The changes in taxation of transactions in futures on equity and commodity underlyings

Taxation of transactions in India began with the equity market in 2004. Prior to 2008, the securities transaction tax (STT) was allowed as a rebate against tax liability against Section 88E of the Income Tax Act. This treatment was withdrawn by the 2008 Budget announcement. After that, STT became a substantial influence on the equity market. In understanding the consequences of the STT, there is an absolute perspective and there is a relative perspective.

In absolute terms, suppose you embark on a spot-futures arbitrage and do an early unwind. In this, you buy shares (pay 10), sell futures (1.7) and then reverse yourself (10). Your tax burden is 21.7 basis points. This is a lot of money when compared with the typical bid-offer spread of the Nifty futures which is around 0.5 basis points. The dominant cost faced in doing spot-futures arbitrage is taxation.

In relative terms, there are two issues. The first is an intra-India comparison between equities and commodities. When activity on the equity market was taxed, eyeballs and capital moved to commodities trading. Commodity futures trading has grown by 3.5 times after 2008, while equities activity has stagnated. Most policy makers think this was an undesirable effect, particularly given the fact that India can free ride on global price discovery for non-agricultural commodities but must foster liquid markets in its own equities.

And then, there is an international dimension. When the activities of non-residents in India are taxed in any fashion, they favour taking their custom to places like Singapore, which practice `residence-based taxation’ where the tax base comprises the activities of residents only. We got a sharp shift in equities activity towards locations outside India.

Putting these absolute and relative perspectives together, from 2008 onwards, equity market liquidity has fared badly. This yields an elevated cost of equity capital.

The budget speech has done two things. First, it has dropped the STT rate on futures on equity underlyings from 1.7 basis points to 1 basis points. This is helpful for certain kinds of trading strategies but not for others (e.g. the spot-futures arbitrage described above will gain little). HF strategies that do not involve the spot market will particularly benefit – e.g. imagine an options market maker who does delta neutral hedging on the futures market. Second, it has introduced taxation for non-agricultural commodity futures on an identical basis to the equity futures (i.e. at 1 basis points).

This will have the following interesting implications:

  1. Capital and labour in securities firms will be less inclined to be in non-agricultural commodity futures. It will tend to move towards agricultural commodity futures, currency futures and equity futures.
  2. The comparison between offshore venues and the onshore market will move in favour of the onshore market for certain kinds of trading strategies.
  3. The bias in favour of equity options will reduce; some business will move to equity futures.
  4. The pricing efficiency of futures will go up.

In this environment, there seems to be a fair arrangement between the equity futures and commodity futures. Conditions seem to be unfair with the equity spot (too high), equity options (too low) and currency derivatives (too low). The next moves on this may appear in July 2014 when the new government unveils its next budget.

One more announcement of the budget speech concerns currency futures: it was stated that FII activity on currency futures will commence. This will also give more activity on currency futures; we now have two reasons for expecting more activity on currency futures (the taxation of commodity futures and the entry of FII order flow). However, the shifting of FII order flow will be a slow process, and a lot of time will be lost on their due diligence of the exchange, safety of the clearinghouse, and so on. While, in the long run, removing capital controls against FII order flow in India is a good thing, it is not an effect that will kick in quickly. Apart from this, most of the action will take place fairly quickly, in early April.

Future finance ministers will need to navigate the difficult landscape of gradually scaling down taxation of transactions while retaining low taxation of capital gains (which has unfortunately come to be seen as a linked issue in the Indian discourse). Along this path, the first priority should be to remove distortions. Our first priority should be to achieve a low rate, a wide base, and the minimal distortions. Reduced rates will always yield welfare gains. The Budget 2013 announcement makes progress on two things (reduction from 1.7 to 1, and reduced distortions between equities and non-agricultural commodities). There is much more waiting to be done: integrating currencies and fixed income, bringing sense to options, and getting away from the very high rates on the equity spot market.

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The rise of high-end finance work in India

Until recently, outsourcing by global financial firms to India conjured up an image of commoditised low end services outsourcing: call centres, peripheral systems programming, and testing and maintenance. However, in recent years, there is a new rise of more sophisticated work. This reflects supply and demand factors. Global financial firms are keen to cut costs. Capabilities of operations in India — both captives and independant firms — have grown for many reasons:

  • The individuals involved in this field in India have gained experience (”learning-by-doing”) and credibility.
  • New management practices and improved telecommunications technologies have improved the extent to which teams and projects are handled in a more non-local way.
  • The Indian diaspora has been rising to senior management levels in global firms, and is better able to envision what can be done in India and to obtain execution.

