Xenomorph Blog - Hedge Funds

Posts categorized "Hedge Funds"

PRMIA - Operational Risk, Big Data and Human Behaviour

I attended Challenges and Innovations in Operational Risk Management event last night which was surprisingly interesting. I say surprising since I must admit to some prejudice against learning about operational risk, which has for me the unfortunate historical reputation of being on the dull side.

Definition of Operational Risk

Michael Duffy (IBM GRC Strategy Leader, Ex-CEO of OpenPages) was asked by the moderator to define Operational Risk. Michael answered that he assumed that most folks attending already knew the definition (fair comment, the auditorium was full of risk managers...), but he sees it in practice as the definition of policy, the controls to enforce the policies and ongoing monitoring of the performance of the controls. Michael suggestion that many where looking to move the scope and remit of Operational Risk into business performance improvement, but clients are not there yet on this more advanced aspect.

Vick Panwar (Financial Services Industry Lead, SAS) added that Operational Risk was there to mitigate the risks for those unexpected future events (getting into the territory of Dick Cheney's Unknown Unknowns which I never tire of, particularly after a glass of wine).

Rajeev Lakra (Director Operational Risk Management, GE Treasury) took his definition from Basel II of Operational Risk as risk of loss resulting from inadequate or failed internal processes, people and systems, or from external events. Coming from GE, he said that he thought of best practice Operational Risk as similar to another GE initiative in the use of Six Sigma for improving process management. Raj said that his operational risks were mainly concerned with trade execution so covering data quality/errors, human error and settlement errors.

Beyond Box Ticking for Operational Risk

Raj said that Operational Risk is treated seriously at GE with the Head of Operational Risk reporting into the CRO and leaders of Operational Risk in each business division.

Michael suggested that the "regulators force us to do it" motive for Operational Risk had reduced given some of the operational failures during the financial crisis and recent "rogue trader" events, with the majority of institutions post-2008 having created risk committees at the "C" level and being so much more aware of tail events and the reputational damage that can damage shareholder value.

Vik said that Operational Risk is concerned primarily with "tail events" which by definition are not limited in size and therefore should be treated seriously. Pragmatically, he suggested that "the regulators need it" should be used as an excuse if there was no other way to get people to pay attention, but getting them to understand the importance of it was far more powerful.

The "What's in it for you" Approach to Operational Risk

Raj emphasised that it was possible to emphasise the benefits of operational risk to people in their everyday jobs, explaining to operators/managers that if they get frustated with failures/problems in the working day, then wouldn't it be great if these problems/losses were recorded so that they could justify a process change to senior management. He emphasised that this was a big cultural challange at GE.

Michael suggested that his clients in financial markets had gone through risk assessment, controls and recording of losses, but had not yet progressed to the use of Operational Risk to improve business performance.

Duplication of Effort

A key thing that all the panelists discussed was the overlap at many organisations between Operational Risk, Audit and Compliance. The said that the testing of the controls used for each had much in overlap, but was not based on a common nomenclature nor on common systems. For instance Vik pointed out that many of the tests on controls in Sarbanes-Oxley compliance were re-usable in an Operational Risk context, but that this was not yet happening. Vik said that this pointed to the need for comprehensive GRC platform rather than many siloed platforms.

Michael said that regulators want an integrated view, but no institution has an integrated nomenclature as yet. He recounted that one client sent 12 different control tests to branches that needed to be filled in for head office, which was a waste of resources and confusing/demotivating for staff. Raj said that the integration of Audit and Operational Risk at GE had proved to be a very difficult process. All agreed that senior management need to get involved and that a 5 year vision of how things should be incrementally integrated needs to be put in place.

Audience Questions:

Is business process risk different to business product risk? Michael said that Operational Risk certainly does and should cover both internal process and also the risks produced by the introduction of a new financial product for instance (is it well understood for instance, do clients understand what they are being sold?). He added that Operational Risk encompassed both the quantitative (statistical number of failures for instance) and the qualitative for which statistics were either not available (or not relevant to the risk).

Are there any surrogate measures for Operational Risk? Here a member of the audience was relaying senior management comments and frustration over the stereotyped red/amber/green traffic lights approach to reporting on operational risk. Michael mentioned the Operational Riskdata eXchange Association (ORX) where a number of financial institutions anonymously share operational risk loss data with a view to using this data to build better models and measures of operational risk. Apparently this has been going on since 2003 and the participants already have a shared taxonomy for Operational Risk. (my only comment on having a single measure for "operational riskiness" is that do you really want a "single number" approach to make things simple for C-level managers to understand, or should the C-levels be willing to understand more of the detail behind the number?)

Is "Rogue Trading" Operational Risk? Michael said that it definitely was, and that obviously each institution must control and monitor its trading policies to ensure they were being followed. The panel proposed that Operational Risk applied to trading activity could be a good application of "Big Data" (much hyped by industry journalists lately) to understand typical trading patterns and understand unusual trading patterns and behaviours. (Outside of bulk tick-data analysis this is one of the first sensible applications of Big Data so far that I have heard suggested so far given how much journalists seem to be in love with the "bigness" of it all without any business context to why you actually would invest in it...sorry, mini-rant there for a moment...)

Summary

Good event with an interesting panel, the GE speaker had lots of practical insight and the vendor speakers were knowledgeable without towing the marketing line too much. Operational Risk seems to be growing up in its linkage into and across market, credit and liquidity risk. The panel agreed however that it was very early days for the discipline and a lot more needs to be done.

Given the role of human behaviour in all aspects of the recent financial crisis, then in my view Operational Risk has a lot to offer but also a lot to learn, not least in that I think it should market itself more agressively along the lines of being the field of risk management that encompasses the study and understanding of human behaviour. Maybe there is a new career path looming for anthropologists in financial risk management...

Posted by Brian Sentance | 27 January 2012 | 11:30 pm

The Volcker Rule - aka one man's trade is another man's hedge

One of the PRMIA folks in New York kindly recommended this paper on the Volcker Rule, in which Darrell Duffie criticises the proposed this new US regulation design to drastically reduce proprietary ("own account") trading at banks.

As with all complex systems like financial markets, the more prescriptive the regulations become the harder it is "lock down" the principles that were originally intended. In this case the rules (due July 2012) make an exception to the proprietary trading ban where the bank is involved in "market-making", but Darrell suggests that the basis for what types of trades are "market-making" and what types of trades are more pure "proprietary trading" are problematic in this case, as there will always be trades that are part of "market-making" process (i.e. providing immediacy of execution to customers) that are not directly and immediately associated with actual customer trading requests.

He suggests that the consequences of the Volcker Rule as it is currently drafted will be higher bid-offer spreads, higher financing costs and reduced liquidity in the short-term, and a movement of liquidity to unregulated entities in the medium term possibly further increasing systemic risk rather than reducing it. Seems like another example of "one man's trade is another man's hedge" combined with "the law of unintended consequences". The latter law doesn't give me a lot of confidence about the Dodd-Frank regulations (of which the Volcker Rule forms part), 2319 pages of regulation probably have a lot more unintended consequences to come.

Posted by Brian Sentance | 20 January 2012 | 3:47 pm

The financial crisis and Andrew Lo's reading list

I spotted this in the FT recently - for those of you diligent enough to want to read more about the possible causes and possible solutions to the (ongoing) financial crisis, then Andrew Lo may have saved us all a lot of time in his 21-book review of the financial crisis. Andrew reviews 10 books by academics, 10 by journalists and one by former Treasury Secretary Henry Paulson.

Andrew finds a wide range of opinions on the causes and solutions to the crisis, which I guess in part reflects that regardless of the economic/technical causes, human nature is both at the heart of the crisis and evidently also at the heart of its analysis. He regards the differences in opinion quite healthy in that they will be a catalyst for more research and investigation. I also like the way Andrew starts his review with a description of how people's view of the same events they have lived through can be entirely different, something that I have always found interesting (and difficult!).

A quote from Napolean (that I am in danger of over-using) seems appropriate to Andrew's review: "History is the version of past events that people have decided to agree upon" but maybe Churchill wins in this context with: "History will be kind to me for I intend to write it.". Maybe we should all get writing now before it is too late...

