The effect of Basel 3 and other bank regs...Winners and Losers

The net effect of all these regs to discourage financial innovation, increase capital and liquidity costs, encourage consolidation based on scale economies, discourage moves to universal banking based decreased scope economies, encourage moves to lower tax regimes (mainly in the east), discourage securitization, discourage otc derivs, encourage exchanges and CCPs, increase risk management especially CCR and MR, encourage collateralization, make trading books smaller, banking books bigger, increase demand for ops efficiency,increase reg arbitrage, increase compliance and reporting costs, discourage alternative assets.

Moral Hazard is a wonderful thing! NOT.

Moral Hazard is a wonderful thing! Part of the fundamental role of regulatiom is to avoid it, and yet in our increasingly short term world, politicians and voters alike are unwilling to take short term pain for a long term benefit. Like letting some of these companies pay the price of poor liquidity risk management. Even liquidity/capital injections just make the problem more trenchant the next time. Sometimes i think that risk management only works against a stable context, some lender or provider of liquidity of last resort, a government, an insurance company, and IMF, and without it the network of relationships crumbles. As institutions get bigger and more global, there is no longer some JPMorgan in the background ready to bail out the system. Perhaps this suggests too big to fail really is just too big...

Proprietary trading at federally insured banks

I have never really bought into the need for proprietary trading at federally insured banks. The ugly undisclosed truth is that most banks have no competitive advantage in much of their trading activities, if these operations were evaluated on a risk adjusted basis, they would be, and have been, value destroying. If truly private institutions want to do this that's between them and their shareholders, but when public guarantees are made, then the government has a responsibility to intervene. Moral Hazard is alive and well. Banks like the rest of us, delude themselves into believing short term gains are indicative of internal competence. In a somewhat efficient market, most of us have beta but alpha is and will always be a rarity.

Technocrats vs Politicians Round 1...

The world of bank regulation is being torn between two very different agendas. First, the technocrats of Basel, as they struggle to put in place amendments to the comprehensive version (June 2006) that has formed the bedrock of much market and credit risk management thinking for the past few years. BIS has introduced a host of new consultative documents, subject to ratification, that promise significant increases in the levels of regulatory capital and liquidity particularly for the trading book. Initiatives like the stress var calculation, the calculation of an incremental risk capital charge for users of internal models for specific risk, counterparty credit risk capital increases, the Liquidity Coverage Ratio, the Net Stable Funding Ratio and the Leverage Ratio, all proffer band aids to weaknesses in the original accord. The danger is that the technocrats responding to real issues in the original accord lose the "high ground" and surrender the two principles that made Basel II such an innovation - capital is alligned with risk, and the better the job we do of measuring risk the lower the capital charge. Unfortunately the "band aid" approach understandable as it is, risks making an already highly complex set of regulations, conflicting, opaque and even more open to the regulatory arbitrage that brought down its predecessor - Basel I.

So not surprising therefore is the new found emphasis on the agenda of the second group of actors in this drama - the politicians. They are reacting to market and economic crisis, and selling their approaches to an angry and impatient tax paying public. Here initiatives are basically four fold. In the US, a raft of initiatives have been proposed by the Obama government, in general limiting the scope and the size of federally insured bank activities. The real challenge of all these initiatives is of course congress, where well funded lobbyists may easily derail the worst vicissitude of the proposals. The UK has taken a different approach, experimenting with macro prudential regulation an structural regulatory change, but they face two different challenges - increasing regulation yet not killing the Golden Goose of the City that sustains a sizable chunk of the UK economy. Added to which is the upcoming election which may endanger any initiative. The EU has been hamstrung by government deficits in certain member countries and has revealed just how hard it is get cross the board agreement in such national sensitive economic issues. Finally enter the G20 and the IMF, frustrated at the lack of regulatory changes a full year after the crisis, has argued for the simplest, but possibly most destructive approach of all, bank taxes based on the size of liabilities.