A European investment bank was among the first to experiment by bringing in teams in India into critical projects. This was a landmark change as a lot of inertia about confidentiality was overcome. Other banks followed suit. New management practices, higher pay, greater meritocracy came in, which helped Indian teams make the transition from low-end work where the HR and management techniques used are quite different. Demand for high skill labour has helped induce greater supply, with a lag, as individuals were more inclined to tool up with advanced degrees and high-end knowledge.

Alongside the developments in finance, parallel developments were taking place in the field of offshoring which have driven up skill levels, and helped create a high skill ecosystem in India. Top tier consulting firms launched `centres of excellence’ in India, hiring grads from IITs, IIMs, IISc, statisticians, economists. While education in India has huge problems, the raw talent available in India was of good quality, particularly when we focus on individuals who were able to read on their own and reinvent themselves (”never let your school come in the way of your education”). This process has been helped by globally recognised certification exams such as the FRM and the PRM.

IT firms have have been evolving from core development and maintenance to an entire gamut of IT strategy and consulting for financial firms. Many smaller KPO firms with specialised domain knowledge in finance have emerged, who cater to smaller hedge funds, trading houses, not just outsourcing increasingly complex pieces of work, but also advising them on the entire outsourcing strategy. All this has helped create a pool of high skill labour which is moving between multiple employers in India and able to build knowledge through diverse kinds of experience.

The most impressive development of recent years has been the growth of offshore trading units of global brokerages and trading houses, where people sitting in India take independent trading decisions in international financial markets based on their own skills and judgement. In some ways, this is the highest level of transfer of decision functions to India, albeit at relatively low monetary stakes.

In this fashion, within a period of 15 years, India had graduated from doing repetitive low value tasks to Knowledge Process Outsourcing (KPO) for the global financial system. While these activities are primarily in Bombay, they are also taking place in Gurgaon and Bangalore. The number of high-end finance workers in Bombay has never been greater than it is today. It is estimated that there are now 50 individuals working in Bombay doing work for global financial firms who have Ph.D. degrees in quantitative fields. This is starting to become a big enough number for them to talk with each other and get network effects going. From an employer’s point of view, it is now possible to shop in the labour market in Bombay and recruit a 10-man team all with Ph.D. degrees so as to get a new group going. This is a sea change when compared with conditions just a few years ago.

To appreciate this change a little further, it was interesting to take a look at some of the capabilities of finance focussed KPOs, divided mainly into 4 broad categories, catering to Sales and Trading, Middle office and Back office:

  1. Quantitative Research and Analytics Support:
    1. Equity and FICC Analytics: Model Validation, Price Verification jointly with clients: these are pretty quant heavy functions which require in-depth understanding of products.
    2. Technical and Fundamental Analytics.
    3. Index and Portfolio Analytics: Index maintenance, design, construction, operations and after sales, Portfolio tracking, decomposition and correlation analysis, performance measurement and attribution support.
    4. Derivatives and Risk Analytics: Measurement of derivatives Greeks, Value at Risk, Tolerance checks.
  2. Research:
    1. Equity and FICC Research: Company research, Credit Research, Economics research etc. to augment senior analysts in money centres.
    2. Trade idea generation and back testing: Sales pitches for clients and internal trading desks.
    3. Country, Sector, Company profiling, trends, news and projections: Pitch book generation and support.
    4. 24×7 weather patterns tracking for global energy trading outfits
    5. Overnight trade and market tracking to feed in summary reports, Market Dashboards, news letters, morning meetings and agendas
    6. Market Research: Pre-entry market research and positioning survey for bank’s clients.
  3. Data Analysis and Modelling:
    1. Data sourcing from multiple heterogeneous sources, refining and maintenance: Static data, Live and Historical market data maintenance. Data research and statistical studies feeding into trading strategies.
    2. Data Mining solutions.
    3. Data modelling, smoothing: Providing data solutions for Algo trading desks.
  4. Operations and Control
    1. Derivatives trade processing and documentation: Trade review of structured trades and complex documentation. End to end life cycle management of trades e.g., matching, broker confirmations and fee calculations.
    2. P&L and balance sheet control: Generation and reporting of P&L for vanilla products. Some banks have started moving exotics P&L functions to India. This is quite a significant milestone as such activities require high degree of confidentiality and direct user (e.g., traders) interaction who have zero tolerance for mistakes.
    3. Risk Stress testing, VaR back testing, Risk reporting to senior management.
    4. Auditing: external auditing of valuation marks of trading desks and control processes around it.
    5. It should be noted here that since the funding crisis of 2008, these jobs have become quite complex as most banks have built more sophistication into their analytics. For example, most yield curves would now have multiple basis spreads (like tenor basis, xccy basis) and not just rates desks but even credit and equities desk have been using such advanced discounting curves.)

