Xenomorph Blog - Risk Management

Posts categorized "Risk Management"

Transparency Regulation is not Transparent.

Decent FT article on the problems with the transparency of stress testing of financial institutions in Europe.

Posted by Brian Sentance | 9 July 2010 | 3:31 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 | 2:22 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 | 8:00 am

XTrakter Conference

I went along to the XTrakter Annual User Conference in London on Thursday - Good event with some great speakers. Angela Knight, CEO of the British Bankers Association, gave a talk to start off the day. Angela seemed a lot less on the defensive than when I have heard her on national radio here in the UK, usually being interrogated by some journalist who wants answers to difficult questions on the financial crisis and the banks role within it.

Angela said that we were in year 3 of the "crisis" with 2008 being about the banks, 2009 being about governments and politics and 2010 being the year of sovereign debt. I guess she enjoyed saying this but that everyone is blaming "Anglo Saxon Banking" for our problems and yet it was not the banks that contributed to the fundamental problems that Greece is facing.

One major theme of her talk was decidedly Euro-Sceptic in tone, which was that the UK idea of internationality and international trade was different from that of Europe. She perceived that in the UK one of our trading parties is Europe, whereas international trade in Europe was more about inter-European and not world-wide trade - I think that there are elements of truth in this but not sure that Germany industry for example would agree that it is not conscious of truly "global" trade? She said that she was concerned by the rules and regulation being put up by governments, particularly in respect of there being too much and in too short a time.

Angela was an engaging speaker and at the very least her opinions prompt reaction, however I have to end this quick post with the best quote of the morning from Anthony Belchambers, CEO of the Futures and Options Association. Anthony said that current frenzy around political and regulatory initiatives to control the financial markets remind him of:

"A bar room brawl, where the brawlers don't punch the person that started the fight, they punch the person they have always wanted to punch..."

Posted by Brian Sentance | 24 May 2010 | 4:11 pm

Counterparty Event

I went along to a morning panel on counterparty data management on Tuesday, sponsored by GoldenSource, Avox and Interactive Data, and hosted by Virginie O'Shea of the A-Team. Counterparty data obviously has a very high profile currently in light of recent events, however the advice from the panel fundamentally seemed to be get the basics of data management right (ownership, control, consistency, quality, transparency), rather than anything radically new.

There was some debate about the possible extension of BIC (Bank Identifier Code) to be used more generally as a standard for a unique business entity identifier - this seemed to be received well but there were concerns that such an initiative would not solve the problem but rather become an addition to the already complex entity-mapping process.

The "Data Utility" from the ECB was also debated, and it was refreshing to here some negative (realistic?) things said about it, such as the concern raised by Interactive that this might involve huge public spend without necessarily understanding why a new government sponsored entity would be able to do better than existing data providers. Obviously a data provider would say that, but I have to agree, it seems there is too much focus on having a data utility and not looking at the different options for solving industry data issues (one option obviously being a data utility, but lets not pre-package the problem with a solution but more of that in later posts...).

For more detail on the event, then take a look at Virginie's blog post.

Posted by Brian Sentance | 21 May 2010 | 10:56 am

The Value in Product Control

Good post from Robert Peston on the BBC website on part that the Product Control Group did (or rather didn't?...) play in the problems at Lehman's, according to the official US bankruptcy report on Lehman's by Anton Valukas.The post highlights the report's findings that the Product Control Group did not have the quant experience to keep up with CDO trading desk.

Interesting findings on Lehman's, but variants on this theme seem to be elsewhere too. A contact who knew Merrill's New York trading operation in the run up to the crisis recently asked me how many quants did I think used to work on the CDO trading desk. The surprising (?) answer was not one...

Posted by Brian Sentance | 21 March 2010 | 5:22 pm

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

Risk, Data Transparency and the MBS Market

I spent the morning yesterday over at the FIMA USA event in New York, and caught the panel discussion chaired by Neil Edelstein of GoldenSource. Stand out speakers were Amy Hawkins of BNY Mellon and John Bottega of the Federal Reserve.

Neil started the panel by asking the panel for their thoughts on the current drive to improve "data management for risk". Transparency and quality were mentioned a lot unsurprisingly, with John Bottega adding that he was aware that a lot of banks were now focussed on the data that in the past had been "not available" for risk management, not just the quality of data that is readily accessible. All panelists focussed on the need to manage risk across the whole institution, not just by product silo.

On the topic of data standards and transparency, John referred the audience to testimony on the Mortgage Backed Securities (MBS) market presented to the US Government by the XBRL group. Apparently the filing process for mortgages allows free format filing and so is of little use from an automated processing point of view. John also pointed out that a key piece of data in assessing risk is that the "first time buyer" flag was found to be present in only 15% of the filings.

John also mentioned that if loans and mortgages could be given standard identifiers, then this would enable new levels of risk management - for instance it should be able to extract those obligations against a specific region that for example is experiencing economic recession. These would be the benefits of getting data standards in place.