So whose constraints will determine the future of banking for the next ten years? I vote for the politicians - but it will further push financial innovation to the east and away from established financial centers.

On having multiple discount functions

Another interesting development in the world of Behavioural Finance is the idea that individuals have multiple discount functions. For example, researchers such as Prof David Laibson argue that we have at least 2 discount functions, one for the very short term say minutes, hours, days, and then another for the longer term. The tension the investor faces is the tradeoff between these two. For example, simple exponential discount functions argue that the change in  discount rate is more or less constant over time. Yet consider this thought experiment - imagine you were given two sets of choices 1) a) $100 now or b) $101 in 60 mins from now and 2) a) $100 in 1 week or b) $101 in 1 week and 60 mins. Almost everyone will choose 1a and 2b but this is not consistent with a simple discount function. The attraction of the immediate is overwhelming for most people, percieved as far more beneficial than any delayed extra value. Yet beyond the immediate people switch to a more rational process incorporating the extra delayed benefit. Its as if they have two discount functions, one that kicks in for the near term, emphasizing short term benefits and the second which is used to evaluate longer term costs and benefits. Even more fascinating some researchers are arguing that these discount functions actually correspond to different more or less developed parts of the cerebral cortex, associated with high level reasoning and more emotional animalistic instincts. But these discount functions are not merely quantitatively different, they seem to be qualitatively different too. For example, when you change the reward, say to ice cream or a candy bar, the short term benefits even more massively outweigh longer term benefits.

Of course, marketing people instinctively know these things we suspect, the offer of the free ipod when you sign up for a new credit card, peoples tendancy to spend hours negotiating on physical aspects of a car purchase, and then only a moment to decide whether to get auto financing (which is where most of the profits are made).

So what is the punchline - real physical things obtained immediately are valued much MUCH more than abstract non physical things delayed.

What do probabilities mean to people? The Cost of Certainty

One of the most interesting notions in Prospect Theory, is the idea that individuals really don't understand probabilities. That is they make little distinction between similar probabilities (say the difference between 0.25 and 0.3) and treat them essentially the same. However that is not true at the extremes, we seem to have a cognitive bias in favor of zero and 1 as absolute certainties. Yet ironically, absolute certainties are never the case. Mathematically this is described as a weighting function that converts quantitative probabilities into qualitative weights - using a function like the following:

So basically we underestimate probabilities when they are slightly less than 1 and overestimate them if they are slightly more than zero. What does this mean for finance? Well, people will pay more to receive contingent cashflows which are very unlikely because they will overstate the actual probability. This is part of the attraction of lotteries - although the probability is small, there is a small probability of success and that makes all the difference. Similarly investors will heavily discount cashflows that are not absolutely certain.

Prospect Theory and what it means for economics

Traditional Economics is based on the notion of a utility function which increases as a concave function) with increasing levels of wealth. Our decisions as economic actors therefore boil down to selecting the option that generates the highest expected utility. But ask yourself this, faced with a fair one off gamble in which you might make 2000 dollars or you might lose 1000 dollars, what would you do? Most people would choose not to gamble even though the expected utility will be positive. Why? Note that this is not true if we were able to play the game say a thousand times - in which case almost everyone will take the bet.
Behavioral theorists suggest this unwillingness to take the single bet is because we care about losses more than gains, counter to the principles of traditional utility theory, and so have posited a prospect theory that charges a greater value loss for losses in current wealth that for gains. If you like, the utility function is "kinked" around the current level of wealth.