What’s next

The biggest push probably has been in quantitative middle-office functions with an ever increasing emphasis on valuations and counterparty risk management. Given the way markets have adopted collateral based pricing of derivatives, and the regulatory push on managing counterparty default risk, some captives have started building quantitative teams who will develop and manage CVA, DVA, etc. processes for all trading desks.

The new regulatory climate (Dodd Frank, Basel III etc) has lead to a substantial increase in costs due to additional checks and reporting requirements e.g., centrally cleared OTC trades, real time trade reporting to regulators, exhaustive risk reporting – all of which can are leading to fresh volumes of activity in offshoring.

All high quality banks have a team of techno-quants who work closely with the sales/trading desk, risk managers etc, on their day to day needs as well as on strategic projects. It is now feasible to move such high impact roles to India. It would be possible to have “extended front office teams” where dedicated staff support traders in money centres, doing real time risk analysis and client profiling, while the trade is being dealt overseas.

For a back-of-envelope calculation, if we think of internal billing rates of $100,000 per person per year, and if there are 10,000 persons at this average price, then this is services export of $1 billion a year, which is a sizeable amount. It appears that the early beach-head is in place, and this area will grow dramatically now.

This blog post reflects my experience, which is in investment banking and money management. A similar escalation of complexity of work in India is taking place in retail banking, insurance, etc., reflecting similar compulsions and opportunities.


There is a certain tension between the push towards offshoring to India, and the activities that regulators consider `key in-house activities’ that cannot be outsourced.

There are serious constraints with education in India. The top institutions are producing some quantitative skills (e.g. fluency with matrix algebra, fluency in numerical computation). On one hand, there are weaknesses of broad intellectualisation that shapes cognition, creativity and malleability. On the other hand, there is essentially nothing in place by way of a finance education in India. A small amount of high-end finance research is taking place (example) but for the rest, there isn’t much capacity in the existing academic campuses. New approaches to learning and training need to be devised through which high quality individuals, with strong quantitative skills, can be converted into full fledged participation in high-end global finance work. A mix of public and private initiatives are required in order to jump to the next level.

There are strong synergies between the sophistication of the Indian financial system and the work that is done for global financial firms. There is a two-way feedback loop here: Better domestic capabilities will help do sophisticated offshore work, and the brainpower built for offshore work will strengthen domestic capabilities. The best example of this is found in the equity derivatives market, where India has a world-class market. The individuals with a domestic background here are ready for offshore jobs in fields like algorithmic trading, and individuals with capabilities built in offshore work are useful in the domestic setting. This is where India can set itself apart from Malaysia and the Philippines. To the extent that Indian financial reform makes progress, this will fuel the rise of high-end outsourcing to India.


I am grateful to Anand Pai, Paul Alapat and Gangadhar Darbha for useful discussions.

International financial centres: Peering into the future

I did the SIGFIRM Quarterly Lecture at the University of California in Santa Cruz recently:

Also see: Mumbai as an International Financial Centre, a project led by Percy Mistry.

You may like to subscribe to the NIPFP MF channel on youtube.

Rupee and Real futures at ICE

Intercontinental Exchange has announced cash-settled futures on the Indian Rupee and the Brazilian Real [press release] [Saabira Chaudhuri in the Wall Street Journal]. With this, ICE is the first serious global exchange to start trading in the rupee.

Vimal Balasubramaniam and I have pointed out that the global market for the Indian rupee is adding up to some fairly big numbers. I recently noticed that in 2010, even though China is a much bigger economy than India, rupee trading was 0.9 per cent of global currency trading while RMB trading was at 0.7 per cent. Similarly, it appears that the INR NDF is bigger than the RMB NDF, even though China is a much bigger economy. Something is going right in the growth of the rupee as a big currency by world standards. Rupee trading at ICE would strengthen that process.