As was later expanded upon in a later talk by Kay Vicino of Northern Trust, there was a lot of panel discussion on organisational data governance and the management structures needed to achieve it. On the governance side of things then whilst it is not an exciting topic, it is obviously vital - main point seems to be establishing data ownership and responsibilities which brings me back to the point that a lot of (most?) data management issues are down to managing people and organisational politics, not just down to good technology (although it helps!).

Overall a reasonable panel, and the XBRL testimony looks worth a more detailed read (if the testimony link doesn't work then go to the www.xbrl.org site and search for a report called "Using Standards for Transparency")

Posted by Brian Sentance | 17 March 2010 | 4:42 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

Data Management Panel

Thomson Reuters held a panel event on data management at their London offices on Tuesday last week, with speakers from Barcap, LCH.Clearnet, DB, Mizuho and Citi. This event was held in follow up to their recent report "Beyond Golden Copy". Below are some of my notes on the summary points the panelists made:

The Value of Data - Kris Bhattacharjee of Barcap said that there were currently two main drivers behind the perceived business value of data; i) Regulators are expecting more information, adding additional requirements and conducting more adhoc reporting requests. ii) Business users/decision makers want more granular understanding of trading and risk management data, in order to decide how best to allocate scarce capital to what trading positions.
Data Metrics - Kris said that the metrics were many but timeliness of data was becoming a key metric - over the past two years regulators have moved from allowing say 2 months as a reporting timeline down to 10 days recently. Additionally timeliness is again vital as regulators demand adhoc reporting in response to market events.
Accuracy/Completeness - Again regulators are driving this, with the "bad numbers in, bad numbers out" as the main motivation. Unsurprisingly, counterparty data is also being required at a new level of detail and accuracy down to a portfolio level in light of the crisis.
Granularity of Data - Deeper granularity of data being driven by scarce capital and the need to understand how efficiently it is being used. Basel II has also driven greater granularity over Basel I. Reflecting what I have heard from some our clients, Kris added that the data associated with securitised products had increased greatly as people need to understand exposure/risk and pricing in more detail (rather than assume blanket statistical behaviour for a whole basket of assets).
Stress Scenarios - Kris again mentioned the understanding of counterparty exposure driving the need for new data sets, as had the initiative of banks having "living wills" to allow a bank to be wound down in an orderly manner.
Everybody has Left the Building! - Martin Taylor of LCH.Clearnet was a great speaker and said that the biggest new problem that the collapse of Lehman's created was that ordinarily there are people around to help with extracting from systems what the exposure is to the various counterparties. In the Lehman's case there was nobody around to help, making the process very difficult and leading to the need for changes to address this problem.
Mandating Data Integrity - Martin added that data security, integrity and auditabiliy were vital, and in particular put emphasis on the people that are running the systems that they have their own form of integrity so that an institution knows that the people can trusted but is also capable to deal with a situation where the people are not around to help. Martin felt that this level of data management should be mandated on the industry and that there was an awful lot that finance could learn from industries such as Pharmaceuticals in terms of product approval and management/robustness of data.
Data with No Cost or Value - Neil Fletcher of DB was another good speaker who started his talk by saying that pre-crisis people thought of data as project based, otherwise dealt with it on an adhoc basis and considered data as having no cost or value. Institutions had a spaghetti approach to data, with systems/projects being process not data based i.e. the systems get only the isolated data sets they need only when they need it.
Quality is Now the Data Driver - Neil said that 18 months on from the crisis, then whilst ROI is still important for data projects then quality of data is the key driver.
Sponsorship and Ownership of Data - Neil added that quality data is an asset as are the systems that produce data quality, and to ensure success data management projects needed high level business sponsorship, but also ongoing and clearly defined ownership of all data sets and their quality.
Enterprise Data Virtualisation - Neil said that DB were embarking on a long term project to ensure that all systems get data from the same logical place on a global basis, and that they were investing heavily in data virtualisation technology as a key means of achieving this goal. DB are starting with reference data, moving to transactional/positional data and on to other data types. For each type/category of data ownership would be clearly defined across all systems and would enable real-time transformation of the data into whatever format it is needed in.
Enterprise Data Model - Neil said that as a result of this virtualisation approach then you have to invest in putting together an enterprise data model for all data used in an institution. From my point of view this could be interpreted as a move back to "big EDM" (with all the project risk that implies) but I guess it is being approach on a more staged manner.
Lip Service to Data has Ended - Neil summarised by saying that lip service to data management has ended with the start of the crisis and that 18 months on the enthusiasm for dealing with the data problem has not diminished.
Publish/Validate/Subscribe - Simon Tweddle of Mizuho echoed a lot of what Neil said in approach to global data management and ownership, but added that he believed that the model of publish/subscribe needs to change to publish/validate/subscribe to ensure data quality.