Posted by Brian Sentance | 18 January 2012 | 11:17 pm

Pandit on Comparing Apples and Risk

For someone who has been criticised a lot over recent years, Vikram Pandit CEO of Citigroup, seems to have come up with an interesting risk management idea in his latest article in the FT. Vikram proposes that regulators put together an standard, multi-asset "benchmark" portfolio that all financial institutions would have to provide risk numbers on, enabling regulators to understand more of the risk management capabilities of each institution and avoiding any detailed disclosure of the portfolio actually held by each firm.

I guess a key thing would be that such numbers would have to be disclosed to the regulator away from public view, since we all know that otherwise the numbers would converge and all the banks would be doing the same thing (or at least copying each other's numbers?). Reminds me of a great talk at the RiskMinds event a few years back, praising diversity of approach and criticising regulators for effectively forcing everyone to do the same thing.

Posted by Brian Sentance | 12 January 2012 | 2:34 pm

PRMIA - From Risk Measurement to Risk Management by Samuel Won

I attended the PRMIA event last night "Risk Year in Review" at Moody's New York offices. It was a good event, but by far the most interesting topic of the evening for me was from Samuel Won, who gave a talk about some of the best and most innovative risk management techniques being used in the market today. Sam said that he was inspired to do this after reading the book "The Information" by James Gleik about the history of information and its current exponential growth. Below are some of the notes I took on Sam's talk, please accept my apologies in advance for any errors but hopefully the main themes are accurate.

Early '80s ALM - Sam gave some context to risk management as a profession through his own personal experiences. He started work in the early 80's at a supra-regional bank, managing interest rate risk on a long portfolio of mortgages. These were the days before the role of "risk manager" was formally defined, and really revolved around Asset and Liability Management (ALM).

Savings and Loans Crisis - Sam then changed roles and had some first hand experience in sorting out the Savings and Loans crisis of the mid '80s. In this role he become more experienced with products such as mortgage backed securities, and more familiar with some of the more data intensive processes needed to manage such products in order to account for such factors such as prepayment risk, convexity and cashflow mapping.

The Front Office of the '90s - In the '90s he worked in the front office at a couple of tier one investment banks, where the role was more of optimal allocation of available balance sheet rather than "risk management" in the traditional sense. In order to do this better, Sam approached the head of trading for budget to improve and systemise this balance sheet allocation but was questioned as to why he needed budget when the central Risk Control department had a large staff and large budget already.

Eventually, he successfully argued the case that Risk Control were involved in risk measurement and control, whereas what he wanted to implement was active decision support to improve P&L and reduce risk. He was given a total budget of just $5M (small for a big bank) and told to get on with it. These two themes of implementing active decision support (not just risk measurement) and have a profit motive driving better risk management ran through the rest of his talk.

A Datawarehouse for End-Users Too - With a small team and a small budget, Sam made use of postgraduate students to leverage what his team could develop. They had seen that (at the time) getting systems talking to each other was costly and unproductive, and decided as a result to implement a datawarehouse for the front office, implementing data normalisation and data scrubbing, with data dashboard over the top that was easy enough for business users to do data mining. Sam made the point that useability was key in allowing the business people to extract full value from the solution.

Sam said that the techniques used by his team and the developers were not necessarily that new, things like regression and correlation analysis were used at first. These were used to establish key variables/factors, with a view to establish key risk and investment triggers in as near to real-time as possible. The expense of all of this development work was justified through its effects on P&L which given its success resulting in more funding from the business.

Poor Sell-Side Risk Innovation - Sam has seen the most innovative risk techniques being used on the buy-side and was disappointed by the lack of innovation in risk management at the banks. He listed the following sell-side problems for risk innovation:

politically driven requirements, not economically driven
arbitrary increases in capital levels required is not a rigorous approach
no need for decision analysis with risk processes
just passing a test mentality
just do the marginal work needed to meet the new rules
no P&L justification driving risk management

Features of Innovative Approaches - Sam said that he had noted a few key features of some of the initiatives he admired at some of the asset managers:

Based on a sophisticated data warehouse (not usually Oracle or Sybase, but Microsoft and other databases used - maybe driven by ease of use or cost maybe?)
Traders/Portfolio Managers are the people using the system and implementing it, not the technical staff.
Dedicated teams within the trading division to support this, so not relying on central data team.

A Forward-Looking Risk Model Example - The typical output from such decision analysis systems he found was in the form of scenarios for users to consider. A specific example was a portfolio manager involved in event-driven long-short equity strategies around mergers and acquisitions. The manager is interested in the risk that a particular deal breaks, and in this case techniques such as Value at Risk (VaR) do not work, since the arbitrage usually requires going long the company being acquired and short the acquiror (VaR would indicate little risk in this long-short case). The manager implemented a forward looking model that was based on information relevant to the deal in question plus information from similar historic deals. The probabilities used in the model where gathered from a range of sources, and techniques such as triangulation where used to verify the probabilities. Sam views that forward-looking models to assist in decision support are real risk management, as opposed to the backward-looking risk measurement models implemented at banks to support regulatory reporting.

Summary - Sam was a great speaker, and for a change it was refreshing to not have presentation slides backing up what the speaker was saying. His thoughts on forward looking models being true risk management and moving away from risk measurement seem to echo those of Ricardo Rebanato of a few years back at RiskMinds (see post). I think his thoughts on P&L motivation being the only way that risk management advances are correct, although I think there is a lot of risk innovation at the banks but at a trading desk level and not at the firm-wide level which is caught up in regulation - the trading desks know that capital is scarce and are wanting to use it better. I think this siloed risk management flies in the face of much of the firm-wide risk management and indeed firm-wide data management talked about in the industry, and potentially still shows that we have a long way to go in getting innovation and forward looking risk management at a firm level, particularly when it is dominated by regulatory requirements. However, having a truly integrated risk data platform is something of a hobby-horse for me, I think it is the foundation for answering all of the regulatory and risk requirementst to come, whatever their form. Finally, I could not agree more easy analysis for end-users is a vital part of data management for risk, allowing business users to do risk management better. Too many times IT is focussed on systems that require more IT involvement, when the IT investment and focus should be on systems that enable business users (trading, risk, compliance) to do more for themselves. Data management for risk is key area for improvement in the industry, where many risk management sytem vendors assume that the world of data they require is perfect. Ask any risk manager - the world of data is not perfect and manual data validation continues to be a task that takes time away from actually doing risk management.

Posted by Brian Sentance | 14 December 2011 | 11:29 pm

Data Unification - just when you thought it was safe to go back in the water...

Sitting by the sea, you have just finished your MATLAB reading and now are wondering what to read next?

No worries!

We have just published our "TimeScape Data Unification" white paper. Not a pocket edition I am afraid, but some of you may find it interesting.

It describes how - post-crisis - a key business and technical challenge for many large financial institutions is to knit together their many disparate data sources, databases and systems into one consistent framework than can meet the ongoing demands of the business, its clients and regulators. It then analyses the approaches that financial institutions have adopted to respond to this issue, such as implementing a ETL-type infrastructure or a traditional golden copy data management solution.

Taking on from their effectiveness and constraints, it then shows how companies looking to satisfy the need for business-user access to data across multyple systems should consider a "distributed golden copy" approach. This federated approach deals with disparate and distributed sources of data and should also provide easy and end-user interactivity whilst maintaining data quality and auditability.

The white paper is available here if you want to take a look and if you have any feedback or questions, drop us a line!

