Making Real Sense of Real Exchange Rate of Indian Rupee 

By VK Sharma , Former Executive Director, RBI 

It is a stock  refrain of business and industry in India , as indeed globally,   that they consistently need competitive exchange rate to succeed in a highly competitive global trade environment. Of course, a competitive and fairly valued exchange rate is also a macroeconomic policy imperative for a sustainable balance of payments . But competitive exchange rate shouldn't be  at the expense of productivity and efficiency of domestic production . However, given an optimal level of productivity and efficiency of domestic production, competitiveness of exports may still be compromised by higher domestic inflation relative to that in trading partner countries  and in third countries which also compete in a country's export markets ! But it is noteworthy that former Prime Minister Margaret Thatcher reportedly  pursued a strong real exchange rate policy to compel British business and industry to significantly improve productivity and efficiency of domestic production to stay competitive in their export markets , quite apart from making imports cheaper and inflation lower in the process ! 

By now it is clear that even if nominal exchange rate of Indian Rupee remains stable or depreciates , it's real exchange rate may still appreciate unnoticed over a short horizon due to domestic prices rising more than  in our trading partner countries and in our competitor countries. To measure real appreciation and depreciation of a currency, Real Effective Exchange Rate , REER for short, is globally the widely used metric . But this metric is derived from what are called Nominal Effective Exchange Rate , NEER for short, and Effective Relative Price , ERP for short . NEER is not a single currency exchange rate but a ( geometric) weighted average index comprising currencies of countries which are India's major trading partners and countries which are our competitors in our export markets , with weights being shares of respective countries in India's total trade basket . Thus , in its concept and design, it is exactly like Consumer Price Index ( CPI for short ) . NEER of Indian Rupee is thus the weighted average of the ratios of exchange rate of Indian Rupee expressed as one Rupee in terms of a numeraire ( SDR) and one unit of select countries currencies also expressed in terms the same numeraire ( SDR) . As per the RBI website , this  is what the RBI has done but any other common numeraire will equally do . 

ERP is nothing but again the weighted average of the ratios of CPI in India and CPIs of select countries included in the NEER . And finally, REER is simply NEER multiplied by ERP and obviously, like in the case of any index, is normalised to 100 in the chosen base year . Thus, in the  base year, all the three metrics are normalised to 100 . The way the above indices are constructed, increase in their values represents  appreciation of the Indian Rupee and vice versa . 

For Indian Rupee 's NEER , ERP and REER , the base year used by RBI  is 2004-5 . Also , RBI computes and publishes these metrics on a monthly basis . As of the date of writing this column , the the latest month for which NEER and REER are available on RBI website is May 2015 . RBI computes and publishes 6 currency and 36 currency NEERs and REERs . 

In May 2015, the 6 Currency NEER was 68.94 and REER 122.21 and dollar rupee exchange rate was 63.80 . Although RBI website doesn't give ERP , it can be backed out from NEER and  REER as 122.21/ 68.94 = 1.7727*100= 177.27 . Thus , we see that , while the rupee depreciated in nominal terms by 31% , in real terms , it appreciated by 22.21% because of relative prices in India rising by 77.27 % over the 10 year period since the base year 2004-5 ! 