The ICE announcement also connects to the issues of global competition for Indian underlyings. The two biggest financial markets in India are Nifty and the rupee. So far, NSE faced serious competition with Nifty futures trading at SGX and CME, but there was no significant rival with the rupee. With the arrival of ICE, the competitive dynamics for the rupee changes, which is a welcome development. NSE now faces genuinely difficult competition from three first-tier rivals: CME, ICE, SGX. At the same time, the outlook for rupee trading in India is hobbled by an array of constraints:

  • ICE can pitch for business from non-residents, while NSE cannot, since foreign participation in currency futures is banned. We seem to think that OTC trading of currency forwards requires encouragement from industrial policy operated by RBI.
  • ICE is able to start contracts any time it likes on (say) the Brazilian Real while NSE is forbidden from starting any new contracts.
  • India has mistakes on tax treatment, lacking residence based taxation, while the world has all this well sorted out.
  • India has an array of other policy and regulatory mistakes that hobble local players. The ICE transaction charge is zero. I wonder if litigation will now start at CCI to try to block this.
A process is afoot, at present, through which the Indian financial system is being hollowed out. If this process runs unchecked, RBI and SEBI will be left lording over nothing. There is a need to reverse this  policy framework of reverse protectionism.
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The IRR of UIDAI is over 50 per cent in real terms

We have released a cost-benefit analysis of the UID system. In one line, the result of the calculations, under fairly conservative assumptions, is that the IRR of building the system is 53% in real terms. Hence, building UIDAI is a pretty good use of public money.

Through this page, you can access a short and accessible explanation, a video presentation, and the full PDF paper. We have also released the spreadsheet used in our calculations, so that others can modify the assumptions or other numerical values, and obtain alternative answers.

This is true in the Indian case. Is it true in general? I feel the answer depends on (a) The scale of expenditure on subsidy programs and (b) The extent to which present implementation systems suffer from the kinds of leakages that UID readily addresses (multiple payments to one person, payments to ghosts). If a country has small welfare programs, that would undermine the case for UIDAI. If a country is doing a pretty good job of paying out subsidies through conventional procedures, that would undermine the case for UIDAI.

Finding the right path in consumer protection

by Anand Sahasranaman.

The recent approach paper of the Financial Services Legislative Reforms Commission has brought a fresh focus on consumer protection. What are the possible frameworks for financial consumer protection in India, and what would be the core elements of an ideal framework? This is the question that the IFMR Financial Systems Design Conference 2012 sought to answer. The Conference titled Envisioning the Future of Financial Consumer Protection in India was held at IFMR Trust, Chennai, on 31st August and 1st September 2012.

The Conference was designed to take a first principles look at financial consumer protection, deliberately setting aside constraints that reflect the current realities of the Indian context of consumer protection. The conference was organised to carry out deliberations around three stylised approaches to consumer protection, namely: an Emphasis on Disclosure, an Emphasis on Eliminating Conflicts of Interest, and an Emphasis on Suitability. In reality, any consumer protection framework would include elements from all three approaches, and the objective in setting up the conference as a debate between approaches was meant to sharply identify the way in which these approaches would fit into an overarching framework for India.

Keeping in mind the two-fold agenda of creating a framework for solving the current failings of the Indian market and providing a meaningful long-term solution for consumer protection in view of the future of Indian finance, Suitability emerged as the paradigm of choice to be placed at the heart of the consumer protection framework for India. The Suitability framework shifts the onus of consumer protection from the buyer to the seller of financial services through legal liability on the latter. However, it was also felt that very important aspects of Disclosure and Eliminating Conflicts of Interest would need to be built around this foundation of Suitability.

A Suitability Framework

Suitability is defined to be a process that pervades all functions within financial services manufacturers, intermediaries, and their representatives, such that at all points of time, the provider acts in the best interests of the consumer. The power of the Suitability framework will derive from the imposition of legal liability on financial services providers to act in the best interest of consumers, and thus decisively shift the onus of consumer protection from the buyer to the seller.

Suitability will not take away the right of the consumer to choose. The final decision, on whether to accept the financial advice or buy the product recommended by the seller must always lie with the consumer. What Suitability is meant to ensure is that the consumer gets expert unbiased recommendations that are in her best interest.

For Suitability to be realised, every citizen must have the right to be provided suitable advice or recommended suitable products. The principle of Suitability needs to be enshrined in mother regulation and the interpretation of suitable behaviour would be best determined by the build-up of case law precedents over time, thus ensuring that our understanding of Suitability comes from the realities of the financial marketplace and its evolution over time

Role of Disclosure in Suitability Framework

India has so far relied on caveat emptor, or a disclosure based framework of consumer protection. Participants however noted the fact that increased disclosure has resulted in information-overload for consumers and, along with behavioural biases, led them to make sub-optimal decisions resulting in bad financial outcomes. Despite this, it was felt that there were aspects of Disclosure that would be essential in a Suitability framework. Within the Suitability framework, it was felt that disclosure of real time transaction level data that could be meaningfully analysed be analysed by neutral third parties – industry analysts, financial advisors, market aggregators, media – or “wholesale” consumers could be useful in developing comprehensible welfare enhancing consumer-level outputs. Other aspects of Disclosure such as the need for comparators and benchmarks for products, and the need to make some financial terms commonly understood were also deemed important.