Posted by Sara Verri | 27 July 2011 | 3:19 pm

Removing the punchbowl at NYU-Poly

A few of choice quotes from the rest of the day at NYU-Poly:

"The difference between economists and meteorologists is that meteorologists can at least agree on what happended yesterday"
"A bubble can only be identified from a trend when the bubble bursts"
"Capital flows from strange places to strange destinations in today's financial markets"
"In a Basel III world, the stock price of Morgan Stanley would rise if its investment banking division were sold off"
"Basel III is a good attempt at managing systemic risk"
"Hedge Funds are the risk takers of the future"
"Hedge Funds have the partnership mentality that the commercial banks have lost and should regain"
"CCPs should not compete on risk management"
"Economists are trained to predict everything except the future"
"Dodd Frank was a missed opportunity to consolidate the many regulators in the United States"
"Washing D.C. is all about turf and theatre"
"Insolvency and liquidity risk are not clearly separable"
"Beware the Golden Rule. He who makes the Gold makes the Rule"
"Systemic risk is not the sum of individual institutional risk"
"As Chuck Prince said "As long as the music is playing, you’ve got to get up and dance""
"Systemic risk management only works when we all stop dancing"
"Regulation should remove the punchbowl just when the party is getting started"

Posted by Brian Sentance | 20 June 2011 | 8:43 pm

More formal management of instrument valuation needed

Xenomorph has today released its white paper “Instrument Valuation Management: management of derivative and fixed income valuations in a multi-asset, multi-model, multi-datasource and multi-timeframe environment”.

The white paper expands on the “Rates, Curves and Surfaces – Golden Copy Management of Complex Datasets” white paper Xenomorph published recently (see earlier post) and describes how, despite the increasing importance of instrument valuation to investment, trading and risk management decisions, valuation management is not yet formally and fully addressed within data management strategies and remains a big concern for financial institutions.

Too often, says Xenomorph, valuations (and the analytics used to process input and calculate output data) fall between traditional data management providers and pricing model vendors. This leads to the over–use of tactical desktop spreadsheets where data “escapes” the control of the data management system, leading to an increased operational risk.

Whilst instrument valuation is certainly not the primary cause of the recent financial crisis, the lack of high quality, transparent valuations of many complex securities resulted in market uncertainty and in the failure of many risk models fed by untrustworthy valuations.

“A deeper understanding of financial products reduces operational risk and promotes quality, consistency and auditability, ensuring regulatory compliance”, says Brian Sentance, CEO Xenomorph. “Clients’ requirements have evolved and portfolio managers, traders and risk managers recognize that it is no longer sufficient to treat valuation as an external, black-box process offered by pricing service providers”, he adds.

Nowadays, regulators, auditors, clients and investors demand even more drill-down to the underlying details of an instrument’s valuation. It is therefore important to implement an integrated, consistent analytics and data management strategy which cuts across different departments and glues together reference and market data, pricing and analytics models, for transparent, high quality, independent valuation management.

“Our TimeScape solution provides a valuation environment which offers rapid and timely support for even the most complex instruments, allowing our clients to check easily the external valuation numbers, based on their choice of model and data providers”, says Sentance. “Otherwise, what is the point of good data management if the valuations and the analytics used are not based on the same data management infrastructure principles?”

For those who are interested, the white paper is available here.

Posted by Sara Verri | 4 May 2011 | 12:41 pm

2010 Risk in Review NY

I went along to a a Prmia event last night "2010 - Risk Year in Review". The event started with a somewhat overwhelming brain dump of economic and credit statistics from John Lonski, Chief Capital Markets Economist at Moody's Analytics. In summary he seems very bullish about corporate credit spreads tightening given the way in which corporate profit growth is surging ahead of debt growth. His main concern for the economy was maybe unsurprisingly the US housing market and whether this will bottom out and start to rise in 2011. Given fiscal imbalances and competition from emerging markets he did not think that inflation was a big risk despite activity such as QE2.

Robert Iommazzo of search firm Seba International did a fairly dry presentation on industry compensation for risk managers. Seba seem to getting around having had a big presence at Riskminds in Geneva last week. This section only livened up when the questions started after the presentation, and is probably worth noting that the UK FSA is being perceived as a "Big Brother" with its involvement in setting compensation policies in financial markets. Obviously the FSA is not heading back to the heady days of the 1970's where central government set industry pay rises (journalists please note this meant you back then!), but it is also obvious that such control over an individual's remuneration is something that goes totally contrary to an American way of thinking. UK Government needs to be mindful of this perception particularly if it leaves itself open to arbitrage on compensation policy from other financial centres.

Panel debate followed, involving Ashish Das of Moody's, Yury Dubrovsky of Lazard Asset Management, Jan H. Voigts of the NY Fed and Christopher Whalen of Institutional Risk Analytics. Main points:

Chris said that he was one who was predicting a further fall in the housing market next year, and he asked the audience that when they looked at economic statistics, credit spreads,the Vix, bond spreads, did anyone getting the feeling the things are "normal" yet? Using these numbers and plugging them into a model does any believe the results are stable and can be relied upon? The audience fundamentally seemed to agree with these "warning" questions.
Jan asked the audience to consider how believable is your data and to try to understand what data is critical for your business and that is imperative to create tools to manage this data appropriately. Jan said that the biggest challenge for financial institutions going forward is how to calibrate what rate/volume/type of business you can transact safely and that this needed a lot more consideration.
Yury said that he finds that the risks present in 2008 are still around in 2010, but now with the addition of European sovereign credit problems and the raft of regulation heading towards the industry. To add to this pessimistic note, he also said that some of the interest in "hot" emerging markets such as the BRICs was resulting in investments in lower quality IPOs relative to previous years.
Ashish thought that systemic risk was going to become more important for the industry. With the setting up of the Office of Financial Research (OFR) next year, he suggested that the industry needed to take much more of a lead in sorting out its own house in advance of letting the regulators do so. On the subject of models, he said that models should supplement human judgement but not replace it, and mentioned the quote by George E. P. Box that "all models are wrong, but some are useful".
Chris suggested that the role of risk managers will become more like that of a credit collector, with more involvement in actually seeing what can be recovered once a default has occurred. He also suggested that the industry should create its own consensus-based ratings (supplemented by the existing CRAs) to get a more reliable view of credit.
Ashish echoed some of the speakers last week at Riskminds in saying that regulatory compliance is not risk management, and that practitioners should do more to guide the regulators.
On the subject of risk culture, Yury asked how many risk managers knew data, quant, markets and how to deal with the egos of traders and senior management. This last point seemed to be conceded by the audience as a major weakness of the risk management profession and goes back to whether a risk manager is willing to put his career on the line to go against accepted business strategy.
Chris added that having worked at several investment banks he had not yet experienced a risk manager attending a senior committee, let alone a risk manager speaking up against a senior trader. He talked of two business models "Paranoid and Nimble" and "Well Documented and Pedantic" with the second one being the only one possible in his view once a business gets to a certain size.
On the subject of Government Sponsored Enterprises (GSEs like Fannie Mae and Freddie Mac) Chris said that the role of these will be up for review by the end of 2011. He thinks that the banks will head back towards actually holding mortgages and loans and the GSEs will become more conduits rather than direct sources of finance. This was news to me, given that so far the GSEs have been notably left out of recent reviews of what went wrong with the recent crisis.

Panel was very good, all speakers very knowledgeable. "Regulation is not risk", "models are not perfect", "risk governance" and "take control of your data" were all themes that echoed last week's RiskMinds event, allbeit with more of an American rather than international viewpoint on the economy, regulation and markets.

Posted by Brian Sentance | 15 December 2010 | 5:16 pm

Risk USA - 15 cents in the dollar isn't good...

I went along to the Risk USA event yesterday and caught a good panel in the afternoon called “Garbage in, garbage out” Servicing the data supply and analytic needs for risk management.

In particular, one of the speakers, Frank R. Brown, described some work he had done as a consultant at one financial institution on tracking and rebalancing an index product. To do this, Frank had to integrate the constituent instrument symbology of the:

Custodian
Index Provider
Real-Time Data Provider
Rebalancing Software
In-house Trading System

On top of this, corporate events might result in changes to symbology that not all providers would be up to date on, with various lags before all had caught up with the corporate action (rebalancing software often late, custodian often not changing symbol at all). He mentioned that he did all of this symbology management manually in Excel.

Of his time, he said he spent:

65% on managing the symbology and dealing with data issues
20% managing the various vendor APIs in Excel to update the data
15% on tracking and rebalancing

To sum up, he said that a productive work level of 15 cents in the dollar wasn't good value for the client and yet the issue continues on and on. I don't think that his example was particularly earth shattering in terms of newness, but it put in a very simple and pragmatic context the importance of doing some of the simple things right and the benefits of a more automated approach to data management, even before you delve into the data quality/validity issues of the market data itself.