But it is more insightful and useful to make real sense of the Real exchange rate of the rupee by looking at what this means  in terms of where the dollar rupee ought to be for restoring the REER back to 100 as in the base period 2004-5 ! And the way to do this is simply to multiply the relevant dollar rupee exchange rate of ₹ 63.80 by the latest REER/100  , that is , 63.80 * 1.2221 which gives ₹ 78 ! In other words , to make Indian exports as competitive as they were in the base year 2004-5 , ceteris paribus , the dollar rupee nominal exchange rate needs to depreciate to ₹ 78 . Another instructive way to make real sense of the real exchange rate is to back out , from the latest available REER reading 122.21 ,  the base period  REER reading in terms of the dollar rupee exchange rate . However , it must be noted that this dollar rupee exchange rate will not be the actual dollar rupee exchange rate used in the REER computation . And the way to do this is simply to divide the current dollar rupee exchange rate of ₹ 63.80 by the current REER 1.2221which gives ₹ 52.20 . In other words , what exporters were getting  in May 2015 was not ₹63.80 but actually only ₹ 52.20 per dollar in real terms and , therefore, for exporters to continue to get what they were getting in base year 2004-5 , ceteris paribus , the rupee needs to depreciate in nominal terms from the current ₹ 63.80 to ₹ 78 . Based on the 36 Currency REER , the rupee needed  to depreciate from ₹63.80 to ₹ 70 and for every one dollar , exporters were getting in May 2015 not ₹ 63.80 but only ₹ 58 ! This then is the insightful and useful way of making real sense of the real exchange rate of the rupee ! 

The Inevitable Challenge of Financial Leverage in Modern Banking 

VK Sharma , Former Executive Director , Reserve Bank of India

 vksvs2009@gmail.com

The inevitability  of the challenge of public policy having to countenance higher, but not excessive, financial leverage in banks relative to that in non-bank corporates, arises from the public policy imperative of efficient and effective transmission of monetary policy in the larger interest , in turn, of the public policy imperative of a globally competitive and efficient real economy, in which modern banks play a critical intermediation role . 

( The author’s paper in the Colloquium in April- June 2015 issue of Vikalpa, The Journal for Decision Makers , published by Indian Institute of Management, Ahmedabad http://vik.sagepub.com/  ) 

To see why higher financial leverage in modern banks  is inevitable for efficient and effective transmission of monetary policy is to consider the extreme case of Equity Multiplier of 1 which means the entire assets of a bank are funded by common equity only . To deliver market competitive  equilibrium RoE ( Return on Equity)of ,say 14%, a bank’s RoA ( Return on Assets) will also have to be 14% . So , even if policy rate be 1% , banks will, no matter what , lend at 14% plus only , and no lower ! Modern, competitive, safe, sound and efficient banks have typically operated on an RoA of 1% and EM of 14 times delivering RoE of 14% . Thus both modern banks and non bank corporates have generally delivered market competitive equilibrium RoE of 14% with their financial leverage, as measured by Equity Multiplier, poles apart ! But those who swear by the Modigliani-Miller Theorem aver that such higher financial leverage in banks relative to that in non-bank corporates will not work because higher leverage, or so much lower nominal common equity, will make  cost of bank debt/deposits higher. But in what he believes a first, the author provides a very original insight that lower nominal common equity is complemented by what the author calls “quasi equity” comprising 1) effective and credible bank supervision/regulation, 2) deposit insurance 3) implicit taxpayer guarantee and 4) a central bank’s lender of last resort function ! Of course, another name for all these fouris the so-called  “moral hazard”! And, in fact, the author argues that this “quasi equity” brings banks on par with non-bank corporates in terms of equity and, thus, makes the business model of modern  banks consistent with the Modigliani-Miller Theorem, one for one! Thus, the author shows that while , in terms of nominal common equity, banks and non-bank corporates are poles apart, in terms of being compliant with the Modigliani-Miller Theorem, they both become identical as both deliver similar market competitive equilibrium Return on Equity (RoE), in spite of way too diverging financial leverage , because they both have necessarily to compete in the same capital markets for raising equity capital ! 

