ESMA renews prohibition on retail sales of binary options

News

Set 08 2018

The European Securities and Markets Authority (ESMA) has agreed to renew the prohibition of the marketing, distribution or sale of binary options to retail clients, in effect since 2 July, from 2 October 2018 for a further three-month period. ESMA has also agreed on the exclusion of a limited number of products from the scope of the measure.

ESMA has carefully considered the need to extend the intervention measure currently in effect. ESMA considers that a significant investor protection concern related to the offer of binary options to retail clients continues to exist. It has therefore agreed to renew the prohibition from 2 October.

During its review of the intervention measure, ESMA considered the specific features of binary options currently within the scope of the measures. Certain binary options were found to have specific features which mitigate the risk of investor detriment, namely; they are sufficiently long-term (at least 90 days); are accompanied by a prospectus; and are fully hedged by the provider or another entity within the same group as the provider. ESMA considers that a binary option that benefits from the cumulative effect of these three criteria is less likely to lead to a significant investor protection concern.

In addition, products that at the end of the term have one of two predetermined pay-outs, neither of which is less than the initial investment of the client, will be excluded. The pay-out for this type of binary option could be the higher or lower one but in either circumstances the investor would not lose money compared to their total investment. As the investor’s capital is not at risk these products should be explicitly excluded.

Hence, ESMA agreed to exclude from the scope of the renewal the following binary options:

  • a binary option for which the lower of the two predetermined fixed amounts is at least equal to the total payment made by a retail client for the binary option, including any commissions, transaction fees and other related costs; and
  • a binary option that meets cumulatively the following three (3) conditions:
    • (a) the term from issuance to maturity is at least ninety (90) calendar days;
    • (b) a prospectus drawn up and approved in accordance with the Prospectus Directive (2003/71/EC) is available to the public; and
    • (c) the binary option does not expose the provider to market risk throughout the term of the binary option and the provider or any of its group entities do not make a profit or loss from the binary option, other than previously disclosed commissions, transaction fees or other related charges.

ESMA will continue to keep these products under review during the prohibition period. The renewal was agreed by ESMA’s Board of Supervisors on 22 August 2018.

Incentives to centrally clear OTC derivatives: evaluating the G20 regulatory reforms

News

Set 08 2018

The Financial Stability Board (FSB), the Basel Committee on Banking Supervision (BCBS), the Committee on Payments and Market Infrastructures (CPMI) and the International Organization of Securities Commissions (IOSCO) examined the effects of G20 financial regulatory reforms on the incentives to centrally clear over-the-counter (OTC) derivatives.

The central clearing of standardised OTC derivatives is a pillar of the G20 Leaders’ commitments to reform OTC derivatives markets in response to the financial crisis. A number of post-crisis reforms are, directly or indirectly, relevant to incentives to centrally clear. A large majority of the relevant international standards have been agreed upon and are being implemented. This evaluation is the second using the FSB framework for the post-implementation evaluation of the effects of the G20 financial regulatory reforms.

The report concludes that the reforms – particularly capital requirements, clearing mandates and margin requirements for non-centrally cleared derivatives – are achieving their goals of promoting central clearing, especially for the most systemic market participants. This is consistent with the goal of reducing complexity and improving transparency and standardisation in the OTC derivatives markets. Beyond the systemic core of the derivatives network of CCPs, dealers/clearing service providers and larger, more active clients, the incentives are less strong.

The report identifies reform areas that may merit consideration by the relevant standard-setting bodies (SSBs). The findings from the report will inform relevant SSBs regarding any subsequent policy efforts and potential adjustments, bearing in mind the original objectives of the reforms. This does not imply a scaling back of those reforms or an undermining of members’ commitment to implement them.

 

Incentives to centrally clear over-the-counter (OTC) derivatives (PDF)

EBA publishes QIS templates to assess the impact of the finalised Basel III standards

News

Set 08 2018

The European Banking Authority (EBA) released today the two sets of templates, which will be used in the 2018 impact assessment of the finalised Basel III standards. These two sets of quantitative impact study (QIS) templates, which build on the Basel III regular monitoring templates, will ensure that the data collection burden is proportionate to the institutions’ size and complexity.