Just to end on an entertaining note, then back to the title of the talk on "Garbage-in, garbage-out..." the panel moderator (Domenic Iannaccone of Sybase) put forward a good quote he had heard:

"If everyone used the same garbage at least that would be a step forward!"

Transparency and consistency can take many forms, but I didn't know it needed to apply to incorrect data too!...

Posted by Brian Sentance | 4 November 2010 | 7:15 pm

A French Slant on Valuation

Last Thursday, I went along to an event organized by the Club Finance Innovation on the topic of “Independent valuations for the buy-side: expectations, challenges and solutions”.

The event was held at the Palais Brongniart in Paris, which, for those who don’t know (like me till Thursday), was built in the years 1807-1826 by the architect Brongniart by order of Napoleone Bonaparte, who wanted the building to permanently host the Paris stock exchange.

Speakers at the roundtable were:

Eric Benhamou, CEO Pricing Partners
Francis Cornut, Président DeriveXperts
Jean-Marc Eber, Président LexiFi
Patrick Hénaff, Associated Professor at the University of Bretagne (see model validation paper for additional background)
Claude Martini, CEO Zeliade Systems

The event focussed on the role of the buy-side in financial markets, looking in particular at the concept of independent valuations and how this has taken an important role after the financial downturn. However, all the speakers agreed that remains a large gap between the sell-side and buy-side in terms of competences and expertise in the field of independent valuations. The buy-side lacks the systems for a better understanding of financial products and should align itself to the best practices of the sell-side and bigger hedge funds.

The roundtable was started by Francis Cornut of DeriveXperts, who gave the audience a definition of independent valuation. Whilst valuation could be defined as the “set of data and models used to explain the result of a valuation”, Cornut highlighted how the difficulty is in saying what independent means; there is in fact a general confusion on what this concept represents: internal confusion, for example between the front office and risk control department of an institution, but also external confusion, when valuations are done by third-parties.

Cornut provided three criteria that an independent valuation should respect:

Autonomy, which should be both technical and financial;
Credibility and transparency;
Ethics, i.e.: being able to resist to market/commercial pressure and deliver a valuation which is free from external influences/opinions.

Independent valuations are the way forward for a better understanding of complex, structured financial products. Cornut advocated the need for financial parties (clients, regulators, users and providers) to invest more and understand the importance of independent valuations, which will ultimately improve risk management.

Jean-Marc Eber, President LexiFi, agreed that the ultimate objective of independent valuations is to allow financial institutions to better understand the market. To accomplish this, Eber pointed to the fact that when we speak about services to clients, we should first think of what are their real needs. The bigger umbrella of “buy-side” implies in fact different needs and there is often a contradiction on what regulators want: on one side, having independent valuations provided by independent third parties; on the other side, independent valuations really mean that internal users/staff do understand what there is underline the products that a company have.In the same way, we don’t just need to value products but also measure their risk and periodically re-value them.It is important, in fact, to have the whole picture of the product being evaluated in order to make the buy-side more competitive.

Another point on which the speakers agreed is traceability: as Eber said, financial products don’t exist just as they are, but they go under transformation and change several times. Therefore, the market needs to follow the products across its life cycle till its maturity stage and this pose a technology challenge, in providing scenario analysis for compliance and keeping track of the audit trail.

At the question, ‘what has the crisis changed’ panellists answered:

Eber: the crisis showed the need to be more competent and technical to avoid risk. He highlighted the need to understand the product and its underlying. Many speak of having a central repository for OTCs, obligations, etc but this needs more thinking from the regulators and the financial markets. Moreover, the markets should focus more on quality data and transparency.

Eric Benhamou, CEO pricing Partners, sees an evolution of the market as the crisis showed underestimated risks which are now being taken in consideration.

Claude Martini, CEO Zeliade, advocated the need for financial markets to implement best practices for product valuations: buy-side should apply the same practices already adopted by the sell-side and verify the hypotheses, price and risk related to a financial product.

Cornut admitted things have changed since 2005, when they launched DerivExperts and nobody seemed to be interested in independent valuations. People would ask what value they would get from an investment in independent valuations: yes, regulators are happy but what’s the benefit for me?

This is changing now that financial institutions know that a deeper understanding of financial products increases their ability to push the products to their clients. The speech I enjoyed the most was from Patrick Hénaff, associated professor at the University of Bretagne and formerly Global Head of Quantitative Analysis - Commodites at Merrill Lynch / Bank of America.

He took a more academic approach and contested the fact that having two prices to confront is thought to reduce the incertitude on the product but highlighting as this is not always the case. I found interesting his idea of giving a product price with a confidence interval or a ‘toxic index’ which would represent the incertitude about the product and reproduce the model risk which may originate from it.

We speak too often about the risk associated to complex products but Hénaff, explained how the risk exists even on simpler products, for example the calculation of VAR on a given stock positioning. A stock is extremely volatile and we can’t know its trend; providing a confidence interval is therefore crucial. What is new instead, it is the interest that many are showing in assigning a price to a determinate risk, whilst before model risk was considered a mere operational risk coming out from the calculation process. Today, a good valuation of the risk associated to a product can result in less regulatory capital used to cover the risk and as such it is gaining much more interest from the market.

Henaff describes two approaches currently taken from academic research on valuations:

1) Adoption of statistic simulation in order to identify the risk deriving from an incorrect calibration of the model. This consists in taking historical data and test the model, through simulations and scenarios, in order to measure the risk associated in choosing a model instead of another;)

2) Have more quality data. Lack of quality data implies that models chosen are inaccurate as it is difficult to identify exactly what model we should be using to price a product.

Model risk, which as said above was before considered an operational risk, now becomes of extremely importance as it can free up capital. Hénaff suggested that is key to find for model risk the equivalent of the VAR for market risk, a normalized measure. He also spoke about the concept of a “Model validation protocol”, giving the example of what happens in the pharmaceutical and biologic sectors: before launching a new pill into the market, this is tested several times.

Whilst in finance products are just given with their final valuation, the pharmaceutical sector provides a “protocol” which describes the calculations, analysis and processes used in order to get to the final value and their systems are organized to provide a report which would show all the deeper detail. To reduce risk, valuations should be a pre-trade process and not a post-trade.

This week, the A-Team group published a valuations benchmarking study which shows how buy-side institutions are turning more and more often to third-parties valuations, driven mainly by risk management, regulations and client needs. Many of the institutions interviewed also admitted that they will increase their spending in technology to automate and improve the pricing process, as well as the data source integration and the workflow.

This is in line on what has been said at the event I attended and confirmed by the technology representatives speaking at the roundtable.

I would like to end with what Hénaff said: there can’t be a truly independent valuation without transparency of the protocols used to get to that value.

Well, Rome wasn’t built in a day (and as it is my city we’re speaking about, I can say there is still much to build, but let’s not get into this!) but there is a great debate going on, meaning that financial institutions are aware of the necessity to take a step forward. Much is being said about the need for more transparency and a better understanding of complex, structured financial products and still there is a lot to debate. Easier said than done I guess but, as Napoleon would say, victory belongs to the most persevering!

Posted by Sara Verri | 28 October 2010 | 4:50 pm

Dodd Frank Regulation - being seen to be doing something?

I went along to a Six Telekurs event "Securities Valuations: Is the Price Right?" last week - good event with some interesting speakers, most notably Paul Atkins of Patomak Partners to talk about the Dodd-Frank Wall Street Reform and Consumer Protection Act 2010. Paul is based out of Washington and was not very complimentary about what has been going on.

He started by saying that the Act was very large in size, with over 2319 pages (compared to SarbOx with only 60) and given this size he suggested that you could guess how many in Congress had actually read it. Background to the Act were:

"Political Tailwinds" such as:
- New Democrat Government with tenuous majority
- Ambitious legislative plans
- Bleak economic back-drop
An angry populace:
- TARP bailouts/Wall St bonuses
- Recession and high unemployment
- Perception that Govt. contributed to crisis
Aggressive case for new regulation based on:
- Lack of confidence in current systems and regulation
- "Too big to fail" demonstrating that regulators lack the toolsets necessary to deal with such events
- High leverage across the financial system and the economy
- Poor risk management by existing participants
- Opaque shadow banking system and opaque derivatives markets

He summarised that Housing and the Credit Rating Agencies were the key fundamentals behind the financial crisis.