4.             If only to complete the story of the inevitability of the challenge of financial leverage in modern banking and central banking , it would only be appropriate to put it in historical perspective . Specifically , in the mid 1800s,  Danish banks had leverage ratio( inverse of EM) of 75% , Americans had 55% and European ones had 25% in early 1900s cf  The Economist of 12 November 2012   " How much capital banks had when they had choice"  ! In other words, banks then had roughly the same business model as non bank corporates have today !  And significantly, monetary economics, monetary policy and modern central banking with lender of last resort function and bank regulation and supervision and deposit insurance , as we know them today , were nonexistent then and followed only later  in the late 1800s and early 1900s, and ,so did with them, the challenge of the inevitability of higher financial leverage ! And from there , it took about a century to reach Basel 2 which prescribed capital adequacy , not  in terms of common equity as a percentage of total assets( leverage ratio) , but risk- weighted assets ,quite apart from introducing the so-called Tier 2 debt capital , thus sowing the seeds of the worst global financial crisis what with financial leverage in global banks , reachingfrom less than 2 times ( leverage ratio of more than 50% ) in the early twentieth century to more than 50 times ( leverage ratio of less than 2% ) in the early twenty first century ! This happened because pre crisis global banks ,in spite of being compliant with Basel 2 on a risk weighted basis ( capital adequacy of 8%) , had risk weighted assets of only 20% of their actual total assets which had the effect of increasing their financial leverage, measured by Equity Multiplier , by 5 times ( leverage ratio of less than 2% as noted above ) ! 

But then, there is no free lunch; there is a price to be paid by economic agents and stakeholders in the form of effective and credible bank supervision/regulation which, significantly, depending upon how effective and credible it is, reduces potential recourse to the other three moral hazards of deposit insurance , taxpayer-funded bailout and central bank as lender of last resort !  The challenge of higher financial leverage in modern banking is inevitable given the imperative of efficient and effective monetary policy transmission in the real economy so that borrowing costs in the real economy  are higher not because of lower financial leverage/ higher leverage ratio but largely, if not only , because of higher monetary policy rates and vice versa  ! This is precisely here that the synergies  between monetary policy , credible and effective banking supervision and , no less ,  lender of last resort function , come in and which is why banking supervision was taken away from the now defunct Financial Services Authority and given back to the Bank of England after the crisis . In decisively and deftly managing the inevitable challenge of leverage in modern banking , effective and credible supervision makes  for efficient and effective monetary policy transmission and , in the process , makes for a globally competitive and efficient real economy ! In other words, there is a trade off between leverage and effective, credible, proactive, preemptive  , and even intrusive, supervision of banks. In other words, the more effective and credible the supervision, the higher the leverage threshold can be and vice versa !  The higher regulatory capital,or lower leverage, is the cost of supervisory failure,, inertia and inaction imposed on banks but borne by the real economy !  To make this seemingly heretical statement realistic , one can make leverage subject to a ceiling as indeed, as we have seen above , Basel 3 has done ; only this ceiling or limit is limited only by the fallibility of those in charge of banking supervision ! So to conclude , to prevent a repeat of the worst global financial crisis , what we need more than, and beyond, Basel 1,2,3,4.......is supervisory temper,culture and attitude !

 Significantly, and hearteningly, to the credit of the RBI and the Indian banking sector, Indian banks collectively have an average leverage ratio ( inverse of EM) of 7%+ which,  at about 2.5 times, is way higher than 3% mandated under Basel 3 capital rules to be complied with only in 2018 ! Incidentally, but significantly, Indian banks being already 2.5 times Basel 3 compliant with leverage ratio of 7% + will need to increase equity capital only to maintain their existing leverage ratio i.e to remain compliant with themselves and not at all to comply with Basel 3 as is widely , but erroneously, made out in many quarters ! This conclusion will very much be valid even if the denominator of the leverage ratio is inflated to include all off balance sheet liabilities which ,in the case of Indian banks,  are about 100% of the aggregate assets because this will only reduce the leverage ratio from 7%+ to 3.5%+ which is still higher than Basel 3 requirement of 3% ! I

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Getting Credit Default Swap Market  In India Up and Running 

I propose to discuss in my column today the long overdue imperative of developing a vibrant Credit Default Swap market in India . 