Following the European Commission’s Call for Advice on the European impact and implementation of the revisions to the Basel III standards agreed by the Basel Committee on Banking Supervision (BCBS) in December 2017, the EBA launched, on 13 August 2018, a data collection exercise, which runs in parallel with Q2-2018 EBA-BCBS Basel III regular monitoring exercise.

To ensure that this data collection, which covers a wider sample of institutions, remains proportionate to the size and complexity of each institution, the EBA distributed two different types of QIS templates, which build on and expand the EBA-BCBS Basel III regular monitoring templates.

In particular, the ‘full’ template was distributed to all banks participating in the Q2-2018 EBA-BCBS monitoring exercise and to those banks that only participate in the Call for Advice data collection that are large (as defined by Tier 1 capital higher than EUR 1.5 billion).

The ‘reduced’ template was distributed to banks participating only in the Call for Advice data collection that are medium or small (as defined by Tier 1 capital equal or lower than EUR 1.5 billion).The two sets of templates available for download are for information purposes only. Banks participating in the data collection should only use templates they received from their Competent Authority.

EBA QIS 2018 Template Instructions Data collection for the Call for advice for the implementation of the revision of Basel III framework (PDF)

Interest rates volatility in the insurance liabilities evaluation
di Silvia dell’Acqua

Articolo

Set 08 2018
Interest rates volatility in the insurance liabilities evaluation di Silvia dell’Acqua

Under Solvency II (SII), insurance and reinsurance companies have to evaluate their assets and liabilities following harmonized principles, among which the discounting of the liabilities cash flows through a risk free interest rates yield curve, that EIOPA has been publishing on a monthly basis since February 2015. The Authority does not state anything else regarding the future evolution of the risk free yield curve or the volatility it should show, which count a lot in the determination of the liabilities value.

If the liabilities were characterized by having no optionality, their present value could be easily calculated discounting the cash flows though the deterministic yield curve provided by EIOPA; in truth, insurance products usually offer a guarantee on a minimum level of return credited to policyholder fund. This optionality must be priced in a risk neutral framework, likely making use of Monte Carlo simulations. Whatever model is chosen to project the shape of the interest rates in the future, it must satisfy the risk neutrality principle (i.e. all the assets are expected to earn, on average, the risk-free rate). Roughly speaking, this means that, if we consider an asset that is worth X euros in t=0 and capitalize and discount it over the N paths of the projected interest rates, the average value of the N evaluations should be X. Although, Liabilities cash flows are not that simple and the volatility of the projected rates plays an important role when defining the value of the optionality they embed. The Interest Rate (IR) model adopted is calibrated such that the projected interest rates are Market Consistent (MC), that is, capable of replicating some Implied Volatilities (IVs) quoted in the market. The question is: which IV shall be targeted? It is worth noticing that we move from talking about the volatility of the interest rates, used to price the optionality (and therefore the IV) of the liabilities to a different IV, that comes from the market, from completely different types of options. When thinking about the market, another important piece of information is that the price of an instrument is unique, while its IV depends on certain assumptions: it is implied by a specific formula. Another key element is that prices are the unique quantity definable via Monte Carlo simulation, while IV shall be derived from the former.

The SII regulation does not provide any answer and the choice is left to the insurance and reinsurance undertakings, which can select the IR model they prefer and its market target for the calibration purposes. Actually, the Standard Formula does not even consider the IR volatility as a risk.

The IVs quoted in the market are those of the Cap, Floor and Swaption contracts, all the three being defined over an Interest Rate Swap (IRS).The IRS is a derivative instrument where two parties agree to exchange IR cash flows from a fixed () to a floating () rate, or vice versa. The IRS is called payer/receiver when the fixed rate is paid/received. The fixed rate that makes the contract fair is called forward swap rate and is equal to:

where is the time when the contract starts and the number of years it lasts.