Paul said that with the new regulation had the following features:

The Act is a sweeping revision of financial regulation in the US
- few dodged the regulatory changes (notably insurance managed to do this)
The Federal Reserve has emerged pre-eminent amongst all regulatory bodies in the US.
Significant discretion has been yielded to regulators to work out specifics
Sheer size and ambiguous wording of the Act exacerbates the uncertainty in the market and economy and will require further fixes over coming years
The Act does not reform Government Sponsored Enterprises (Fannie Mae, Freddie Mac)
Far from reducing/simplifying the number of agencies involved in regulation the Act eliminated 1 agency and created 13 more
Paul asked the question whether spreads and volatility will rise in the market due to new regulation (such as the Volcker rule) and whether ultimately this will trickle down to hinder or benefit SMEs.
The Act will likely result in regulatory arbitrage opportunities and Paul said this was not a good thing for the United States

Paul said that in his view Congress learned the wrong lessons from the crisis:

No reform of Fannie Mae and Freddie Mac
Government Housing Policy left unaddressed
Transparency still lacking despite efforts from FASB on fair value
International Policy Co-ordination is still an open question as to its extent
No reform of existing regulator structures
The crisis has resulted in payoffs to favoured groups (Unions, Trial Lawyers etc)

Paul talked about how hedge funds and private equity funds were going to experienced increased regulation with them having to register if they have over $100M assets under management and future implications for systemic risk provisions. He mentioned that Venture Capital investments had escaped being required to register if the lock-up period was over 2 years.

He briefly discussed the coming changes in OTC derivatives on centralised clearing, post trade reporting and new liability provisions. Paul was also concerned about certain SEC related issues such as "Whistleblower" provisions which contain a bounty programme of about 10-30% of any fine subsequently awarded against a financial institution. He re-iterated that it was not yet clear what all of the bodies involved in regulation would be doing, and at the same time as this was the case the very same bodies were also being given very strong powers such as that of legal subpoena.

Paul was a very knowledgeable speaker and had some good points to make. Listening to him speak it would seem from my perspective that the Act is a prime example of "being seen to be doing something" to address the crisis rather than something better structured, with all of "law of unintended consequencies" risks that such an initiative entails.

Posted by Brian Sentance | 14 October 2010 | 7:32 pm

Active to Passive and Back Again

FT article saying that passive fund management is set for growth giving the disillusionment of investors with the benefits of active fund management. Interesting piece was the bit where the growth in index-based investment may ultimately introduce index-inclusion distortions in constituent pricing, so ultimately swinging round to benefit those active fund managers that are still around to see this. Makes sense as there is always some money to be made (and lost!) when everyone starts to do the same thing, or maybe I am already being taken in by the forward-looking PR departments of the active fund managers?...

Posted by Brian Sentance | 27 June 2010 | 6:33 pm

The Humans Between Risk and Data

Some of my thoughts on risk management, data management and human behaviour, are to be found on page 20 of the Inside Reference Data Special Report "Managing Risk"

Posted by Brian Sentance | 21 June 2010 | 1:22 pm

A Crisis Needs a Utility?

I heard Francis Gross of the ECB speak at one of the panel events at the XTrakter Conference last week, and found that I couldn't avoid asking him whether the aims of the "Data Utility" initiative by the ECB could be better separated from the means by which the ECB proposes to solve them. At the moment, reference data issues for the industry and the data utility seem to be presented as a single "package". I can't say that the response to my question was a clear one to my understanding; however I would say that Francis was helpful after the panel had finished and provided a recent presentation of their ideas, of which you can find a copy here.

Looking through the presentation, the motivations put forward for why the industry needs a data utility seem to include:

Data processing must be done in an automated manner, since data volumes have moved beyond the capabilities of manual processing.
- can't see anyone arguing with this
Data is a major bottleneck, with multiple providers/sources each with the own "data dialect"
- agreed and to some extent what keeps data/data management vendors in business, but sounds sensible to standardise if possible as there are plenty of other problems to address
These data dialects lead to increased cost, operational risk and reduced responsiveness
- agreed, mainly a cost aspect I would suggest
The recent crisis was not helped by weak data management in the industry
- but nor was it the cause, so not a great premise for a data utility
- lack of transparency of data
  - "transparency" is an over-used word at the moment, but certainly clarity and quality were/are needed
- systematic risk could not be assessed due to the availability of data
  - using terms like "systematic risk" seems to imply the regulators could calculate something, whereas this discipline is new so I guess we are really talking about simply knowing who is exposed to who and how.
We need the capability to run large scale computing analysis on a vast pool of micro data, sometimes on an ad-hoc basis when a crisis begins
- fundamentally agreed but also good to qualify with what you propose to be calculated - having a set of "numbers" doesn't seem to have helped much recently...

I started the above bullet point list by saying it contains the motivations for "why the industry needs a data utility" but I guess looking at the above list they really point to the more general aim of "why we need better industry-level data management". In the presentation the above points are then used to state:

"We all need the same good basic reference data. Why build more than one infrastructure?"

Maybe "Why build more than one infrastructure?" should really be changed to say "Why maintain more than one infrastructure?" given that Bloomberg, Thomson Reuters, Six Telekurs, Interactive, Markit and all the other vendors already infrastructure to do this. Not sure if I should read anything into the wording but more logical leaps of faith are to follow.

The presentation then moves on to state that shared reference data standards are a must, to which I cannot see many consumers of data disagreeing with that statement. Not sure I agree though with the overly simplistic statement that "Data will be good for all users or good for none". Trying telling that to the accountancy and risk departments for example but I suppose what we are talking about here is basic reference data not the more subjective price and valuation data. Reference data on instruments and entities is either right or wrong, and the presentation makes the good point that no amount of "data cleaning" can help this i.e. if wrong, the data needs to be re-captured from an accurate source.

The call for the establishment and use of reference data standards in the presentation then seems to be used to "slide "into a call for a standard reference data infrastructure. Unless I am very much mistaken, these two things are not necessarily the same thing and so it seems a logical leap has been taken here. The presentation talks about the possible necessity of "top down" legal compulsion for the industry, again something that I could agree and see the need for, but both the issues and legal compulsion do not automatically drive us to a "data utility" as the only option? Why couldn't legal compulsion be applied to the existing data vendors to standardise on common IDs for instance? ISIN is proposed as a standard in the presentation, but I can only assume that this is due to the ECB being mainly focussed on the bond world where to a large degree ISIN's work (i.e. are unique), whereas in the world of equities ISIN needs a lot of qualification (currency, exchange, share class...) before it uniquely identifies a quoted equity.

In summary, the presentation starts with showing how great the ECB's Centralised Security DataBase is (7 million securities, 3 million record updates/day etc...) and it does look good. The data issues for the industry seem clear, although I think the "crisis" is a bit of a red herring to the aim of data cost reduction, however the logical jump from industry need to effectively "we must have a data utility" is an interesting one, one where I would prefer that more options were discussed. It seems ironic that in these days of "transparency" it is not at all that transparent to me why more alternative solutions are not being discussed and a choice justified. Talking of choice and as a final thought, I am also not sure why the data vendors are not up in arms about this initiative - are they frantically lobbying behind the scenes? - do they simply think the utility won't go ahead? - or are they afraid of upsetting the EU? Any insight is very welcome, and maybe more of update from me when I get chance to speak with Francis in more detail.

Posted by Brian Sentance | 4 June 2010 | 7:00 am

Accountants, Prices and Upsidedown Elastic...

I am sure I am not the only one who has had to suffer the boredom of a economics lecture on price elasticity, but my interest in this old topic was sparked by an article by Tony Jackson in the FT on Monday, providing a very simple and clear explanation of how mark-to-market accounting (see earlier post) can conspire with leverage to turn price elasticity on its head, so the more something goes up in price, the more in demand it becomes...perhaps I should have paid more (or less?) attention to what the dusty prof was saying...

Posted by Brian Sentance | 31 March 2010 | 11:35 am

Data models are not what they used to be...