In the inflating of the credit bubble in the run up to the Global Financial Crisis , and its inevitable concomitant, the Great Recession from which the global economy is yet to recover , inflated ratings to sub-prime mortgage backed Collateralised Debt Obligations by global rating agencies played a significant role. Given,therefore, the question mark over the infallibility of rating agencies, the Basel Committee needs to revisit the primacy of role assigned to ratings of such agencies for assigning capital charge for credit risk by banks . In fact, credit appraisal and measurement are the most basic functions of intermediation performed by banks traditionally. In the light of this, ratings may be meant for, and be relied upon by, the unsophisticated and uninitiated retail and small investors, but certainly not banks. Besides, given the fact that pre-crisis rating agencies generated almost 40 per cent of their revenues from assigning the so-called inflated ratings to CDOs (Collateralised Debt Obligations) tranches, backed by sub-prime mortgages and the obvious inherent conflict of interest involved, the US Congress and regulators investigated the role and function of rating agencies in the aftermath of the Global Financial Crisis. In view of this, Basel Committee needs to de-emphasise ratings assigned by Rating Agencies for assigning capital charge for credit risk by banks. Indeed, if anything, given the tremendous volumes and liquidity of Credit Default Swaps (CDSs), both single-names and indices-based, it would be far more market-price discovery-driven for banks and regulators alike to rely on prices backed out from these credit derivatives . Indeed, CDSs price credit risks almost on real-time basis as much as Government bonds , foreign exchange, stock and commodities, markets do. Credit rating agencies, in comparison, are inertial and lagged. In the way of example, in the USA, the traditionally very healthy AAA rated mono-line municipal bond insurers MBIA and Ambac changed their business model from insuring only their staple municipal bonds to insuring CDOs and ABS (Asset Backed Securities) . While this went unnoticed by insurance regulators, Pershing Square, a hedge fund, spotted trouble and started shorting both equity and credit risk of these two companies by buying their CDSs. But even after sharp increase in real time CDS spreads of these two insurers , regulators failed to take notice of these early warning signals and any timely preemptive corrective action with the two companies being eventually downgraded several notches by Credit Rating Agencies but only much afterwards ! Significantly, as if to redeem their lost infallibility and reputation, these Rating Agencies , almost immediately after the financial crisis, started a new service which provided implied credit ratings backed out/derived from CDS spreads ! There is thus a very strong case for kick-starting a full-fledged CDS market in India. 

The popular refrain that the last global financial crisis was caused, or exacerbated,  by CDSs is again a myth in that CDSs which are simple plain-vanilla off-balance-sheet/non-fund based credit derivatives, were confused with the CDOs (collateralised debt obligations) which are on-balance-sheet and funded securitised structured credit products. It was securitisation/re-senuritization, involving CDOs that played a seminal role in the crisis and no way the CDSs ! In fact, it is also a myth that securitisation through CDOs was an originate-to-distribute model; rather, really speaking, it was an originate-to-distribute-back-to-originators model! This is because almost all CDOs originated came back to sit on the SIVs (Structured Investment Vehicles)/ conduits sponsored by originating banks themselves. Besides, for all the overdone and totally uninformed fears about systemic risks from the so-called unregulated Over the Counter (OTC) CDS markets, remarkably orderly and non-disruptive auction-based settlement of CDS claims in respect of CDSs written on Lehman Bros., Icelandic Banks, Fannie Mae, and Freddie Mac, incontrovertibly attested to the resilience of CDS markets. Indeed, if anything, CDSs can be an effective and neat answer ,and substitute,for lagged and inertial ratings of credit rating agencies ! And indeed precisely for this reason , RBI should not insist on CDSs being allowed only on listed and rated corporate bonds as what listing and rating purport to deliver is actually delivered far more efficiently on real time basis by CDSs , as typically, CDS markets sniff out financial mess much faster than even equity markets ! 

