il comparto danni.

Relazione annuale IVASS
Considerazioni del Presidente IVASS

Giu 162016
 

On the 6th April 2016 EIOPA published a consultation document to seek for a feedback on the methodology to derive the Ultimate Forward Rate (UFR). The Authority intends to decide on the outcome of the review by September 2016.

Under Solvency II (SII) the insurance and reinsurance companies have to evaluate their assets and liabilities following some harmonized principles. Among those, there is the discounting of the liabilities cash flows through a risk free interest rates yield curve, which EIOPA has been publishing on a monthly basis since February 2015. These risk free yield curves are derived from financial instruments (interest rates swaps and, if not available, government bonds) traded in deep, liquid and transparent markets till the Last Liquid Point (LLP) and then extrapolated to longer maturities. The extrapolation is needed as the insurance liabilities may have durations of several decades, while the LLP are usually shorter – e.g. 20y for EUR. The extrapolation is performed such that the forward rates converge towards the UFR within the convergence period – e.g. 40y for EUR. This means that at the end of the convergence period – 20y+40y for EUR – the forward rates are equal to the UFR, but different from the published risk free interest rates, being those expressed as spot rates. The UFR has to be set appropriately to ensure the protection of policyholders: the liabilities calculated by the insurance companies have to be sufficiently high to cover their obligations.

The methodology to derive the UFR, which was initially described in a background document to the QUI5 study back in 2010, has to be aligned to the Delegated Regulation established in 2014: the derivation approach that will be applied on an ongoing basis has to be clarified, bearing in mind that the UFR should change with long-term expectations. The UFR currently in use is the one derived in 2010 – e.g. 4.20% for EUR – and starts to seem too high when compared to the market rates observable in the low interest rates environment of some economies. On one hand, it needs to be taken into account that the UFR is a long-term forward rate, but on the other hand it needs to be considered that a delay in the change of the UFR may result in more drastic impacts in case the long term expectation will move further away from the current UFR level.

What is clear is that any change in the UFR is expected to have a material impact for the insurance companies with significant long-term liabilities (beyond the LLP). To understand this better, it is worth recalling the results recorded in the 2014 stress test low yield module:

– the interest rate risk was material due to the common duration mismatches between asset and liabilities: the more positive the duration mismatch (liabilities > asset), the more vulnerable insurance companies are to negative interest rate shocks (and low yield curve in general)

– the average guaranteed rates on life insurance business (excluding unit-linked and index linked business), taking into account options and guarantees and surrenders, were between 2% and 4%, although being progressively decreased in the previous 5 year

– considering the application of LTG measures the percentage of the sample that did not meet the SCR requirements increased from 16% (base situation) up to 20/24% (low yield module).

The proposal made by EIOPA for the UFR methodology and its implementation is as follow:

– the UFR will be calculate every year, announced by the end of March and used to calculate the risk free yield curve three months later (the first UFR will be calculated by the end of March 2017 and applied to the risk free term structure for end-June 2017). A more frequent update would be not in line with the objective of stability and the three months period is intended to warn the insurance companies to prepare for the possible change

– the UFR cannot change by more than 20 bps (up or down) per year: a limitation is applied in case. As an example, given the current level of UFR=4.20% for EUR, if the long term expectation was, let’s say, 3.70%, in the next four years the UFR would be 4.00% in 2017, 3.80% in 2018 and 3.70% in 2019.

– the UFR before the limitation of the annual change is the sum of an expected real rate and an expected inflation rate; the former is the same for each currency, while the latter is currency specific. Making use of historical real rates and inflation targets, this approach have similarities with the methods used by both Moody’s Analytics (ex Barrie & Hibbert) and IAIS

– the expected real rate R is the weighted geometric average of the n annual real rates ri from 1960 to the year before the update of the UFR (wider window than the one currently adopted)

  • the annual real rates ri are derived as the simple arithmetic average of the annual real rates of Belgium, Germany, France, Italy, the Netherlands, the United Kingdom and the United States. The current approach, based on the average of 12 economies, was changed not to give too strong rates to certain economies (like Australia or Canada) that are not represented in the asset portfolios of European insurers
  • for each currency the annual real rate is calculated as  . The short term nominal rates are taken from the macroeconomic database of the European Commission (AMECO); the inflation rates are taken from the Main Economic Indicator database of the OECD. These two sources of data have been changed from the current approach to rely on databases provided freely and maintained transparently by public institutions
  • the expected real rates is rounded to full five bps (upward or downward) in the direction of the value registered the previous year (e.g. t-1=420; t=434 → 430; t=411 → 415)
  • differently from the current approach that relies on an arithmetic average, the proposed approach makes use of a geometrical weighted average with a fixed parameters of 0.99 to give less influence to oldest data
  • following the article 47 of the Delegated Regulation, EIOPA intends to exclude the term premium (and the convexity effect embedded in the term premium) that reflect the additional risk of holding long-term investments by using short-term interest rates from the AMECO database

– the expected inflation rate is based on the inflation target if announced by the central bank

  • 4 buckets are considered
    • target  < 1% → expected inflation=1%
    • target ∈ (1%, 3%] → expected inflation=2%
    • target ∈ (3%, 4%] → expected inflation=3%
    • target  > 4%→ expected inflation=4%
  • in case the central bank does not target a specific figure but indicates a corridor, the midpoint of the corridor is considered
  • in case the central bank does not announce a target, the expected inflation is set equal to 2%. The value can be change whether the long term expectation is at least 1% higher/lower than 2% (downward rounded to full percentage points). The past inflation is assessed against the average of 10y data and the projection derived on a basis of an ARMA model.