AIM have released the results from their 2009 survey on reference data management which is worth a look, particularly given the 2008 results are also shown for comparison. Seems like Mike Atkin and the EDM Council have their work cut out in getting the Semantics Repository adopted if the survey is anything to go by, with the number of institutions using standards-based data models having dropped significantly when comparing 2009 to 2008. What is going on there in these heady days of the finance industry sorting out its data problem through adopting standards? - In cash starved times, maybe it costs more to conform to a standard? - Is the survey data not broad enough? Any ideas appreciated!

Posted by Brian Sentance | 18 March 2010 | 8:09 pm

One man's speculation is another man's insurance...

The current finanical crisis in Greece has prompted an outburst of entertaining discussion at the FT about CDS contracts, initiated by a feature article by Wolfgang Munchau who advocates that naked CDS contracts should be banned. The main argument used is that you should not be able to insure against a risk that you do not face e.g. buying insurance on somebody else's house then arranging to have the house burnt down. In support of Mr Munchau, one reader letter points out that insurance without interest in the insured item has been illegal since 1746, which on the face of it seems a long enough time to be a credible point in the discussion.

However, in using this argument then Mr Munchau seems be to attacking the whole of the derivatives industry not just CDS, for example the same argument could be used to ban the use of naked index puts to hedge equity market risk. I guess he is also helping some of the politicians in the EU direct attention away from Greece's financial mismanagement more towards the "evils" of the derivatives markets and hedge funds.

Some good letters in response, for instance this one with a good illustration of what hedging would be like without intermediaries to buy and sell risks that they do not own, plus another more direct one from the Association of Corporate Treasurers.

Whilst talking of Greece and credit, the FT Alphaville team also poked some fun at Anatole Kaletsky, the economist of the London Times Newspaper, who has recently done some interesting articles in the paper concerning his predictions about the stresses being suffered by Greece and the Euro. From their post, it would seem that Mr Kaletsky also runs a credit related fund, so it is implied that some of his newspaper views need to "calibrated" against his own vested interests...

Posted by Brian Sentance | 9 March 2010 | 2:40 pm

"Cut and Paste" Valuation Services

You can talk about more robust modelling, more stringent scenario testing and even moving everything onto an exchange, but unless we move the principles of good data management (in my view: consistency, security and quality of all types of data) into the front office then we will continue to get front-office mis-marking as described in this article in the FT.

Thanks to Ralph Baxter from Cluster7 for highlighting this article for me and those of you interested in this topic of operational risk and spreadsheet mis-use should maybe go along to EuSpRiG this year, and maybe take a look at a paper Xenomorph presented at a previous conference.

Posted by Brian Sentance | 4 February 2010 | 9:49 am

More Products, Less Complexity?

Decent article(and title!) explaining ETFs in FTfm today - growth of the market sounds impressive, from $40bn in the year 2000 to over $1,000bn under management now. Seemed like a bit of a day for new financial products in the FT, with the LSE announcement of opening up direct bond trading to retail investors through offering corporate bonds issued in sizes well below the usual £50,000 size (and catching up with more usual practice in Europe). Whilst not a retail product (I guess some of us already have life insurance?), longevity derivatives seem to continue their rise too in liability driven investment.

Meanwhile over on Linkedin, Structured Products magazine are asking just what constitutes a "complex" product? A decent question since complex products are not necessarily risky, but certainly "complexity is in the eye of the beholder" is most likely answer in my view - echoing a growing problem in finance, regulation and economics at the moment; there are too many people searching for the unique "right" answer to questions that simply do not have one. Maybe we should stick to the answer to everything being "42" and give up the search for the question?...

Posted by Brian Sentance | 2 February 2010 | 1:51 pm

Maths to Money - Quantitative Investment

I attended the Quant Invest 2009 event for the first time last week in Paris. The event is unsurprisingly about quantitative investment strategies, but with an institutional asset manager and hedge fund focus - so not so much about ultra-high frequency trading (although some present) but more about using quantitative techniques to manage medium/longer-term investment decisions and applied portfolio theory. A few highlights below that I found interesting:

Pierre Guilleman of Swiss Life Asset Management gave an interesting 1/2 day workshop entitled "A random walk through models":
He is a strong supporter of the need to understand more about the data and statistical assumptions upon which any quant investment model is based and how these fit with the desired investment objectives (similar to the Modeler's Manifesto)
He made the point that good models can sometimes be almost annoyingly simple, and cited the example by a Professor Fair of Yale who had determined that US elections were predictable based on simple parameters such as past results, inflation and gdp and that policy did not seem to be a key factor at all - annoying for the politicians anyway!
Pierre seems very concerned that the Solvency II regulation applied to Life Institutions will negatively influence the investment policies of many institutions - applying sell-side risk measures like VAR to the insurance industry will drive a more short-term approach to investment. He strongly believes that VAR applied to his industry should have an expected return parameter introduced to fit with longer term investment horizons of 10 to 25 years.
Bob Litterman of Goldman Sachs Asset Management opened the first "official" day of the conference:
Bob put forward his "scientific" approach to investment modelling going through the stages of hypothesis, test and implement. He warned against overconfidence in investment (apparently 70% of us think we are "above average"...) and impulsiveness (quick impulsiveness test: "if a bat costs $1 more than the ball, and the bat and ball together cost $1.10 then how much does the bat cost?...")
He said that the failure of quantitative investment models in 2007 needed to be understood given the success of quant models over past decades. In particular he thought that quant investment became the "crowded trade" of 2007 with every hedge fund having a quant investment strategy. In terms of why this became a "crowded trade" Bob thinks that the barriers to entry into quant investment (particularly technology) have lowered significantly recently.
He noted that factor-based investment opportunities decay quicker than they used to due to increased competition - implying the need for a more dynamic and opportunistic investment approach.
GSAM are now looking at new markets and new investment instruments, trying to find areas of market disruption but without following what others are doing in the market.
He pointed out the conflict between investors wanting more transparency over what is done for them, against the need to be more proprietary about the investment models developed.
Next there was a talk on regulation from the French regulator that was dull, dull, dull both in terms of content and presentation style (when will regulators actually prepare well for the talks they give?)
Panel debate was also pretty average, with the word "alpha" being used too much in my view - asset managers of a certain type seem to hide behind this word as an opaque "magic wand" to justify what they do.
Jean-Phillippe Bouchard of Capital Fund Management did a great talk called "Why do Prices Move?". Some points from the talk:
He started off with a reminder about the Efficient Markets Hypothesis (EMH) and how it says that crashes and market movements are caused by events outside (endogenous to) the market such as news, events etc.
He then said this was not born out in the data, where extreme jumps in prices were only related to news only 5% of the time.
Volatility looks like a long memory process with clustering of vol over time - similar to behaviour in complex systems
The sign of order flow is predictable but the price movement is not, with only 1% of daily order volume accounting for price movements over 5%
Even very liquid stocks have low immediate liquidity, meaning that price movements can play out over many hours and days as liquidity is sought to "play-out" some change in fundamental price levels.
Joseph Masri of the Canadian Pension Plan Investment Board then did a good talk on Risk Management:
Jo said that sell-side risk was easier to deal with in some ways since it involved fewer strategies in high volumes, and hence could be better resourced.
Buy-side quantitative risk was harder due to its reliance onsell-side research and risk tools, the outsourcing of credit assessment to the credit rating agencies, the loss of Bear and Lehman's having caused the buy-side to have to do more risk management itself (and through third parties) rather than rely on the sell side risk management tools.
He said that sell-side risk models are a good start for an asset manager, but need to be adapted to give both absolute and relative risk (to a benchmark fund for instance). All models are no substitute for risk governance.
He described the cross over from risk methods: VAR, stress testing, factor-based and their applicability to market risk, credit and counterparty risk.
Like Pierre he was not a fan of 1 or 10 day trading VAR being applied to investment managers since this risk measure was not suitable for long term investment in his view.
On stress testing he said this needed to be top down (using historical events etc) as well as bottom up from knowing the detail of strategy/portfolio.
In terms of challenges in risk management he said that VAR needed more stress testing to cope with the fat tails effect in markets, that liquidity risk both of counterparties and of illiquid products was vital and the importance of stress testing (he mentioned reverse stress testing) plus also the feedback (crowding effects) of having similar investment strategies to others in the market.
Dale Gray of the IMF gave a very interesting talk on how he and Bob Merton have been applying the contingent claims model of a company (looking at equity in terms of option payoffs for shareholders and bondholders) to whole economies:
He said that some of his work was being applied to produce a model for the pricing of the implicit guarantees offered by governments to banks
He said these models were also applicable to macro-prudential risk
Very interesting talk, and if he really has something of macro-level risk then this is great relative to the wooly approach by the regulators so far

There were some other good talks from Danielle Bernardi on Behavioural Finance, Martin Martens on Fixed Income Quant Investment, Vassilios Papathanakos on Stochastic Portfolio Theory (seemed to be a "holy grail" of investment model, giving good returns even in the crisis - begs the question why he is telling everyone about it?), Claudio Albanese on unified derivative pricing/calibration across all markets (again another "holy grail" worth more investigation) and Terry Lyons on speeding up monte carlo simulations.

