IS LIBRA FOR LIBERTE?

If to ignore #Libra functionality, it offers the same as Central Banks - centralisation, surveillance, inflation (= proxy inflation of underlying basket of currencies). That's why CB's are worried so much. Last year they discussed, postponed and finally avoided the issuance of own sovereign digital money but were afraid to destroy banking industry.

Now, Libra will damage this strategy, because from user's perspective it will have the same properties. Yet, Libra will be global and will compete even with forex exchange. For example, cuban FB-user from Spain can send money to her mom in Cuba without the need to pay for currency exchange and high transaction fee. Still, the same can be done with #Bitcoin but transaction fee is much higher (use then #LightningNetwork !).

All in all, this creates a mess and will push CB's to get defensive. It will be very hard, taking into account that #crypto provides the average desire of money customers (we all are):

- to avoid intermediary risk taker

- to avoid inflation of monetary base

- to be in control of own deposit (digged under "crypto-tree" in the "crypto-garden")

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PS. Remember the old: "Liberte, Fraternite, Egalite". Missing FrereCoin and EgalCoin. 

Stress testing

Some thoughts aloud.:

Bank employ rich set of scenarios to test resilience of portfolio and to deliver various measures of risk. These models span from

• Type-I: scenarios with attached probabilities (weights), like it is used in Value-at-Risk (VaR) or Monte Carlo (MC) type of models or
• Type-II: stress test based models, where possible market states are scanned in wide range, portfolio performance is inter-/extrapolated and the worse case scenarios are used as risk measure.

hashtagHowever, thinking more about stress tests they should serve as a model independent addition to the usual probability hashtagmeasure *) based tools (type-I).

Another method is to reverse engineer the risk factors of portfolio in terms of weakest points (no likelihood/probability is attached), but that will serve the purpose to some extent, because this exercise will depend on the specific in-house (pricing) model. Some model independence can be achieved by building market-wide (AI?) model which can be used to detect pockets of instability (~singularity) which scenarios have to be injected into pricing of portfolio.

Discrepancy or consistency between measures used in pricing and risk modelling is similar topic, because if singularity becomes certain (realises) it changes/shifts all pricing (via price of risk, e.g. optionality or hashtagXVA type of modelling items).

Libor replacement - 2

Due to directions from FED, ECB, BoE etc there is a hype on #LiborReplacement which is due in 2021. Some argue that this will flow "by itself", similar to the change from national currencies to EURO in 1999-2002, some think that it will be "major disaster".

Indeed, many banking systems are relying on Libor. It starts from pricing and risk models which may use Libor as a core rate. Although such approach has changed since ~2007 when OIS rate was introduced as central rate for modelling, still there might be some entities who use Libor as a central quote.

Libor is often used as a reference rate, e.g. Libor+X%, to price commercial products towards corporate and retail (mortgage) markets. After 2021, all these contracts must be rolled. The change of Libor to the new rate perhaps will be done under zero-profit condition. That has to be calculated. Those who will do the calculations, remember, to account "in-arrears" settlement condition during transition period.

To add few words about causes of #Libor problem and possible solutions:

• Libor was quoted by few closely-related banks. It was tempting for them to manipulate the rate, so they did.
• One of the solutions to avoid manipulation is to invite a #thirdparty who will honestly and independently monitor the market and quote it. However, there are famous negative examples, when rating agencies were part of the deal too.
• Governments take the role into their hands and say that the publicly traded Short-rates will be the new Libor. This is regarded as not the most optimal solution and might turn to be the new handle for corruption or market manipulation when they tried to safe those who are "too big to fail".
• Another solution can be in hands of #CCP's. By definition, many banks today are obliged to process large portion of vanilla IR-contracts through CCP. Hence, these CCP are able to calculate the all-balancing rate out from the inherent cash flows. For the sake of stability of the market it would be useful to publish aggregated distributions of cash flows within financial system. By the way, CCP is also able to calculate implied contractual rates from these flows, hence it is possible to construct more reliable "new Libor" rate. That will embed an useful informational feedback. 
• Yet another possibility, is to build a distributed (blockchained) register for quotes which will be delivered by all participants. The open-source algorithm will calculate and publish the rate based on the information delivered by participants. The readonly-backdoor can be given to regulators for audit purposes. The design of such system can be elaborated further to ensure stability and avoid manipulations. 

Consolidated Basel-4 framework (part-2)

Also seen in https://www.innovaest.org/blog

Previous post was about:

• Border between Banking and Trading books, 
• Alignment (mostly data) problems and solutions of Credit risk measures used in these books
• Structural changes in Trading book capital measurement
• Alignment between EL (Banking book) and CVA (Trading book)