Caps and Floors can be respectively seen as options on a payer/receiver IRS, where the money exchange is set in favorable circumstances only. The present value of the payoff of a Cap is:

Caps can be used for hedging purposes when one is debtor of the floating rate . Indeed, when holding such a contract, the whole exposition becomes , that does not exceed the fixed rate . Caps and Floors are made up of sequences of Caplets and Floorlets, each one defined over a certain époque and referred to a certain forward rate. A Cap contract is said to be ITM (In), ATM (At) or OTM (Out of The Money) when K is respectively <, = or > than the fair value, and the difference between K and the fair value is called moneyness, so

A payer/receiver Swaption contract is an option granting its owner the right but not the obligation to enter in into an underlying payer/receiver IRS of tenor . The actual value of a payer Swaption is:

Because of the Jensen inequality, this value is never grater that the Cap correspondent one. Likewise the Cap, a payer Swaption is said to be ITM, ATM or OTM when the strike K is respectively <, = or > than .

Until the recent past (say, before the negative rates appeared), both Caps/Floors (considered as sum of Caplets and Floorlets) and Swaptions were priced using the Black formula, supposing a lognormal distribution respectively for the forward rates and the forward swap rate. Although widely used in the market, the two pricings were incoherent, being the forward swap rate defined as a weighted average of the forward rates and the being the sum of aleatory variables with lognormal distribution not lognormal distributed (i.e. the two assumptions on the distributions of the rates cannot hold true together). As the price of a Swaption depends on the forward swap rate, knowing the volatilities of the single forward rates is no longer sufficient for the evaluation and information about the forward rates joint distribution and the correlation between different maturities are needed. Because their price embeds more information, Swaption contracts are often preferred to Caps when setting the market target for the calibration of the IR models.

Given a unique price of a Swaption, there are three types of IV quoted in the market, based on different assumptions on the distribution (Lognormal, Displaced Lognormal or Normal) of the swap forward rate:

  • LN-SIV are defined as a relative change of the forward swap rate (bigger changes for higher YC)

  • DLN-SIV are defined as a relative change of the displaced forward swap rate

  • N-SIV are defined as an absolute change of the forward swap rate, independent of its level

All the three are linked by the value of the underlying forward swap rate and, roughly speaking, there are 2 order of magnitudes between the former and the latter. Even though the relationship is not given by a simple rescaling and it is not linear, a good approximation to keep in mind is:

The recent past market environment, characterized by a number of tenors whose rate was negative, has questioned the use of LN-IV: negative/close to zero forward swap rates turn into not defined/extreme IV, which make the calibration of any IR model very challenging and potentially inaccurate.

N-IV has started to catch on, with the additional benefit of mitigating the distortion that comes from applying a market IV to a Yield Curve (YC) that is different from the market one. Indeed, the IV quoted in the market refer to the market swap YC, while the IR models used for the liabilities evaluation are based on the published EIOPA YC (much higher on the long term due to the convergence to the UFR). The misalignment of applying a certain IV (that refers to the market YC) to a higher YC (the EIOPA one) is exacerbated when LN-IV are adopted, as they are proportional to the level of the rates. The usage of N-IV in place of LN ones helps in taming the volatility embedded in the projected rates, that affects the TVOG, normally increasing the BEL value. The following picture clarifies the statement, by comparing the market ATM LN Swption IV (implicit in the market rates) to those derived from the N-IV when the EIOPA YC is used: the latter are smaller because, given the same N-IV, a higher rate appears as denominator.

After having concluded that Swaptions are more exhaustive than Caps and, in this context, N-IV are more appropriate than LN-IV, a question is left: when calibrating an IR model, which data shall be considered as target among all those available for the Swaption N-IV (N-SIV) cube (option maturity , IRS tenor , moneyness) at a certain reference date?

Let’s try not to forget the original goal: determining a value for the Liabilities, that embed a degree of optionality, priced via Monte Carlo methods. The market data chosen as target drive the calibration of the IR model chosen and, in turn, the projected rates and their distribution. Different sets of projected rates give origin to different liability values. Setting a certain target is nothing else than deciding on the properties the projected rates should have, including their volatility, keeping in mind that the IV of the liabilities will not be equal to the IV of the Swaptions as the liabilities are not Swaption contracts.