Overall a good conference although the quality of the asset managers present seemed very digital from those who really seemed to know what they talking about to those who plainly did not (in my limited view!). Along this line of thought, I think it be good to test whether there is an inverse relationship between the quality of the asset manager and the amount of times they use the word "alpha" to explain what they are doing...

Posted by Brian Sentance | 5 December 2009 | 2:08 pm

It's in the hormones...

Taking the discussion on behavioural finance and news analytics a scientific step further, then this article in the FT today on how increased testorone equals an increased appetite for risk taking is interesting. Apparently experience of trading is also a big help in increasing a trader's Sharpe ratio, from which the authors suggest that markets are not efficient and the EMH does not hold. Now if only they could find a hormone that was correlated with increased returns, then I think they'd really have something...

Posted by Brian Sentance | 25 November 2009 | 7:12 pm

Regulatory moves and moods

Seems that the latest EU and Basel Committee proposals on banking regulation cannot make everyone happy (now there's a surprise...). Whilst many seem very happy at the incremental nature of the proposals to increase capital requirements for securitisations and proprietary trading, some of those in the Glass-Stiegal/banking utility camp are less than impressed. I am with the incremental camp myself, but have to acknowledge that the sceptics are not short of ammunition when saying that we are heading back to the future...meanwhile over in hedge fund land, London is currently in a very bad mood with the EU...

Posted by Brian Sentance | 15 July 2009 | 6:02 pm

Lessons for Risk Management - Wilmott and Rowe

Great event organised by PRMIA and IAFE last night at Goldman's London offices with a long title:

"A Little Thought Goes A Long Way and Lessons for Risk Management from the Current Crisis".

The event was moderated by Giovanni Bellossi of FGS Capital, and featured speaking slots by Paul Wilmott and David Rowe of Sungard. Here are my notes on the evening, please forgive any innaccuracies, and please persevere through some of the techy quant stuff, as their general points are well worth understanding.

Giovanni quoted from Nassim Taleb about how VAR is invalid and that mainstream financial mathematics should be banned (or words to that effect, see earlier post on Taleb)
He added that whilst what Taleb says cannot be ignored, he said that despite the current crisis and its causes that we should not "throw the baby out with the bathwater" and added that Taleb "...is not only able to recognise a cow but also knows how to milk one."
Giovanni said that financial mathematics has much to offer and that whilst VAR is simply a number, one of its great benefits has to make one measure of risk simple and compelling enough to get traders and risk managers talking.

Paul Wilmott then took the floor and put forward his thoughts:

On Taleb and the Black-Scholes Model

Paul mentioned that he and Taleb were great friends, and whilst he agreed with much of what Taleb says he has areas of disagreement, particularly over the use of the Gaussian distribution in finance and its implications for "fat tail" events
Paul Googled "Taleb" and found more entries for Taleb than for Stephen Hawkin which shows how much attention had come his way due to the "Black Swan" debate
He thinks that he and Taleb are the "Marmite of finance" (for those of you not in the UK who do not know Marmite, it is a sandwich spread that you either love or hate, never anything inbetween)
He suggested that every quant needs a much more fundamental and practically grounded understanding of financial mathematics.
Paul refered to some work (mentioned by Giovanni) that Peter Carr of Bloomberg had done on discrete daily hedging that showed that this option replication technique could remove up to 85% of the risk and that all quants should know about this 15% error term when trying to calculate an option price to the Nth decimal place.
He described how in the past he had set up a volatility arbitrage hedge fund, wanting to improve upon the flawed assumption of the Black-Scholes (B-S) model that volatility is constant and to build the world's best volatility model for option pricing.
Paul said that he did build the world's best volatility model (?!), but soon found it took too long to calculate, so he reverted back to B-S and has become an unfashionable fan of the model and its assumptions.
He added that many of the variants on B-S to overcome its limitations have made the model worse and harder to calibrate.
In some part due to Taleb's opinions on fat tails of distributions, B-S and other models are now very unpopular but Paul claims that not many people have actually bothered to robustly test the B-S model or take a practical, evidence based approach such as that adopted by Peter Carr.
Paul then showed some example charts and said that with a limited number of opportunities for regular time-period hedging it was not valid to use risk-neutral pricing whereas if the same number of hedges could be used optimally (implying at irregular time periods) then risk-neutral was valid and hedging could be more effective. He emphasised that this was the kind of practical stuff that a quant should know and that quants show know less about esoteric complex financial mathematics.

Correlation

Paul said that of all of the issues that need addressing in mathematical finance, the one that he has very few answers on is correlation.
He showed that even basic questions about correlation are poorly understood, even by quants - a question he asks some quants was that if two asset prices both start out at 100, and they have a correlation (of returns) of 1 (perfect correlation) what is the price of the second asset after a year if the first moves to 200. The answer is not 200, and he showed how assets could diverge in overall direction but still have a correlation of 1 or rise together with a perfect negative correlation of -1.
Paul illustrated how correlation was a very blunt measure that is mis-used by people to summarise the highly complex and historically unstable relationships between assets driven for example by industry sector success (leading to +ve correlation) or competitive success (leading to -ve correlation)
As a result, he said that financial products whose value depends on correlation should not be transacted in any great size and moved on to the example of CDOs, where a CDO with 1,000 underlying mortgages has been modelled with 1/2 million correlations all assumed to be 0.6. Why this assumption should be made was his main point.

Sensitivity to Parameters

His main point here was that a constant should not be varied, otherwise it is not a "constant", in particular focussing on volatility used in the B-S model and the calculation of Vega as prices are moving.
Paul added that sensitivity measures may apply locally and is such may look comparible from one situation to another, but quants need to understand how outputs respond over a wider range of inputs, and not to be inhibited by accepted practices and beliefs.

Complexity

Models need to be robust and transparent, and that quants should aim for the mathematical sweet spot.
Paul put forward the following analogy that at least when driving an old car over a long distance, you knew that the car was likely to break down at least once, but you also knew that it was likely that you could fix it. Contrast this with driving a modern sports supercar and finding that it has (unexpectedly?) broken down - you don't know how to fix it, you do not complete your journey and it costs you an ordinate amount of money to put things right...

Self-Referential Feedback

Paul described here how the hedging of derivatives contracts in the underlying markets can cause price movements in underlying markets that cause derivatives contracts to re-price that cause more hedging in the underlying markets...
He was critical of credit derivative pricing as being too complex and too "mathsy" (...but had to admit that he had also endorsed some of this work at the time)

Calibration

Paul said that model parameter calibration is the devil's work...
He refered us to inverse problems in mathematics as a background to this issue in mathematical finance.
He emphasised how markets and price behaviour is fickle and driven by human opinions and behaviours
He said that on-going and regular re-calibration of a model is very, very likely to mean that the model is wrong (he had a particular example of calibrating a particular model he hates where vol is a function of underlying price and time.