The impact of a change in the UFR on the present value of guaranteed benefits is not material for most life insurance portfolios, but can be significant for those with long-term guarantees

– considering cash flows data from 2014 stress test for only life insurance with profit participation and fixed guarantees and a decrease of the UFR from 4.20% to 3.50%

– the present value of fixed guarantees would increase by 0.79% and the eligible Own Funds would decrease by 6.7%

– for three quarters of the companies these figures would be +0.68% fixed guarantees and -5% Own Funds, but for few insurers they would be +2.4% and -50%.

To go deeper into these results one could look at

– the differences in the term structures, which differs significantly by currency

  • the impacts depends on the LLP and the speed of convergence. The highest impact can be observed for the Swedish krone (LPP=10y, convergence period=10y), the lowest impact for the pound sterling (LPP=50y, convergence period=40y)
  • the change of the extrapolated risk free interest rates depends approximately linearly on the change of the UFR. For example, for EUR T=30y the impact of increasing/decreasing the UFR by 10, 20 or 30 bps corresponds to an increase/decrease of 2.1, 4.2, 6.3 bps of the spot rates

– the impact on the present value of simple immediate/deferred annuity. The impact is usually small for immediate annuities as the large part of the cash flows correspond to maturities before the LLP, but can be relevant for deferred annuities being the payments deferred in the future. E.g. considering the Dutch life tables and a person aged 65, a decrease of 10bps in the UFR corresponds to an increase of the Technical Provisions up to 0.3% for an immediate annuity and up to 1.8% for a deferred annuity.

Giu 162016
 

L’EBA ha pubblicato la versione finale delle disposizioni tecniche (RTS) riguardanti le modalità di assegnazione delle ponderazioni per il rischio alle esposizioni derivanti da “specialised lending” (si tratta di esposizioni il cui rimborso dipende strettamente dalla performance dell’attività oggetto del finanziamento). Come specificato dal Regolamento (UE) n. 575/2013 (Regolamento CRR) è, infatti, competenza dell’EBA definire i fattori che le istituzioni finanziarie devono prendere in considerazione per la ponderazione per il rischio di questo tipo di esposizioni.

L’obiettivo delle nuove disposizioni è di armonizzare l’assegnazione dei pesi per il rischio tra le banche che applicano il cosiddetto approccio “supervisory slotting criteria”. Gli RTS definiscono 4 classi di specialised lending e per ognuna di esse introducono una serie di fattori che devono essere presi in considerazione nel processo di valutazione e attribuzione dei risk weights. L’approccio previsto dai nuovi RTS EBA è, inoltre, coerente con quello adottato attualmente dal Comitato di Basilea.

Comunicato stampa
RTS EBA

Giu 162016
 

L’IVASS ha pubblicato 3 nuovi Regolamenti in materia di regolamentazione del settore assicurativo:

– Regolamento IVASS n. 22 concernente la vigilanza sul gruppo e il recepimento delle linee guida EIOPA sulla metodologia della valutazione dell’equivalenza da parte delle autorità nazionali di vigilanza ai sensi della direttiva Solvency II;

– Regolamento n. IVASS 23 recante la disciplina della banca dati sinistri, della banca dati anagrafe testimoni e della banca dati anagrafe danneggiati;

– Regolamento n. IVASS 24 recante disposizioni in materia di investimenti e di Attivi a copertura delle riserve tecniche in recepimento delle linee guida sul sistema di governo societario, con particolare riferimento al principio della persona prudente in materia di investimenti.

Regolamento IVASS n. 22
Regolamento IVASS n. 23
Regolamento IVASS n. 24

Giu 162016
 

L’ESMA ha pubblicato una proposta di Standard Tecnici (RTS) ai sensi del Regolamento (EU) 2015/760, riguardante i fondi ELTIF (European Long-Term Investment Funds).

Tali fondi forniscono finanziamenti di lunga durata a progetti infrastrutturali di varia natura, a società non quotate ovvero a piccole e medie imprese (PMI) quotate che emettono strumenti rappresentativi di equity o strumenti di debito per i quali non esiste un acquirente facilmente identificabile. Finanziando tali progetti gli ELTIF concorrono al finanziamento dell’economia reale dell’Unione e all’attuazione delle sue politiche. Obiettivo della regolamentazione è stimolare gli investimenti europei a lungo termine nell’economia reale.

Le proposte principali dell’ESMA sono le seguenti:

– Definizione dei criteri per determinare le circostanze in cui i contratti derivati possano essere utilizzati solo per finalità di copertura;

– Determinazione della durata di un ELTIF in funzione dell’asset in portafoglio con il più lungo orizzonte di investimento;

– Definizione di una lista (non esaustiva) di rischi di mercato che i gestori di ELTIF dovrebbero prendere in considerazione per l’individuazione preventiva dei potenziali investitori;

– Definizione dei criteri per la valutazione degli asset degli ELTIF in caso di disinvestimento.

L’ESMA, inoltre, propone di fornire ai gestori degli ELTIF un anno di tempo, dall’entrata in vigore degli RTS, per l’adeguamento alle nuove disposizioni.

Giu 162016
 

La BCE ha pubblicato un documento con il quale definisce la procedura adottata per l’esame dell’ammissibilità degli strumenti di capitale quali elementi aggiuntivi di classe 1 (Additional Tier 1, AT1) ed elementi di classe 2 (Tier 2, T2). Precisa inoltre le informazioni che dovrebbero fornire i soggetti vigilati significativi (come definiti dal Regolamento (UE) n. 468/2014), che computano gli strumenti di capitale come capitale aggiuntivo di classe 1 e capitale di classe 2 su base individuale, subconsolidata e consolidata.

Indicazioni BCE ammissibilità AT1 e T2