Being the N-SIV quite smoothed, there is potentially no contraindication in setting the whole SIV cube as target but the runtime needed to carry out the IR model calibration: it is a matter of balance between calibration speed and fitting accuracy, which also depends on the IR model adopted. Deciding on which data to consider introduces a degree of subjectivity and exposes one to the risk/benefit of choosing some points rather than others. What if the others matters more? On the other hand, along with reducing the runtime, the selection of a subset of data may help in discarding unrepresentative or inaccurate data points, not consistent with the surrounding ones.

Once the relevant data have been chosen, the last question is: shall they all be weighted the same way or should some of them count more than others? The easiest possibility is to assign uniform weights to all the points considered, while a more subjective one is to decide on which SIV triples should count more. There is no contraindication of going for the first choice, while the latter introduces again a degree of subjectivity. A possibility for defining a not uniform weighting scheme would be to derive it from the liabilities’ profile, but it would be a more complex approach, less stable over time and subject to introducing sensitivity between rates levels and volatilities (the liability profile depends on the level of the rates and so the derived weights, which will drive the next calibration, like the tail wagging the dog). In addition to that, one should remember that there is no direct link between liabilities and Swaption contracts: the IV quoted in the marked for the Swaptions are not becoming IVs for the liabilities.

Having said that, in case liability driven weights was still the favorite option, an insurance company should define a parallelism between the financial optionality and that embedded in insurance products to derive the option maturities, IRS tenors and moneyness it is more exposed to. To this aim, only contracts with of a minimum guaranteed rate shall be considered. A “with profit” contract, where the policyholder has the right to get a minimum guaranteed rate in case of lapse/death/maturity, could be compared to a Long European Swaption as the policyholder may chose a fixed payout at the end of his contract or a variable benefit if he takes the money and invests it at the risk-free rate; from the perspective of the insurance company, this contract would be comparable to is a Short European Receiver Swaption. One can think of:

  • the option maturity (T) as the time in which the policyholder can decide to leave the contract
  • IRS tenor (n) as the residual time since the policyholder has left the contract till its original maturity
  • the moneyness of the option (r_mg) as the difference between the minimum guaranteed rate (moneyness) and the swap forward rate S(T,T+n). In a market environment characterized by low yields and high guarantees, the liabilities would be more exposed to OTM Swaptions on the short term (a rational policyholder would prefer to stay in the contract and get the minimum guaranteed rate rather than reinvest the benefit in the market at the risk-free rate, which is lower) and to ITM Swaptions on the long term (when the market rates are higher than the guaranteed one).

To put into effect this parallelism between insurance policies and financial contracts, one needs derive a 3D matrix (T,T+n,moneyness) starting from a 1D projection of mathematical reserves and outgo cash flows for the maturity only CF(t,MAT.OUT). The mathematical reserves are used as the best proxy of the amount of money the policyholder will get in case of lapse (exercise of the option), while maturity outgoes are considered being the only outgo cash flows where the policyholder can exercise an option (neither death cash flows are considered as the policyholder cannot decide to die/survive, nor annuity cash flows are, because, when paid, they correspond to a decision already made by the policyholder – staying in the contract and not leaving getting a lump sum).

  • both V(t) and CF(t,MAT.OUT) can be split by r_mg, from which one can derive the moneyness (that gives the 3rd dimension)

  • given a certain r_mg, to transform the 1D projection into a 2D matrix one has to “recycle” the data “moving in time”
  • the first dimension (T) is naturally given by the “move in time”
  • the exposure of the Liabilities to the IRIV risk is given by the amount of mathematical reserves that the policyholders can withdraw at that time (T), given the lapse rate as the base one

  • at each (T), the second dimension (T+n) is given by the amount of contract in place at time e that are expiring in (T+n) – one moves in time considering for each row (i+1) a subset of the data used in (i), removing the first element

As the SIV cube does not include all the possible triples, the data without a correspondence have to be assigned to the nearest existing labels (e.g. tenor 6 is split equivalently to tenor 5 and tenor 7), in a “condensation” process. Even though it is be possible to identify the whole cube, the entries may be further condensed into a limited number of triples, which have been defined as target.

