Bank Recapitalization. Some Scattered Thoughts on Efficacies.

If we are still thinking of Demonetization and GST as speed breakers to economy, which entirely isn’t false, the what could one say of Bank Recapitalization? Is this a master stroke of sorts to salvaging sensibility before the present ruling dispensation of BJP is red-faced before 2019 GE? Or, is Bank Recapitalization is all about safeguarding the dismal dip in the growth and especially so when the world economy is on an ascent, despite warnings of a Minsky Moment? What are the challenges to Bank Recapitalization and how would these face up to the challenges of the NPAs and PSB consolidation? These are pressing questions that simply cannot be answered by a political will getting catalyzed, but requires a deeper economic drift and traction.

So, if Bank Recapitalization to the tune of Rs. 2.1 lakh crore infusion into the public sector banks were to come through, and which it would, the budgetary allocations are a mere chunk, while raising money from the market too isn’t that major a factor. The roost is to be ruled by recapitalization bonds, or recap bonds, in short. What then are the challenges of this methodology?

Technically, in the current context, there is really not much of a risk in issuing recapitalization bonds. The outside risk of recapitalization bonds is that this move may tighten liquidity in the system if all the surplus liquidity in the banking system goes into its capital. However, since recapitalization bonds are callable in nature, this risk should not be too great. Also, the debt markets are now sufficiently deep and broad and can support the funding needs of the India corporates and hence that is unlikely to be a major issue. The only concern is that rating agencies globally will look at recapitalization as a form of off-balance sheet financing, which does not give them too much comfort. Many rating agencies look at such bonds as a means of raising debt that is not visible in the fiscal deficit. This lack of visibility is what might be the hurdles race for the government. But, then is there a way out?

Alternatively, what if the government were not to recapitalize? Then, it can look to postponing its adherence to Basel III from 2019. But that will be seen by global markets as an admission by the Government of India that it does not have the liquidity to capitalize its banks. That may not go down well with foreign investors. Under these circumstances, infusing capital into the banks through the issue of recapitalization bonds may be the best option available!

What are the main economic ramifications as a result of these? The government’s plan at recapitalization would have little impact on its target to shrink the shortfall to 3.2 percent of the GDP because the IMF rules classify such debt as “below the line” financing. Only interest expenses would be added to the fiscal deficit, and this is estimated at about Rs. 90 billion or 0.4 percent of the total budgeted spending. Technically, however, India’s accounting rules require the bonds to be included in the budget deficit, so the government would reclassify them later as off-balance sheet items. The government is yet to disclose the details on the structure and pricing of the bonds, as well as how it would raise the rest of the cash. These will determine if there is a liquidity squeeze. If the measures do revive credit growth, inflation may accelerate as well, limiting scope to lower the policy rate. When it comes to the question of who would buy these bonds, the answer is probably banks themselves, who are flush with deposits following the note ban. Banks can then cleverly invest these funds in the recap bonds which will then be ultimately routed back as equity in the system. This would ensure that the bond market would not be impacted by such a large issuance for the private sector issuers.

Now, these are serious questions questioning some of the advocacy groups have to come to terms with. For one thing, in my opinion, mergers and acquisitions to consolidate PSBs are to be put back on the back foot, for recapitalization has at least punctuated to for the time being. Second is credit growth, or more precisely credit demand, which would be induced with an energy following this exercise. Third, and most importantly, the lending might gain velocity, but only after April 2018, since banks would require a correctional facility on their balance sheets. This lending would somehow be channeled towards infrastructure giants like Sagarmala and Bharatmala with a key difference being that the Government might prioritize Engineering, Procurement and Construction (EPC) over Hybrid Annuity Model like the PPP for the obvious risks associated with the latter subsequently feeding into the NPAs and/or stressed assets. 

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Haircuts and Collaterals.

In a repo-style securities financing transaction, the repo buyer or lender is exposed to the borrower’s default risk for the whole duration with a market contingent exposure, framed on a short window for default settlement. A margin period of risk (MPR) is a time period starting from the last date when margin is met to the date when the defaulting counterparty is closed out with completion of collateral asset disposal. MPR could cover a number of events or processes, including collateral valuation, margin calculation, margin call, valuation dispute and resolution, default notification and default grace period, and finally time to sell collateral to recover the lent principal and accrued interest. If the sales proceeds are not sufficient, the deficiency could be made a claim to the borrower’s estate, unless the repo is non-recourse. The lender’s exposure in a repo during the MPR is simply principal plus accrued and unpaid interest. Since the accrued and unpaid interest is usually margined at cash, repo exposure in the MPR is flat.