Eliminating Conflict of Interest in the Suitability Framework

Regulatory regimes all over the world have used a variety of approaches to eliminate conflicts of interest that exist within providers of financial services. The most common approach is to disclose the existence of such a conflict to consumers and let the consumers decide for themselves. Within the Suitability paradigm, however, eliminating conflicts of interest is naturally built through the legal liability channel. Even in scenarios where is it is not possible to separate out advice from sale, given the legal liability in the form of a fiduciary responsibility on the provider, the provider is obligated to ensure that they act in the best interests of the consumer, ahead of their own self-interest.

The conference also raised a number of questions for research on the Suitability framework related to its implementation, legal framework, regulatory and institutional costs as well as lessons from international experiences.

The detailed conference proceeds can be found here.

Blindly sending money down leaky pipes

Proposals to spend more on government programs in India are generally criticised on the grounds that this is sending more money down a leaky pipe. In addition to the problem that the pipes leak, there is an equally big problem that we have no idea about what happens at the other end.

In order to build and refine a system, the first foundation that has to be laid is that of measurement. What you measure is what you can manage. In India, all too often, government agencies and programs start out with lofty ambitions, and embark on spending money to get there. But there is little measurement about the extent to which those objectives have been achieved. Under these conditions, there is little chance of programs being designed properly, and of wastage and theft being checked.

I was reminded of this as I read As Dengue fever sweeps India, a slow response stirs experts’ fears by Gardiner Harris in the New York Times. There may be an epidemic of Dengue out there. Or there might not be one. The point is, we just don’t know. The statistical system simply does not measure this.

A public goods perspective

What should government do, and what should government not do? The government should work on the provision of public goods and stay out of private goods. In the field of health, what are the public goods and what are the private goods?

When I have a toothache, and I go to a dentist, and I get better, this is a private good. Yet, most government spending is oriented towards building `primary health centres’ and hospitals and such like. Even if these worked well — i.e. even if they were not characterised by theft and incompetence — they are a bad use of public money as they deliver private goods and not public goods.

A public good is something that is `non-rival’ (my consumption of that good does not reduce your access to it) and `non-excludable’ (it is not possible to exclude me from benefiting from this good). The best example is clean air. My breathing in clean air does not diminish the amount of clean air available for you. When one more child is born, it is not possible to exclude him from benefiting from clean air.

What are the public goods in health? A few examples that come to mind:

  • Statistics. Measurement of what is going on about health in India.
  • Epidemiology. Tracking down and eradicating Smallpox. Mounting a response to fresh strains of the common cold.
  • Running public systems that measure and ensure that medicines are not counterfeited, are properly stored in a cold chain.
  • Running certification systems. Enforcing against quacks that practice medicine.
  • Getting research done on diseases that matter on India, and releasing the findings into the public domain (i.e. unencumbered by patents).
We in India have this essentially upside down. Health policy in India is unfortunately shaped by the views of doctors, and is low on skills in public economics. We like to focus on Primary Health Centres that are run by the government, and we cut corners on all the five critical public goods listed above.
It is fashionable to say that India should spend more on health. I would advocate spending less on the things that the Indian government does in health. Until the pipes are fixed, we should be closing the taps.

An objectives-and-accountability perspective

The Indian State is in a crisis. The two key factors at work are mission creep and a lack of accountability.

Mission creep has set in because in India, almost any do-gooding is seen as the responsibility of the State. We need to narrow the mission statement of the State to a tangible set of public goods. Clarity of mission, and a controlled and narrow mission, is of essence to obtaining performance.

Consider the principal-agent relationship between you and your contractor. If the contractor is failing to deliver, you would narrow down the specifications given to him, and monitor him tightly to make sure the work gets done. That is precisely what we need to do, in the principal-agent relationship between citizens and the State. The State has failed on a sprawling mission. We need to narrow down the tasks given to the State, and tightly monitor the delivery of results.

Government and government agencies will work well when they have narrowly defined functions and strong accountability mechanisms. In the field of health, absent measurement of health outcomes, there is no accountability.


Is there a Dengue epidemic in India? We don’t know.

An information system about the health of the people of India is a public good. It should achieve pride of place in the responsibilities of the State. However, health expenditures in India are squandered on private goods. To add insult to injury, there is theft and incompetence, so even these attempts at delivering private goods do not work so well. But the main point is that running PHCs and hospitals should not be done, even if the Indian State had the ability to run these things well.