As already stated, the parallelism between financial and insurance options is just a parallelism that undergoes a number of simplifications, among which:

  • ignoring additional payments on top of the minimum guaranteed amounts (that happen because of the profit sharing) as well as fiscal benefits or penalties in case of early surrender
  • the surrender date is not set at maturity only: policyholders can surrender at any time until maturity (it would be more similar to a Bermudan option rather than to a European Swaption)
    • it is not exactly clear whether an insurance contract shall be addressed as payer or receiver option: looking at the payoff, the payer label would fit more (max(0,L-K) ), but from a definition perspective the policyholder actually receives from the insurance company a fixed amount, that than exchanges with a third party (the market).

 

Il termometro dei mercati finanziari (7 settembre 2018)
a cura di Emilio Barucci e Daniele Marazzina

Termometro

Set 08 2018
Il termometro dei mercati finanziari (7 settembre 2018) a cura di Emilio Barucci e Daniele Marazzina

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.

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.

Basel Committee: technical amendment on Pillar 3 disclosure requirements

News

Set 01 2018

The Basel Committee today released a technical amendment on additional Pillar 3 disclosure requirements for those jurisdictions implementing an expected credit loss (ECL) accounting model as well as for those adopting transitional arrangements for the regulatory treatment of accounting provisions.

Technical amendments are defined as changes in standards that are not substantial in nature but that cannot be unambiguously resolved based on the current text. This specific amendment is intended to provide users with disclosures that fully reflect any transitional effects for the impact of ECL accounting on regulatory capital, as well as to provide further information on the allocation of accounting provisions in the regulatory categories of general and specific provisions for standardised exposures during the interim period.

The consolidated Pillar 3 disclosure standard issued in March 2017 introduced two new disclosure templates (Templates KM1 and KM2) to provide users of Pillar 3 data with a set of key prudential metrics in a format that facilitates comparisons of a bank’s performance and trends over time, improving market discipline in the process. Template KM1 will provide users of Pillar 3 data with a time series set of key prudential metrics covering a bank’s available capital (including buffer requirements and ratios), its risk- weighted assets (RWA), leverage ratio, Liquidity Coverage Ratio and Net Stable Funding Ratio. Template KM2 requires G-SIBs to disclose key metrics on Total Loss-Absorbing Capacity (TLAC). Both templates must be published quarterly.2

As set out in the Committee’s publication on the regulatory treatment of accounting provisions, the standard requires banks to publicly disclose whether they are applying a transitional arrangement for the impact of expected credit loss accounting on regulatory capital. If a transitional arrangement is applied, Template KM1 will provide users with information on the impact on the bank’s regulatory capital and leverage ratios compared to the bank’s “fully loaded” capital and leverage ratios had the transitional arrangement not been applied.

In order to provide users with disclosures that fully reflect any transitional effects for the impact expected credit loss accounting on regulatory capital, as well as to provide further information on the allocation of ECL accounting provisions in the regulatory categories of general and specific provisions for standardised exposures during the interim period, the following disclosures in the Pillar 3 standard will apply:

  • Template KM2 (Key metrics – Total Loss-Absorbing Capacity (TLAC) requirements at resolution group level). Additional disclosures require banks to disclose the “fully loaded” impact of ECL transitional arrangements used in TLAC resources and ratios.
  • Template CR1 (Credit quality of assets). Given that the existing regulatory distinction between general provisions (GP) and special provisions (SP) does not directly correspond to how provisions would be measured under the new ECL accounting standards, additional disclosures are required on the allocation between general and specific provisions for standardised approach exposures.
  •  Table CRB (Additional disclosures related to credit quality of assets). This amendment accompanies those related to CR1. Banks are required to disclose the rationale for their categorisation of ECL accounting provisions in general and specific categories for standardised approach exposures.