A flat exposure could apply to OTC derivatives as well. For an OTC netting, the mark-to-market of the derivatives could fluctuate as its underlying prices move. The derivatives exposure is formally set on the early termination date which could be days behind the point of default. The surviving counterparty, however, could have delta hedged against market factors following the default so that the derivative exposure remains a more manageable gamma exposure. For developing a collateral haircut model, what is generally assumed is a constant exposure during the MPR.

The primary driver of haircuts is asset volatility. Market liquidity risk is another significant one, as liquidation of the collateral assets might negatively impact the market, if the collateral portfolio is illiquid, large, or concentrated in certain asset sectors or classes. Market prices could be depressed, bid/ask spreads could widen, and some assets might have to be sold at a steep discount. This is particularly pronounced with private securitization and lower grade corporates, which trade infrequently and often rely on valuation services rather than actual market quotations. A haircut model therefore needs to capture liquidity risk, in addition to asset volatility.

In an idealized setting, we therefore consider a counterparty (or borrower) C’s default time at t, when the margin is last met, an MPR of u during which there is no margin posting, and the collateral assets are sold at time t+u instantaneously on the market, with a possible liquidation discount g.

Let us denote the collateral market value as B(t), exposure to the defaulting counterparty C as E(t). At time t, one share of the asset is margined properly, i.e., E(t) = (1-h)B(t), where h is a constant haircut, 1 >h ≥0. The margin agreement is assumed to have a zero minimum transfer amount. The lender would have a residual exposure (E(t) – B(t+u)(1-g))⁺, where g is a constant, 1 > g ≥ 0. Exposure to C is assumed flat after t. We can write the loss function from holding the collateral as follows,

L(t + u) = E_t(1 – B_t+u/B_t (1 – g)/(1 – h))⁺ = (1 – g)B_t(1 – B_t+u/B_t (h – g)/(1 – g))⁺ —– (1)

Conditional on default happening at time t, the above determines a one-period loss distribution driven by asset price return B(t+u)/B(t). For repos, this loss function is slightly different from the lender’s ultimate loss which would be lessened due to a claim and recovery process. In the regulatory context, haircut is viewed as a mitigation to counterparty exposure and made independent of counterparty, so recovery from the defaulting party is not considered.

Let y = (1 – B_t+u/B_t) be the price decline. If g=0, Pr(y>h) equals to Pr(L(u)>0). There is no loss, if the price decline is less or equal to h. A first rupee loss will occur only if y > h. h thus provides a cushion before a loss is incurred. Given a target rating class’s default probability p, the first loss haircut can be written as

h_p = inf{h > 0:Pr(L(u) > 0) ≤ p} —– (2)

Let VaR_q denote the VaR of holding the asset, an amount which the price decline won’t exceed, given a confidence interval of q, say 99%. In light of the adoption of the expected shortfall (ES) in BASEL IV’s new market risk capital standard, we get a chance to define haircut as ES under the q-quantile,

h_ES = ES_q = E[y|y > VaR_q]

VaR_q = inf{y₀ > 0 : Pr(y > y₀) ≤ 1 − q} —– (3)

Without the liquidity discount, h_p is the same as VaR_q. If haircuts are set to VaR_q or h_ES, the market risk capital for holding the asset for the given MPR, defined as a multiple of VaR or ES, is zero. This implies that we can define a haircut to meet a minimum economic capital (EC) requirement C₀,

h_EC = inf{h ∈ R⁺: EC[L|h] ≤ C₀} —– (4)

where EC is measured either as VaR or ES subtracted by expected loss (EL). For rating criteria employing EL based target per rating class, we could introduce one more definition of haircuts based on EL target L₀,

h_EL = inf{h ∈ R⁺: E[L|h] ≤ L₀} —– (5)

The expected loss target L₀ can be set based on EL criteria of certain designated high credit rating, whether bank internal or external. With an external rating such as Moody’s, for example, a firm can set the haircut to a level such that the expected (cumulative) loss satisfies the expected loss tolerance L₀ of some predetermined Moody’s rating target, e.g., ‘Aaa’ or ‘Aa1’. In (4) and (5), loss L’s holding period does not have to be an MPR. In fact, these two definitions apply to the general trading book credit risk capital approach where the standard horizon is one year with a 99.9% confidence interval for default risk.

Different from VaR_q, definitions h_p, h_EL, and h_EC are based on a loss distribution solely generated by collateral market risk exposure. As such, we no longer apply the usual wholesale credit risk terminology of probability of default (PD) and loss given default (LGD) to determine EL as product of PD and LGD. Here EL is directly computed from a loss distribution originated from market risk and the haircut intends to be wholesale counterparty independent. For real repo transactions where repo haircuts are known to be counterparty dependent, these definitions remain fit, when the loss distribution incorporates the counterparty credit quality.