In order to reconstruct the Indian State, we need to push on the combination of narrowing the mandate (focusing on a few core public goods) and strong accountability mechanisms.

Rethinking the Statutory Liquidity Ratio (SLR) in Indian banking

by Harsh Vardhan.

The CEO of a leading bank recently caused a flutter in the banking community by demanding the abolition of the Cash Reserve Ratio (CRR). RBI has promptly appointed a committee to look at this issue. The reserve ratios, CRR and SLR (Statutory Liquidity Reserve), are an important feature of Indian banking regulation. Alongside the debate about CRR, and new thinking about how monetary policy should be conducted, we should also review the SLR. SLR is a much bigger burden on the banking system and has no role in monetary policy.

What is SLR?

SLR is the requirement imposed by the regulator on commercial banks that compels them to invest a percentage (currently 24%) of their Net Time and Demand Liabilities (NDTL) in approved government securities. Through this, today, 24% all the resources – deposits and borrowings – mobilised by commercial banks are invested in government securities. Currently bank deposits and borrowings are Rs.7 trillion which means that SLR places Rs.1.8 trillion into purchases of government securities. SLR creates a significant captive source of financing its borrowing program. This has three important implications:

  1. SLR reduces the resources available for commercial lending by banks. Every rupee deployed in SLR is a rupee not invested in a private enterprise that needs capital. There is no free lunch: when capital given to the government, it comes at the cost of capital available to the private sector. Any reduction in the SLR (as in the CRR) will yield more capital for the Indian private sector. It is hence important to critically analyse both.
  2. By creating a large captive source of deficit financing, SLR effectively subsidises government at the cost of savers and commercial borrowers. When a government has to borrow at a competitive rate in the market, the market exerts a check on irresponsible fiscal behavior of the government. When there is a large captive source of borrowing, the government is shielded from the pressures of the bond market and is more likely to engage in fiscal imprudence.
  3. Such a large scale preemption of savings by the government through SLR fundamentally distorts the interest rate structure in the economy by artificially depressing the yield curve. This complicates the pricing of all assets in the economy.

If we want to “right-size” SLR we have to ask some important questions:

  1. What is the rationale for imposing SLR?
  2. What is the right level of SLR, that is consistent with this rationale and does not result in preemption of resources from the banking system?
  3. Are there other conditions that need to be imposed on SLR so that it achieves the objectives?

The rationale for SLR

What is the conceptual foundation for the regulator to impose SLR? The answer is: prudence. Banks raise public deposits with a promise to redeem them at par or more. To reduce the risk of the portfolio of the bank, the regulator ensures through SLR that at least some part is deployed in the safest assets available. But if prudence is the reason, what is the right level of such reserves that will ensure adequate prudence? Could it be that imposing a requirement as high as 24% is beyond prudence, and is actually a means for the government to preempt savings in the economy? It is hence important to ask the next question: What SLR do we need?

What is the right level of the SLR?

Banks are in the business of taking risk. These risks are taken by deploying public deposits. The most potent weapon that the regulators have used against excessive risk taking is “risk capital” which the equity capital committed by the banks owners. In fact, the entire edifice of modern day bank regulation is based on provision of risk capital as a buffer against risk taking by banks. If we believe, as do most regulators, in risk capital as the buffer against risks, then it makes eminent sense for banks to hold this capital safely. This would logically lead us to conclude that prudence should demand that the bank’s risk capital be held in very safe assets. In India, the risk capital requirement is 9% of risk assets which translates roughly to 6.5% of NDTL (given that the risk assets are typically 70% of NDTL). Therefore, the policy prescription should be: Banks must hold their entire risk capital in safe assets which should include both CRR and SLR.

Even if we assume the CRR is zero, this means that the theoretically right level of SLR would be around 6.5% of NDTL. If we scan the international landscape, this is the sort of number that we see in most countries. It is reasonable to argue that an SLR value above 6.5% of NDTL is motivated by pre-emption and not prudence. When the regulator prescribes a level of 24% for SLR, 6.5 percentage points are for prudence and the remaining 17.5 percentage points is really preemption by the government.

The composition of SLR

The next important question about SLR is about its composition – what investments should qualify as SLR investments? Currently securities issued by the sovereign (Central and State Government bonds) are the only ones that are allowed as SLR investments. But if we accept prudence as the logic for SLR, then the regulation must make sure that these investments are as safe as they can be. This raises concerns about the rating threshold and of concentration risk. If Indian government securities are rated BBB and that of New Zealand government are AAA, it makes sense for banks to hold SLR in New Zealand Govt securities. Also, there should be limits on any individual issuer of securities, reflecting the standard risk management practice followed by any portfolio manager.