Pillar 3 disclosure requirements – regulatory treatment of accounting provisions (PDF)

Financial, economic and monetary developments in the Eurozone

News

Set 01 2018

The Governing Council of the European Central Bank, held in Frankfurt am Main on the 25-26 July 2018, reviewed the latest financial, economic and monetary developments since the Governing Council’s previous monetary policy meeting on 13-14 June 2018.

Financial market developments

The slope of the US Treasury and German government bond yield curves, measured as the difference between the ten-year and two-year yields, had continued their flattening trend of recent months. In particular, between April and July 2018 estimates of the term premium in the United States had fallen deeper into negative territory despite factors which should have led, in principle, to a decompression of the premium, such as the gradual balance sheet wind-down by the Federal Reserve System and expectations of an increase in the supply of US Treasury securities based on a projected rise in the US fiscal deficit.

The most recent decline in term premia, both in the United States and in the euro area, might partly be attributed to the growing uncertainty over the global economic outlook owing, among other factors, to escalating trade disputes. This may have affected confidence among investors and contributed to an increase in demand for US Treasuries and German government bonds, widening the negative term premia that also reflected the stock effect of large-scale asset purchases.

Moreover, following the June Governing Council meeting, market participants’ expectations of a first rate increase by the ECB had been pushed further into the future, as suggested by market pricing and the latest analyst surveys. This partly reflected the Governing Council’s enhanced forward guidance on the future path of policy rates, which had also contributed to reducing interest rate uncertainty.

In foreign exchange markets, the euro had traded in a very narrow range against the US dollar. However, in nominal effective terms, the euro had appreciated, in particular against the currencies of a number of developing and emerging market economies. Part of the depreciation of these economies’ currencies was likely related to the growing uncertainty over the impact of trade tensions.

Trade tensions were also seen by market participants to have had a negative impact on stock market valuations, most notably in China. Since its peak in late January 2018, the China Securities Index 300 had declined by nearly 20%, while other stock market indices in the region had also fallen but to a lesser extent. These equity market sell-offs no longer affected only sectors that would be most hit by tariffs. Rather, they had become more broad-based, possibly reflecting increasing concerns among investors over the impact of protectionist measures on the global growth outlook.

Credit spreads in emerging market economies had increased measurably, by around 80 basis points, since the start of 2018. However, they remained well below the levels observed in 2015 and early 2016.

The global environment and economic and monetary developments in the euro area

Regarding the external environment, the global economic expansion had continued, while trade had weakened further. At the same time, inflation dynamics had gained some momentum. Annual consumer price inflation in the OECD area had edged up to 2.6% in May, with inflation excluding food and energy also increasing marginally. Brent crude oil prices had decreased by 2.2% (in US dollar terms) since the June monetary policy meeting. Over the same period, non-oil commodity prices had decreased by 7.4%, food prices by 6.7% and metal prices by 9.7% (all in US dollar terms).

Looking at the euro area, the incoming data confirmed that the moderation in the first quarter of 2018 had reflected a pull-back from the very high growth levels of previous quarters, mostly on account of weaker export demand with some contribution from temporary and supply-side factors. The breakdown of first-quarter growth into its components showed that domestic demand and changes in inventories had contributed positively to the outturn, whereas the contribution of net exports had been negative.

High frequency indicators released since the June meeting had confirmed the ongoing broad-based expansion. The flash composite output Purchasing Managers’ Index for July had decreased only slightly to 54.3, from 54.9 in June. Moreover, consumer confidence and confidence in the construction sector had remained at elevated levels, well above their historical averages. Favourable financing conditions, a robust labour market, and steady income and profit growth had continued to support private consumption and investment.

The June 2018 Eurosystem staff projections for euro area real GDP growth were broadly aligned with, or slightly below, available forecasts from other international institutions.

Turning to price developments, according to Eurostat’s flash estimate, euro area annual HICP inflation had stood at 2.0% in June, up from 1.9% in May. The increase reflected higher inflation rates for the energy and food components, which had more than offset a decline in HICP inflation excluding energy and food. Meanwhile, measures of underlying inflation remained muted overall but had been increasing from earlier lows.