Most of financial markets are based on a zero sum game. Consider a structured product. If I win, you must lose and vice versa. Financial engineering can only add value to such transactions by exploiting the differences in the preferences of the transactors. For example by emphasing the elements of the transaction that most appeal to the other side, say high returns, or delayed payment, or low risk. Being a zero sum game, these elements are paid for by subtracting from aspects of the transaction that the counterparty does not care so much about, like operational complexity, or like risk.  Value is created from the transaction (but not utility however) if the structure reflects the differences in the counterparties wants and needs. Prospect theory  acknowledges that value is inherently client specific (it depends on their reference point for example), and that financial product design is really about understanding behavioral biases in order to better align. So is Prospect theory purely descriptive while Utility theory is normative? Should we give up structured products because they pander to our cognitive weaknesses? Although Prospect theory is partly descriptive, it is also normative. Other counterparties have cognitive biases too, and we must interact with them, so it behooves us to understand and acknowledge these biases/limitations/constraints in our transactions with them.

Models and Overconfidence

Whether a scientist, or a financial engineer, when we invest in an idea, a model, a way of thinking, by definition, we believe it to be an accurate representation of the world, and so interpret new information in terms of this model. New information that is consistent with this model makes us more confident in its use, while new conflicting information is often regarded as spurious, exceptional or irrelevant. The model provides us with an anchor, and biases us away from alternatives.  We protect our models from the world of evidence, in the same way we protect ourselves, no surprise here, as in some sense these models constitute ourselves. The models change only with crisis, some overwhelming surge of evidence that cannot be ignored. Ironically, financial models, (unlike models of physics) when broadly and consistently acted upon, will often build up arbitrage and economic pressures in the market to break the models. So no one can see the breakdown coming, everyone is shocked when it does happen, and yet everyone can rationalize after the fact why the crisis occured.
Perhaps the truth is that reality is more complex than we can ever know, and like a good buddhist, all we can do is acknowledge and respect the complexity that we face, realizing like the quantum physicist, that the act of understanding the world, also changes it into something else.

The Curse of Overconfidence and some revealing party tricks...

Irving Fisher, probably the greatest american economist of his generation (most known for his theory of interest rates), remarked famously just before the great crash of 1929 that "Stock prices have reached what looks like a permanently high plateau". To be fair, he put his money where he mouth was, and invested much of his assets in the stock market. Soon after he was broke, and had to sell his home in NewHaven Connecticut to pay his debts (fortunately his university bought his house and let him live there, or he would have been destitute!). Even after his experience, he continued to argue that he had been right.
The curse of overconfidence is not unique to economists, indeed one of the major trends in new economic thought is behavioral finance, applying all of social science theory to finance, not just economics. And one the cornerstones of this theory is that people are overconfident, inconsistent, lazy, and simply stupid at times. In short, not the "homo economicus" of classical theory. Consider one's own overconfidence - ask yourself or your friends to define a 90% [lower,upper] range for answers to the following questions (no cheating!), and find out if you indeed tend to get 9 out of 10 them right.

1. What is the population of Turkey?
2. What is the weight of the Empire State Building? (tons)
3. What is the GDP of Australia?
4. How many cells in the human brain?
5. How likely is it that you will be struck by lightening this year?
6. How many bibles are there in the world?
7. How many children will die of malnourishment in the world in the next day?
8. How likely is it that you will be in a plane crash this year?
9. What is the likelihood of a asteroid hitting the earth in the next year and destroying all life on the planet?
10. What is the likelihood of a AAA bond defaulting in the next year?

 Answers (no peeking)

1. 72,561,312 as of 1st January 2010
2. 365,000 tons
3. $1 trillion USD
4. 100 billion
5. 1/750,000
6.  6,000,000,000
7. 3000
8. 1/675,638
9. 0.00000002
10. 0.1

Most people (assuming they play fair) get significantly fewer than 9 out of 10 of these questions right. They believe the world is less complex and better understood than it actually is, and this influences their behaviour. Unfortunately sometimes with disasterous results - i am reminded of the quote from Larry Kersten, an american sociologist that "before you attempt to beat the odds, be sure you could survive the odds beating you.”