The ideal SLR

Putting all the arguments above provides us an ideal construct of SLR as follows:

  • SLR is imposed for the purpose of prudence and hence the operative principle is that banks should hold all the regulatory required risk capital in SLR
  • The level of SLR should be consistent with the objective of prudence and anything over such a prudential level should be considered as preemption, which should be gradually eliminated.
  • SLR should be invested in top rated securities available globally; furthermore there should be concentration limits on single security and issuer

Dual limits structure for SLR

In the short term, it would be hard to come close to the ideal SLR outlined above. But there are some incremental changes that can be made without fundamentally altering the current framework that could provide banks with much greater flexibility. The regulator could prescribe 2 separate limits as follows:

  • L1: is the minimum level of SLR that a bank would normally maintain
  • L2: “core” SLR – a minimum below L1 that the banks can go down on SLR as long as the difference is only through repo arrangement on SLR with another bank

What does this mean? Let us assume that L1 is pegged at the currently prescribed level of 24%. We then define another limit, L2, which is closer to the prudential requirement of 6.5%. For simplicity, let us assume that L2 is set at 10%. This policy would demand that all banks maintain SLR at 24% but could go down this level upto 10% if and only if they enter into a repurchase agreement (repo) with another bank. Such a policy will mean that the banking system as a whole will continue to hold 24% SLR and so the government will continue to have access to this captive source of funding deficit. However, individual banks would be able to go down to lower levels if they have commercially viable opportunities to do so. Without diluting the overall investment by the banking system in government securities, it would provide significant flexibility to individual banks on commercial lending. In this respect, it is analogous to the idea of tradeable certificates for priority sector lending.

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Preventing shocks or becoming resilient to them?

My previous blog post, on not cancelling trades after a fat finger trade, elicited some interesting email conversations. In a nutshell, there are two views of the world. One camp argues that it is important to prevent fat finger trades and other such weird episodes. This requires building an array of preventive measures. The other side argues that the costs of prevention are high, and what’s really important is to make a resilient market that is able to absorb shocks.

Prevention is difficult for two reasons:

  1. NSE and BSE are some of the biggest exchanges of the world. We should be pleased that India has two of the great factories of the world doing order matching. But as a side effect, NSE and BSE are at the limits of what today’s CPUs can do. Many, many orders are placed, compared with the number of trades. Pre-trade checks are expensive because the number of orders is high. Fairly trivial notions of pre-trade checks can triple the hardware requirements or worse. We have to ask ourselves: Is it worth driving up the cost of transacting by 3x or 5x or 10x in order to do those checks? In addition, pre-trade checks introduce delays (”latency”) which are not good for the trading process. When an order is placed, the person wants an instant confirmation that it was placed into the order book and ideally matched. More work in screening orders before the trade increases the latency suffered by traders. This, in turn, increases the risk faced by various trading strategies, which has adverse implications for market liquidity and market efficiency.
  2. What validation rules would you write, pre-trade? There is a danger of fighting the last war. New kinds of problems will inevitably surface in the future. Will we keep on increasing the burden of pre-trade computation, over the years, as the list of potential difficulties goes up through time?
There is a shades-of-gray dimension here. It appears obvious to us that if a computer program is buggy, and puts in a wrong order, this should be blocked. But what when a man-machine hybrid (the typical human trader that operates a computer) makes a mistake? What about a pure human trader that makes a mistake (e.g. saying on the phone “buy me 25 million shares of Infosys” when he meant “buy me 25 million rupees of Infosys”)? Where do you draw the line?
It is better, instead, to see that mistakes are an inevitable part of financial markets. I would argue that pre-trade computation should be kept to the bare minimum, and that it is instead important to focus on deeper initiatives that will make the market more resilient. We need more eyeballs, more capital, more limit orders, more arbitrageurs, more algorithmic trading, more short selling. This is what will make the market resilient. A resilient market is one that is ready to accept a diverse array of unpredictable shocks in the future. Until a few weeks ago, we never imagined an order for 17 lakh nifties could be placed. The market did well in absorbing this completely unanticipated shock. The market should be a flexible, intelligent, resilient construct that is ready for all sorts of unexpected events of the future.
Some people say: “We should put in infinite expenses in order to screen orders”. This reflects a lack of  economic thinking. The strategies of prevention and cure need to be evaluated from a cost/benefit perspective. Each features tradeoffs. Driving up the charges of an exchange by 3x to 10x, and increasing the latency suffered by every market participant, is a big cost. This should be weighed against the benefits.
I am reminded of a great story told by the Chilean economist Raimundo Soto at a NIPFP/DEA Conference in 2009. He started by describing a cautious 80-year old person, who is very careful about what he eats, who avoids stepping out of the house, and so on. He stays alive, but is perennially afraid that a small sickness will bring him down. And, indeed, when one small common cold comes along, it can have catastrophic consequences for him. Compare this with a 15-year old prancing around the world, tumbling in the dirt, taking risks, and living a great life. He is exposed to many illnesses, but rapidly bounces back from each of them.
Raimundo Soto said that the analysis of capital account convertibility should be rooted in the desire to become this 15 year old rather than this 80 year old. We should be asking: How can the system be made more resilient to shocks? We should not aspire for a Chinese Wall of capital controls that cuts India off from the global financial system; instead we should be doing the things that make India resilient to international shocks – such as develop a sophisticated Bond-Currency-Derivatives Nexus.
In similar fashion, too much of the conversation in India, after the Emkay fat finger trade, is about asking How can such shocks be prevented? I think we should aspire to be like the 15 year old and not like the 80 year old. The really important question is: How can the system be made more resilient to such shocks?