Interestingly, the New York Fed-led initiative to improve the OTC CDS markets sought to replicate India's CCIL ( Clearing Corporation of India Ltd) -model, where although OTC foreign exchange transactions are bilaterally negotiated, they are cleared and settled through RBI -sponsored Clearing Corporation of India Ltd. (CCIL). Today CDS prices/spreads are by far the most closely tracked early warning signals for real time changes in credit risk profile of an entity, whether private or sovereign. This is because CDSs make it possible to back out an implied credit price even when one is not being discovered in the underlying cash market instruments like bonds or loans as indeed in the latest instance of Deutsche Bank where its CDS spread widened real time from 100 basis points to 245 basis points in a matter of a week !   Thus, CDS market has tremendous practical application as a reliable diagnostic tool in stress-testing for supervisors and regulators. Besides, a CDS market will also enable efficient trading and hedging of credit risk and synergise development of active and liquid corporate bond and Repo markets. Like equity, credit risk subsumes all other risks as it is a function of forex risk, interest rate risk, leverage risk, liquidity risk, human resources and governance risks and that is why CDSs and equity prices have been , in equilibrium, almost perfectly negatively correlated, that is, as CDSs spreads widen, equity prices fall almost one for one !


Credit Default Swap, like Interest Rate Swap (IRS), or for that matter any other derivative, is no exception to the so-called law-of-one-price/ no-arbitrage-argument based cash market replication principle of derivatives pricing. Without going into mathematical gymnastic proper, price of a CDS, in spread terms, is reasonably approximated by the difference between the spread of a reference bond/loan to corresponding maturity G-Sec ( Government Security) yield and the spread of IRS to the same maturity G-Sec yield. Thus, if Sc be corporate bond spread and Ss be IRS spread to risk-free G-Sec yield of corresponding maturity, then the fair/theoretical/model value/price of a CDS is approximately equal to Sc minus Ss. Tautologically, since G-Sec yield is common to both spreads, another way to approximate CDS price is simply to take the difference between the yield of the reference bond/loan and the same maturity IRS yield. As is well known , finally when the product was launched in India on 7th December, 2011, it was a stillborn and remains so even after RBI’s revised Guidelines issued on 7 January 2013 . In fact, its epitaph was written in the warped, anomalous, quirky and preposterous feature of hugely negative IRS yield spreads to corresponding maturity G-Sec yields and which,alas, exist even today !  For, as one will readily see from the above formula, because of the hugely negative IRS spreads, fair price of a CDS would be so high as to make it both pointless, and useless, to buy a reference bond and also hedge it with a CDS! In other words, one is much better off straightaway buying a corresponding maturity risk-free G-Sec itself because hedged reference bond would have CDS-cost adjusted yield of G-Sec yield minus the IRS spread rather than the normal G-Sec yield plus the IRS spread ! Significantly, if actual CDS premium/price/spread is higher than the above theoretical/model price, then an arbitrageur will sell a CDS (which is equivalent to going long the reference corporate bond) and receive this actual spread and short the reference bond and invest the proceeds of short sale at the going corporate bond repo rate and receive fixed, and pay overnight, in an IRS, and do the opposite arbitrage if the actual CDS spread is lower than the theoretical/model spread/price until the arbitrage opportunity disappears and theoretical/model and actual market prices align again. But sadly, like in a classical catch-22, this arbitrage is just not possible simply because of its complete absence in the IRS market and, therefore, alas, much as we would all wish, a happening corporate bond market cannot happen, inter alia, to supplement huge infrastructure financing needs of the Indian economy!        

“Why even an NDF Dog cannot wag the on-shore tail, much less an NDF tail wagging the on- shore Dog !”