 

 

Moves to increase transparency in the OTC market

It’s clear that the juggernaut of transparency will be hard, if not impossible to resist. And this is generally a good thing for most derivatives users, even in sophisticated markets like the US. For far too long, OTC derivatives have hidden risk and complexity from users and regulators under the guise of “customization”, providing much value to product innovators but little real value to end users. Eventually, the essentially one-sided nature of much of this technology will be revealed. However, the real risk is that the pendulum will swing too far in the opposite direction, preventing even sophisticated end users laying off their risks with bilateral contracts. Part of the limitations of such a one-sided response is the assumption that transparent markets are a cure-all. They are not. Transparency is about having a information baseline against which all transactors in the market can make their decisions. However derivatives information does not necessarily equate to knowledge or expertise in derivatives product use. All the information in the world does not create an adequate valuation or hedging model, and even less does it create an understanding of the limitations of the valuation models used.
So Regulation should increase transparency of transactions, but it should also target the expertise of potential counterparties. Some institutions (much like non qualified investors) should not be transacting with counterparties if the expertise imbalance is simply too great. And frankly given the huge investments financial services have made in financial engineering human capital, this may often be the case.

The Rise of Collateral and the Urgent Need for Collateral Risk Management

The downturn has clearly pushed Collateralization to the fore of OTC derivatives, repos and securities financing. What was often viewed as a luxury, is now seen as a necessity as counterparty risk is not confined to low rated entities (sic. Lehmans!). But the rise of collateralization does not destroy the problem faced by counterparties. Collateral may increase some business opportunities but it also converts counterparty credit risk into operational and legal risks and into residual market and residual credit risk. This new bundle of risks is certainly different from what was held before and arguably is more complex. Consider Operational Risk is implied in everything from reconciliation to posting collateral with a custodian, from collateral valuation to settlement. Legal Risk is endemic to the OTC derivatives space and is of course the rationale for the various master ageements (ISDA, GMRA etc) and associated credit annexes, many of which remain to be tested in emerging markets legal jurisdictions. Residual Risk always remains, whether it be from market risk - the changing value of the collateral, or the changing risk sensitive margins, or even reinvestment risk; or from credit risk - wrong way risk - the possibility of correlations between counterparty default and collateral values. In short, collateralization is a good thing, one to encourage, provided one realizes that risk is not removed, merely converted into another form. And these new risks must be managed if collateral is not to give a false sense of security in these turbulent times.

The coming Pension Fund Crisis and how it will change the world

The next big thing, after the sovereign debt crisis that is slowly percolating through the financial system, is the pension fund crisis. Basically the problem is that public and private pension funds across the world have long managed their balance sheet as two independent elements - assets and liabilities and the concept of ALM has never been accepted or acknowledged within the industry. Liabilities - the pensions themselves, very much managed as an actuarial portfolio, usually based on the demographics of a particular fund and its covered employees is best thought of as a set of zero coupon bonds with limited optionality, the duration of which reflects the average life expectancy of the average insured individual. This of course varies by pension plan, and no surprise therefore that the asset side, the funding of these liabilities must depend on a detailed analysis of the cash flows associated with these liabilities. In short we need to build a replicating portfolio for the liabilities (just like in Bank ALM) and use that to define the performance expectations of the asset portfolio. This is rarely done - instead pension funds use fund of funds to "divide and conquer" the asset portfolio and evaluate that performance on existing standard market benchmarks for bonds, equities and other assets. But of course, performance for a pension fund means the ability to fund the liabilities, it does not mean the ability to outperform a bond index like the Barclays Capital Aggregate Bond Index - which is typically industry practice. Analysing risk for a pension fund means analysing the risks to achieving performance, in other words, how likely is it that our asset portfolio will underperform the liability portfolio. With a liability replicating portfolio, we can build var and shortfall models that allow us to monitor and manage the net asset position over time. The lack of this capability is not merely a problem for a few pension funds. The mismatch of mark to market values of asset and liabilities in corporate pension funds is of the order of trillions (yes - trillions) of dollars in the US alone (UK, Russia, Italy also big problems). If there is continued fall in the value of equities this is likely to get worse, and be a drain on corporate performance for years to come.