Cancelling trades on an exchange: When is it a good idea?

When inexplicable things happen on an exchange, many people argue that those trades should be cancelled. I think it is useful to be clear about the test to apply for this.

The key question should be: Did something foul up in the order matching software? If order matching went wrong, or if there was a systematic breakdown of connectivity to the exchange, then there is a case for cancelling trades. We’d say that persons placed certain orders, but the exchange mis-handled the orders, hence the observed series of matched trades and prices is unfair.

If the exchange and its rules worked as advertised, this reason peels away. In fact, I would argue that particularly when there is a fat finger trade or something like the US `flash crash’, it is important to not cancel trades, to cement faith in the trading process.

The recent events surrounding the fat finger trade by Emkay are a good example of this line of thought. Owing to a human error,  a basket trade to sell Rs.17 lakh of Nifty was instead placed as an order  to sell 17 lakh nifties (where one `nifty’ is a basket of 50 shares adding up to the present level of the Nifty index expressed in rupees). If Nifty is at 5000, then an order for “100 nifties” is an order for Rs.500,000.

Through this human error, a very large sell order appeared on the market. At that instant, everyone looking at the market would have been taken aback. What was going on? Has a huge event unfolded which some informed speculator knows about, but I do not know about? It takes nerve in that moment to be on the other side of the order. We must reward the people who did not lose their head when everyone around them was losing theirs.

When the big Emkay order came in, many of the orders which were matched were limit orders which had been patiently waiting there. This does not, in any way, change the analysis. Waiting with `deep out of the money’ limit orders is a hazardous business. As an example, consider the persons waiting with deep out of the money limit orders, standing ready to buy at very cheap prices (e.g. 10% below the current market price) when the Satyam scandal unfolded. They lost money big time because the informed speculators, who understood the Satyam announcement and placed massive market sell orders, knew more than them. Waiting patiently with limit buy orders, 10% away from the touch, is not free money. (”The touch” is finance parlance for the bid and the offer price). It is a risky trading strategy.

Two trading strategies matter most in stabilising a market when crazy things have happened. Traders  have to be there ahead of time, with limit buy orders far away from the touch. The limit order book should be thick with orders; i.e. the impact cost associated with a giant market order should be low. And there have to be traders who see that the market has crashed, are able to work the phone and gain confidence that this is an idiosyncratic shock, and come into the market and buy. The more the capital and intelligence behind such trading strategies, the more stable the market will be.

If trades are now cancelled, these two trading strategies will have suffered the risk and got nothing in return. In the future, they will be more circumspect about stabilising the market. Similar considerations apply on the other side. When there are strange and large upward moves of the market, we want rational speculators who short sell and bring the price back to fundamentals. The market must be designed in a way that supports and enables this. At present, it is not [link, link].

Fat finger trades will happen. There will occasionally be strange rumours and other odd things that will make markets fluctuate away from fair price. In those situations, what we want most is for clear-headed rational speculators to put large scale capital into making money by stabilising the market. The rules of the market should reward the people who perform these roles. Trades from their orders should not be cancelled.

The Emkay story has gone well for the Indian securities markets. The market design worked as it should have. A human error was made, there was a brief market-wide suspension on the equity spot market (but the futures market continued to work). A call auction took place to discover the price, and within minutes everything came back to normal. Emkay took full responsibility for their trades and came through with the money. We shouldn’t stumble in the policy analysis that follows this story.