Annual growth in compensation per employee had increased to 2.0% in the first quarter of 2018, up from 1.8% in the fourth quarter of 2017. In the first quarter of 2018, the impetus for this upward trend had come from stronger negotiated wage growth, rather than wage drift, as had previously been the case. This shift to negotiated wage growth as the main driver bolstered confidence that the pick-up in wage growth would be sustained.

Both market and survey-based inflation expectations were largely unchanged since the June meeting. Compared with other forecasts, the June Eurosystem staff projections for euro area HICP inflation were at the upper end of the range for 2018 and in the middle of the range for 2019 and 2020.

Financial conditions had remained broadly stable, in spite of some exchange rate appreciation in nominal effective terms and lower equity markets. The Governing Council’s June decisions had reduced interest rate uncertainty. In the weeks following the June meeting, EONIA forward rates had continued to decline, accompanied by a further flattening of the forward curve. Meanwhile, mounting global trade tensions weighed on euro area equity markets, while there were only modest changes in sovereign and corporate debt markets. The overall cost of financing for euro area firms had remained very favourable.

Turning to money and credit developments, the annual growth rate of the broad monetary aggregate M3 had risen to 4.4% in June from 4.0% in May. From a counterpart perspective, domestic sources of money creation had remained the main driver of M3 growth. The annual growth rate of loans to the private sector had continued its recovery, increasing to 3.5% in June, up from 3.3% in May. This acceleration had been mainly driven by loans to non-financial corporations (NFCs), which had stood at 4.1% in June.

At the euro area level, the composite cost of borrowing for NFCs had fallen to a new historical low in May, while the borrowing costs of loans for house purchase had remained stable at 1.8%. Moreover, according to the July 2018 euro area bank lending survey, credit standards had continued to ease for NFCs and households in the second quarter of 2018. The main factors contributing to the net easing had been competition and risk perceptions reflecting solid economic growth in the euro area.

Finally, with regard to fiscal policy, the euro area fiscal stance, measured as the change in the cyclically adjusted primary balance, was projected to stay mildly expansionary in 2018.

Monetary policy considerations and policy options

The most recent economic indicators and survey results had stabilised and confirmed the scenario of solid and broad-based growth momentum in line with the June Eurosystem staff projections.

Risks to the growth outlook could still be assessed as broadly balanced. Uncertainties related to global factors remained prominent. In addition, the risk of persistent heightened financial market volatility continued to warrant monitoring.

The strength of the euro area economy supported confidence that the convergence of inflation to levels below, but close to, 2% over the medium term would continue in the period ahead. This confidence was further bolstered by rising wages and increasing price pressures at the early stages of the pricing chain.

At the same time, underlying price pressures were building up only gradually, which argued in favour of patience, prudence and persistence with regard to the conduct of monetary policy in the period ahead.

On the basis of this assessment, Mr Praet proposed keeping monetary policy unchanged and reconfirming all elements of the Governing Council’s forward guidance.

It was important for communication to emphasise that the incoming data confirmed that the euro area economy was proceeding along a solid and broad-based growth path and underlined that risks surrounding the euro area growth outlook could still be assessed as broadly balanced, but uncertainties related to global factors remained prominent.

It was furthermore important to highlight that the underlying strength of the euro area economy continued to provide confidence that the convergence of inflation to levels below, but close to, 2% over the medium term would proceed in the period ahead, as well as to stress that a significant monetary policy stimulus remained necessary for the sustained convergence of inflation.

Likewise important was for the Governing Council to reiterate that an ample degree of monetary accommodation would continue to be provided by the net asset purchases until the end of 2018, by the sizeable stock of acquired assets and the associated reinvestments, and by the enhanced forward guidance.

Il termometro dei mercati finanziari (31 agosto 2018)
a cura di Emilio Barucci e Daniele Marazzina

Termometro

Set 01 2018
Il termometro dei mercati finanziari (31 agosto 2018) a cura di Emilio Barucci e Daniele Marazzina

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.