David Rowe, Sungard's specialist spokesman on risk management, then took over from Paul and set out his five topics for discussion:

Statistical Entropy - fundamentally that information can only be extracted from data, with the emphasis on extraction of information (from that already in the data) rather than creation of new information.
Structural Imagination - that we need to be aware of how the market assumptions we make are themselves a model and that we need to spend more time on thinking about what could happen outside our current understanding or market experience.
Self-Referential Feedback - the feedback loops in pricing, risk management and economics
Complexity and Dark Risk - when you add (untested) complexity of a model to limited data sets you get a recipe for disaster.
Alternate Means of Valuation - when the primary means of valuing a security is not available (illiquid markets anyone?) then what is the secondary means of calculation value.

Some further notes from David's talk:

AAA rating should imply a failing once every 10,000 years, with some super senior CDO tranches being rated as better than AAA - David pointed out that even as recently as the early 1990s there were problems in the US housing market that indicated that AAA did not mean what it was taken to mean.
On structural imagination, David said that quants and risk managers must look for unrepresented variables in a model and track them early to monitor their effects
On feedback he cited an example where increased returns drove product innovation which drove up (CDO) volumes, which caused underwriting standards to fall, that allowed further complexity, that then led to unreliable risk estimation which then led to more product innovation... and so on.
He suggested that quants adopt the "second means of valuation" mantra in a similar way to credit specialists always having the mantra when assessing credit of "what is the second means of repayment" (e.g. a lien on a house) when the primary means (mortgage payments) goes away.
David showed a nice classification from an IASB paper on classifying financial instruments:

Level 1: fair values measured using quoted prices in active markets for the same instrument.

Level 2: fair values measured using quoted prices in active markets for similar instruments or using other valuation techniques for which all significant inputs are based on observable market data

Level 3: fair values measured using valuation techniques for which any significant input is not based on observable market data

David additional proposed the interesting level of "Level ?" for some products, and said that obviously more attention needs to spent on Level 2 and 3 instruments under conditions of reduced (non-existant?) market liquidity.

Summary Session:

Paul and David then answered some questions from the audience:

Paul said that some risk managers lacked the imagination necessary for good risk management, being confined in standard procedures, beliefs and ways of doing things. He wants risk managers who are good at thinking laterally.
Paul said that risk management was often an afterthought, not part of the trading process.
David said that VAR has proven useful despite its weaknesses, in his opinion preventing failures from non-extreme events regardless of the recent extremes
David said that in answer to Taleb's criticism of using history in modelling, it quite frankly is all we have to go on. He quoted Mark Twain in that:

"History does not repeat itself but it does rhyme"

The talks were interesting, and even on points that have been discussed elsewhere both speakers had some interesting slants and good analogies. But maybe I am biassed, as the wine afterwards wasn't bad either!...

Posted by Brian Sentance | 3 July 2009 | 11:28 am

Over The Counter Arguments

George Soros has waded back into the current saga concerning OTC derivatives in his article last week in the FT. The main part of the article focusses on financial markets reform, but ends with a vehement attack on derivatives, building upon some of his earlier ideas (see post) and seemingly going much further:

"Finally, I have strong views on the regulation of derivatives. The prevailing opinion is that they ought to be traded on regulated exchanges. That is not enough. The issuance and trading of derivatives ought to be as strictly regulated as stocks. Regulators ought to insist that derivatives be homogenous, standardised and transparent."

He ends by saying that "CDS are instruments of destruction that ought to be outlawed.". To the extent that Mr Soros attracts press/political attention is probably something the OTC markets should worry about, although it would seem his views are already consistent with many involved in influencing the US financial markets policy - take for instance the submission by Christopher Whalen to the US Senate on OTC Derivatives:

"Simply stated, the supra-normal returns paid to the dealers in the closed OTC derivatives market are effectively a tax on other market participants, especially investors who trade on open, public exchanges and markets."

Fortunately however there are also some more balanced views around - I found the following post on the "(in)efficient frontiers" blog, which references the earlier Senate submission by Richard Bookstaber on OTCs. Mr Bookstaber starts by saying that derivatives can improve financial markets, allowing investors to shape returns, exactly meet contingencies and package risk. Mr Bookstaber also puts forward a very clear summary how participants have also over recent years use derivatives to game the system to achieve tax avoidance, investment mandate avoidance, speculation and to hide risk-taking.

So back to the Soros article, there was a letter in response a few days later from a partner at the legal firm Ashurst's, saying that unfortunately risk does not confirm to a standard. In this I agree, standardising contracts can lead to increased complexity - there was a recent example given by a swaps dealer at JPMorgan who said that a corporate with particular cashflows to be hedged does want to be dealing with the basis risk and admin of using standardised contracts - the corporate treasurer wants something that matches the exposure they have and takes it away, end of story. Again this is an example of derivatives "risk" not being just about the product type, but also about which institution is holding the contract and what they are using it for (see earlier post).

Not sure however how much the Ashurst's partner who wrote the response letter is worried about lucrative legal fees for OTC derivative contracts dying off if Soros-like standardisation occurs - it is a world of vested interests at the moment, never more vested than in a crisis...

Posted by Brian Sentance | 2 July 2009 | 7:26 am

Risk in the Hands of the Holder?

Given the ongoing debate about "too big to fail" and whether we should head back to the days of the Glass-Steagal Act, then here is a slightly different slant on the problem of systematic risk put forward in an article by Avinash D. Persaud.

In the article, Avinash makes the very good point that increasing capital requirements across the board is not the only response that regulators should consider, and that the risk of a financial product cannot be determined in isolation of who is holding it:

"At the heart of modern regulation is the erroneous view that risk is a quantifiable property of an asset. But risk isn't singular. There are credit, liquidity, and market risks, for instance—and different parts of the financial system have different capacities to hedge each. Thus, risk has as much to do with who is holding an asset as with what that asset is. The notion—popular in the U.S. Congress—that there are "safe" instruments to be promoted and "risky" ones to be banned is deceptive."

Obviously the last point is very relevant to the OTC markets at the moment. Avinash suggests that capital requirements should be tailored to what type of organisation is holding a risk and that organisations ability to hedge it, and outlines past mistakes made by regulators:

"By requiring banks to set aside more capital for credit risks than nonbanks must, regulators unintentionally encouraged banks to shift their credit risks to those who wanted the extra yield but had limited ability to hedge this type of risk. By not requiring banks to put aside capital for maturity mismatches, they encouraged banks to take on liquidity risks they couldn't offset. Moreover, by supporting mark-to-market asset valuations (which make institutions value holdings at their current price) and short-term solvency requirements, regulators discouraged insurers and pension funds from taking the very liquidity risks they are best suited for."

On banks and credit risk, then for those interested there is a good regulatory arbitrage example for credit risk described in the following article. Fundamentally I think the paragraph above illustrates some of the reasons why it is right to worry about rushing in new regulation too quickly - certainly things need to change but when dealing with large and complex systems (i.e. in this case Financial Markets) changes should be introduced incrementally in order to understand how the system responds.

Given the political imperative to "do something" then regulators find it all too tempting to stick their noses in everywhere, even in areas that did not lead us to the current crisis - take for instance the regulatory initiatives over the past year in short selling, hedge fund regulation and more recently the dangers of "dark pools" (at least dark pools sound scary I guess?). Where will the next "bogey man" appear on the regulator's radar and what will be the unintended consequences of government pressure on regulators to keep us all "safe"?

Posted by Brian Sentance | 2 July 2009 | 6:00 am

Liquidity Derivatives - the next OTC?

Given the drive the FSA is making in forcing financial institutions to implement "Liquidity Risk Management" (see background on JWG-IT site) are we going to see renewed interest in the creation of "Liquidity Derivatives" to hedge liquidity risk? I found the following post on the subject applied to hedge funds but not much information else where, although Tony Jackson did an interesting article on liquidity in the FT last week, indicating that liquidity derivatives have been tried before with little success.

I was thinking of the advent of credit derivatives being driven in no small part by Basel II regulation on capital charges for credit risk. Maybe given the current battle going on around OTC regulation (see FT feature today) there are institutions working on liquidity derivatives but nobody in the finance industry wants to admit that they are already creating the next "innovative" OTC to nullify regulatory charges?

Mr Geithner better watch out, innovation will always beat "rules" in my view...

Posted by Brian Sentance | 21 May 2009 | 6:20 am

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