By VK Sharma,

Former Executive Director, 

Reserve Bank of India                                       

       There is quite some compulsive feel, rather than any grounding in logic and reason, to the current hype and hoopla over Non -Deliverable Forward (NDF) market influencing the on-shore USD-INR market ! And,no less, a high degree of interlinkage / correlation between the two is confused with causality. This is because the whole debate lacks in conceptual clarity on how arbitrage actually happens both, in theory, and practice. Only through the organic connect of arbitrage is it possible for information in one market to be seamlessly transmitted to, and influence,the other market. Arbitrage between discrepant prices of an asset in two different markets requires taking simultaneous long and short positions to benefit from, and eventually align, the discrepant prices in two markets. Tautologically, this arbitrage is risk free in that loss on one position is offset by a matching gain on the other and vice versa .  But restrictions on who, and how one, can take positions in the on-shore and NDF USD-INR market come in the way of agents engaging in risk-free arbitrage for NDF market to influence exchange rate in the on-shore market. More specifically, domestic entities, whether banks or businesses / individuals, are not permitted to engage in any transactions in NDF market. But banks are permitted to take open positions in the on-shore OTC (Over the counter) forward market subject to RBI monitored, and supervised, limits and businesses/ individuals are permitted to engage in on-shore OTC forward market subject strictly to actual underlying - exposure requirement and not otherwise . In other words, a forward seller (exporter) has to have actual underlying export and a forward buyer (importer/ foreign currency borrower) has to have actual underlying import/ foreign currency loan. Therefore, if FEMA regulations are not breached / violated, arbitrage between the two markets is impossible because the net position will always be open and not zero which is the hallmark of any arbitrage. Specifically, if forward dollar is trading higher in the NDF market relative to the one in the on-shore forward market, an arbitrageur will typically sell the dollar forward in the NDF market and buy it forward in the on-shore market. But a domestic entity cannot do this because of FEMA regulations which require an actual underlying exposure i.e. either an import order or foreign currency loan. And if there indeed is such an actual underlying exposure, then the net position is not zero- a ' sine qua non ' for a typical arbitrage - but actually net short because the actual underlying short position of import/ foreign currency loan is offset by the on-shore long forward dollar position, leaving the NDF short dollar position open and thus exposing the entity to the risk that the US dollar may appreciate which may potentially more than wipe out the entire arbitrage profit ! Of course, if only there is no underlying actual exposure in the way of import, or foreign currency loan, will a typical arbitrage be possible with the on-shore long forward dollar position exactly offsetting the NDF short forward dollar position, locking in the benefit of higher NDF forward dollar price ! But this will not be possible if FEMA regulations are strictly monitored and actually enforced . In other words,  only in breach and violation alone of FEMA regulations will the much-hyped arbitrage be possible and in no other way ! The same holds when the opposite is the case viz; the forward dollar price is higher in the domestic on-shore market relative to the one in the NDF market in which case an arbitrageur will typically sell dollar forward in the domestic on-shore market and buy dollar forward in the NDF market. But, again, a domestic entity cannot do this because of FEMA regulations which require an actual underlying exposure i.e. export order. And, therefore, as before, if there indeed is such an actual underlying exposure then the net position is not zero - a ' sine qua non ' for a typical arbitrage - but actually net long because the actual long position of export is offset by the on-shore short forward position, leaving the NDF long dollar position open and thus exposing the entity to the risk that the US dollar may depreciate which, as stated before, may potentially more than wipe out the entire arbitrage profit ! Of course, if only there is no actual underlying exposure in the way of export will a typical arbitrage be possible with the on-shore short forward dollar position exactly offsetting the NDF long forwarddollar position, locking in the benefit of higher onshore forward dollar price ! But again, as before, this will not be possible if FEMA regulations are strictly monitored and actually enforced. In other words, again , as before, only in breach and violation alone of FEMA regulations will the much - hyped arbitrage be possible and in no other way ! The foregoing thus conclusively proves and establishes that the NDF USD INR market influencing the on-shore USD INR market cannot just happen, except ,of course, only in breach and violation of FEMA regulations, and to that extent, RBI and Government must agonize only over effectively,decisively, credibly and inviolably enforcing extant FEMA regulations ! 

While still on the subject, as regards statistically establishing causality, this can be credibly and effectively done by recourse to the so-called Granger Causality Test. But it is very important that the USD-INR data points must be taken as frequently as feasible for the Granger causality conclusions to be robust and reliable. Ideally, such data points can be taken at 5 to 1 minute intervals when both the markets are active . Since  NDF market is almost a 24- hour market, the data points can easilyoverlap the market timings of the on-shore market. Significantly, under no circumstances should  Granger Causality Test   be applied to closing data points !