What does it mean to hold a diversified portfolio?

Imagine we have a portfolio of equal positions in different securities? Is this diversified? Probably not. What if these securities were all bonds with small volatilities, and one equity position with a much higher volatility - that clearly would not count as properly diversified. So individual security variances need to be considered when thinking of diversification. What about correlation? This too should be included. The best measure of diversification probably considers the contribution of the pieces to the overall variance of the portfolio. But a complication here is that variance is not additive - so instead we often talk of factor variances, calculated based on some form of Principal Component Analysis (PCA) - basically computing the eigenvectors of the original covariance matrix in order to produce orthogonal risk vectors (whose variances are then additive). Having PCA risk factor variances then allows us to estimate the cumulative contribution of different securities to aggregate variance starting with the greatest factor contribution. Much like a Pareto Analysis, we ask how different is the actual contribution to perfectly diversified case - a straight line, and this gives us a robust measure of diversification.

Socialism and Risk Management

So what does socialism have to do with risk management? Everything! Socialism, whether it is in the form of a kibuttz, or Robert Owen's New harmony, or Karl Marx's Communism, is ultimately about the provision of a safety net for all workers. High but unequal and uncertain levels of income are sacrificed for equality. Or to put more poetically in the words of Marx, from each according to his ability, to each according to his need. It is a form of risk reduction based on pooling of risks and of resources. Much like social security or insurance, it works because individual losses (and gains) are shared across a wider population. And of course losses are usually feared more than gains are valued, so such insurance is deemed to have value. The problem with such socialism (and for that matter, communism and insurance) is moral hazard. The old Soviet joke "we pretend to work and they pretend to pay us" captures it all. Moral Hazard is endemic to risk sharing particularly when the potential outcomes are partly under the control of the individuals themselves. The fire insurance that encourages arson, the seatbelts that encourage fast driving, the federal deposit insurance that discourages due dilligence in banks. Most of political philosophy is actually an extension of this idea, the production and the distribution of resources in an uncertain world. Unfortunately our positions on such political ideas are usually coloured by our current states, and the inherent moral hazard associated with that state as we try to game the system for our personal benefit. Philosophers like John Stuart Mill, Rawlings have said much the same from the liberal tradition.Howver even some conservative thinkers, particularly communitarians, have realized that we are part of a society and our survival as individuals depends on our building networks that share opportunities and risks within that society.

Counterparty Risk Management - Best of times? Worst of times?

It was the best of times. It was the worst of times...Stealling a few classic lines out of Dickens' "A tale of two cities" is apropos for today's post - the new demand for counterparty credit risk management and collateralization. The best of times for counterparty credit risk? Not a surprise that the crisis has made all and sundry realize that highly rated counterparties such as Lehman Brothers can default, and in turn has push counterparty credit risk to the top of the agenda for risk managers and regulators alike. BCBS in particular is pushing for incremental risk capital charges for traded credit (including counterparty credit risk) and is increasing incentives for centralized counterparties and collateralization as a means to significantly reduce counterparty credit exposures. Nor are the regulators comfortable with banks' or the rating agencies ability to track counterparties PDs proactively. So naturally the focus on counterparty credit turns to exposures management through techniques like mark to market valuations plus addons or even potential future exposures. Although arguably more representative,the latter is a major computation challenge for many institutions requiring huge monte carlo simulations over long time periods. Not surprising therefore, that enterprise collateral management is the flavor of the month in counterparty credit risk circles.

But is it the worst of times? The same regulatory pressures have discouraged many from otc derivatives and securities borrowing/lending particularly in the developed world. In Asia by contrast, OTC derivatives do have the same stigma they have in the US and Europe.