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.

FSB: Analysis of Central Clearing Interdependencies

News

Ago 31 2018

The Financial Stability Board (FSB) issued a joint report with the Committee on Payments and Market Infrastructures, the International Organization of Securities Commissions and the Basel Committee on Banking Supervision exploring interdependencies between central counterparties (CCPs) and clearing members and other financial service providers.

The report would eventually serve as a proxy to mitigate possible systemic risk arising from the increasing weight of central counterparties in global markets. The international standard-setters published a first report on central clearing interdependencies in July 2017.

To assess whether the findings of the July 2017 report were stable over time, the international standard-setters conducted another more streamlined data collection (as of October 2017) from the same 26 CCPs. The results are broadly consistent with the previous analysis with the data as of September 2016 and can be summarized as follows:

  • Prefunded financial resources are concentrated at a small number of CCPs.
  • Exposures to CCPs are concentrated among a small number of entities.
  • The relationships mapped are characterised, to varying degrees, by a core of highly connected CCPs and entities and a periphery of less highly connected CCPs and entities.
  • A small number of entities tend to dominate the provision of each of the critical services required by CCPs.
  • Clearing members and clearing member affiliates are also important providers of other critical services required by CCPs and can maintain several types of relationships with multiple CCPs simultaneously.

There are, however, some changes to highlight in the interdependencies in central clearing. For instance, the concentration of client clearing activity has decreased. Compared with the last report, initial margins from clients are now concentrated in two CCPs, compared to only one with the data as of September 2016.

The analysis of interdependencies in central clearing is intended to provide useful inputs for designing supervisory stress tests and has informed the policy work as set out in the joint workplan to promote CCP resilience, recovery and resolvability. The standard-setters published a report on the implementation of the workplan in July 2017.

 

Analysis of Central Clearing Interdependencies (PDF)

Banca d’Italia: identificazione dei paesi terzi rilevanti per il CCB

News

Ago 30 2018

Nel dicembre 2015 lo European Systemic Risk Board (ESRB) ha emanato una raccomandazione per favorire l’uniformità delle decisioni dei singoli Stati membri relative al coefficiente della riserva di capitale anticiclica (CCB) da applicare alle esposizioni verso residenti in paesi che non fanno parte dell’Unione europea (paesi terzi).

La raccomandazione prevede che le autorità nazionali designate identifichino annualmente i paesi terzi verso cui i sistemi bancari nazionali hanno esposizioni rilevanti e adottino misure per il controllo dei rischi per la stabilità del proprio sistema derivanti da una crescita eccessiva del credito in tali paesi. La Banca d’Italia, sulla base dei dati disponibili al 31 dicembre 2017, ha identificato come rilevanti per il sistema bancario italiano i seguenti paesi terzi: Russia, Stati Uniti, Svizzera e Turchia.

Poiché questi paesi sono stati identificati anche dall’ESRB come rilevanti per l’intera Unione europea e sono quindi sottoposti a sorveglianza da parte dell’ESRB medesimo, la Banca d’Italia ha deciso di non svolgere attività di sorveglianza diretta dei rischi dei quattro paesi.

L’identificazione dei quattro paesi è stata effettuata seguendo i criteri utilizzati dall’ESRB per individuare i paesi terzi rilevanti per l’Unione europea. La valutazione ha riguardato tutti i paesi verso cui le banche italiane hanno esposizioni e ha preso in considerazione tre indicatori riferiti rispettivamente:

  1. alla quota delle esposizioni originarie (ad es. le esposizioni non ponderate per il rischio);
  2. alla quota delle esposizioni ponderate per il rischio;
  3. alla quota delle esposizioni in default verso ciascun paese terzo sul totale complessivo delle corrispondenti esposizioni del sistema bancario italiano.

Sono stati identificati come rilevanti quei paesi per i quali almeno uno dei tre indicatori era pari o superiore all’1 per cento in ciascuno degli ultimi due trimestri e nella media degli ultimi otto.