1. Changes in Banking book:
1. Change in Credit Risk measurement is driven by IFRS9 requirements about classification of portfolio items, measurements (Fair Valuation vs Amortization vs FVOCI (Fair Value Other Comprehensive Income))
2. Changes from TTC (Through The Cycle) to PIT (Point In Time), which is closer to the Risk Neutral measure used in Trading book). It helps to reduce delay in recognition of asset impairments
3. (Current) Expected (Credit) Loss (CECL) model with smoother and faster reaction to the state of counterpart. Compare to IAS39, where loss is expected and accounted in pre-default and default state. 
4. With regard to what has been discussed in the previous part, the questions are: 
1. Can we compare CECL and CVA directly? 
2. Hence can we compare PD(PTI) and PD(Risk Neutral)?
3. Also, can we compare LGDs? Trading book credit related items are mostly governed by ISDA, while Banking book is governed by local legislation and loan agreements with lender (be it mortgage or plain customer loan)
5. Remark: Changes in BigData industry led to openness of SME financial data, better predictability of economical data and also increased research about predictions of economic activities coming from satellite surveillance (by the way, this is interesting for separate discussion)
2. Balance sheet structural effects, related to ALM:
1. IRRBB - Net Income Interest (NII) risk
1. Main driver of confusion and problem here is the existence of different methods of accounting interest:
1. accrual as in contract method vs 
2. aligned with IR instruments, like swaps. 
2. This difference in methods is the main reason for the gap.
3. Consistent simulation of IR-scenarios across entire book can be a source for more optimal resource allocation.
2. Liquidity
1. HQLA requirement creates demand for government bonds, which are required to be supported with deposits. Liquidity Coverage Ratio (LCR) implicitly demands equalisation of HQLA with run-out Cash Flows within 1-month, where deposits are the most vulnerable in this regard. Net Stable Funding Ratio (NSFR) is closely related to this ratio
3. Structural FX risk 
1. This one comes from the necessity to protect capital adequacy ratio at the aggregated level (denominated in base currency) from changes of capital in branches (denominated in other currencies) due to movements in foreign exchange rates (see "Minimum capital requirements for market risk", jan2016, item 4, page 5). 
3. In summary, overall balance sheet optimization must be done within the following regulatory constraints:
1. Capital adequacy ratio
2. Leverage ratio
3. LCR and NSFR

Consolidated Basel-4 framework (Part-1)

Also seen in https://www.innovaest.org/blog

BIS has published their Consolidated B4 framework for Banks.

Summary of themes:

1. Introduce stronger border between Banking and Trading books.
2. Better alignment between Credit Risk measures withing Trading and Banking books:
1. Trading Credit Risk was measured over risk neutral measures (i.e. implied from traded instruments, such as CDS, Bonds etc.), while
2. Banking Credit Risk was simpler, but had more complicated structure. It was a blend of
1. Ratings coming from major rating agencies
2. Statistics from the sample of default events
3. Fundamental information coming from business (market size, accounts etc) of the counterpart
3. Main difficulty of implementation of such alignment lies in the search of equivalent measure between Risk Neutral and Fundamental/Structured Credit risks present in the Trading and Banking books. 
3. Trading book (Market and Trading Credit risks):
1. It fixes capital arbitrage problem as a main concern from regulators. In the past, it was possible to shuffle instruments between those books in order to optimize (reduce) capital requirement. FRTB (Market risk) sets two restrictions:
1. on product definitions, where they can be "hold till maturity" (banking book) or "available for trade" (trading book). 
2. it is not possible to change capital model for those items which changed the book
2. Capital for Trading book must be calculated with Standardized  Approach. It is done for the better and more homogeneous capital benchmark between banks.
3. Traded Credit risk formerly accounted in IRC (Incremental Risk Charge) now moves into DRC (Default Risk Charge).
1. IRC included both, credit spread (tradeable diffusion-type series) and default events (jump)
2. DRC moves capital from default event into banking book.
4. Cross-border (banking/trading) hedges are disallowed.
5. Replacement of VaR with Expected Shortfall seems to be not much of the problem.
6. NMRF (Non-Modellable Risk Factors) are very close to those mentioned as RNIV (Risk Not In VaR) by PRA (UK).
7. New regulation requires approval at desk level. 
8. Overall, the structure has changed:
1. Basel-2: Regulatory Market risk RWA was a blend of IMA and Standardized approaches. Regulators encouraged banks to develop Economic Capital to allow regulators to benchmark both numbers. 
2. Basel-3: Market risk RWA is calculated ultimately by SA, while IMA becomes the "new Economic Capital" and will be used for regulatory benchmarking.
4. Cost of Credit - Expected Loss and CVA (Credit Valuation Adjustment)
1. Within Basel-2 Expected Loss (EL) was provisioned within annual budget. Any Unexpected Loss was covered from Capital buffer. Trading Credit Risk (also Credit Counterparty Risk) accounted EL similarly.
2. After and during the crisis of 2007-2009, CVA became important as a measure aligned with other instruments in Trading Book. Resolution of problems related to hedging rules. 

Continued here

IBOR replacement

#IBOR #replacement by 2021-dec-31: 

• US: Secured Overnight Funding Rate (SOFR) 
• UK: Sterling Overnight Index Average (SONIA)  
• EU: Euro Short Term Rate (ESTER) 
• Switzerland: Swiss Average Rate Overnight (SARON) 
• Japan: Tokyo Overnight Average Rate (TONAR or TONA) . 

 Main care is about products with maturity > 2021-dec-31.
"Younger" products will mature naturally.
 
ISDA prepared report: Anonymized Narrative Summary of Responses to the ISDA Consultation on Term Fixings and Spread Adjustment Methodologies

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