Most of the panelists agreed that bringing in experience from external industries (Pharma, Oil & Gas, Internet Search etc) would be beneficial since we should not assume that the financial market has the expertise to get data management right first time (take a look at this article from the FT for a related idea). Martin of LCH.Clearnet was convinced that mandated data management would come and would be beneficial, which some of other panelists did not agree with and suggested that the industry needs to get ahead of the regulators to head this possibility off. Simon said that the focus on complex data/products was wrong given that the basics (what is our exposure to this counterparty?) were not being done (not sure I agree with this totally, both are needed given the losses from CDOs etc). Overall it was good panel with some interesting debate and speakers.

Posted by Brian Sentance | 8 March 2010 | 2:30 pm

Beyond Golden Copy?

Interesting reading in a survey put together by Lepus and Thomson Reuters and publicised on Finextra this week. Summary findings:

Data management budgets are increasing, with 77% of firms intending to increase spend on data quality and consistency and 32% saying spend would increase significantly.
Tearing down data silos is a key initiative, 70% of firms are looking to revise data management solutions as a result of the crisis, and 31% of firms cited data quality and consistency as the most important driver.
Data management for risk is the top concern, with 87.25% of firms looking to integrate data repositories in risk, and 62.5% saying that they were close/very close.

This seems to be consistent with another article on Finextra this week, with Deloitte predicting a much greater spend on risk management projects. Putting the marketing aspects aside for a moment, I don't think it is abundantly clear from the actual content of the Lepus survey as to why the title includes the phrase "...Beyond Golden Copy" other than the type of data management they refer to seems to have more emphasis on global/firm-wide data integration than your traditional EDM golden copy data warehouse approach.

It is also interesting to hear so much about consistent data across the entire enterprise (driven by risk and regulation) which seems to echo the "big EDM" projects of old that did prove that successful, and to some degree is at odds with what the likes of Golden Source and Asset Control are currently saying about choosing smaller projects to bite off on rather than the enterprise approach. I would suggest however that there is no issue in having smaller projects in mind so long as they are compatible with the overall goal.

The integration and consistentency of data across front, middle and back office was also interesting, and in particular the front office integration echos some of the things I have been saying about the need for analytics management and the management of front office data as part of the data management process, not something to be ignored in the hope it sorts itself out.

Posted by Brian Sentance | 5 March 2010 | 3:28 pm

When is a trade, not a trade?...

...er, when it is a hedge? Adding to my current confusion over just how the Obama administration is going to define just what is and is not "proprietary trading", Gillian Tett of the FT today has put together a good article on some of unexpected effects that such a ban may have - my advice is don't mess with the all-powerful "Law of Unintended Consequencies"...

Posted by Brian Sentance | 19 February 2010 | 2:58 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

RiskMinds - VaR as simple as chartism?

Interesting panel debate at RiskMinds Wednesday morning, entitled "Sophisticated Complex Models vs. Crude Robust Risk Measures".

Riccardo Rebonato of RBS started off the debate in (untypically?) controversial style by saying that he thinks that the risk management models (mostly VaR) used in financial markets are peculiar. Peculiar in that coming from a physics background he is used to models that have "causal" links between inputs and outputs, whereas VaR is based simply on the P&L distribution of a portfolio i.e. all the information is contained in the data itself. Riccardo said the obvious analogy was with chartism, where decisions are made on the observed market data itself without any reference to external (exogenous) factors at all (perhaps he should have a discussion on endogenous risk with Jean-Phillippe Bouchard at Quant Invest). Riccardo suggested that in the range of models from those that are "over specified" with two many inputs to those in "reduced form", then VaR was far too much at the reduced form end.

In response to Riccardo's proposal that risk models should involve more causal ("factor") effects, Andreas Gottschling of Deutshe Bank countered with the quote from Harry S. Truman "Give me a one-handed economist! All my economists say, On the one hand on the other.". To which Riccardo acknowledged that maybe Economists and Econometrics were less suited to trading/analyst reports (e.g. give me a single view of what the prospects/returns will be) and more suited to risk management (e.g. give me a range of scenarios with supporting assumptions for each).

Chris Finger of RiskMetrics moved on to put forward an argument for standardisation of risk reporting, saying that it was impossible to say what methodology was behind the VaR numbers disclosed by major financial institutions. He proposed that risk reporting needed to be standardised and obligatory, but emphasised that risk management should not standardised. Paul Shotton of UBS agreed, saying that whilst micro-prudential risk of Pillar I had decreased risk on an individual institution level, it had increased systematic (macro) level risk and this was an area of failure for the regulators. On this the panel agreed, echoing a lot of what Avinash Persaud said in proposing the more diversity of risk management was highly desirable.

On standardisation, Riccardo noted that many banks had switched from using 10-day to adjusting up a 1-day VaR, and as a result presenting a less risky picture to analysts and regulators, regardless of how risky the "tail" of each institutions' P&L distribution is. Riccardo also proposed that there should be "constructive ambiguity" over what is asked of the banks by the regulators - put another way he suggested the regulators should come up with the "curriculum" for risk but not the "questions", as definitive questions encourage arbitrage.

Andreas then brought the debate back to its title, and put forward that maybe VaR should be replaced by simpler measures such as limits on notional traded. Paul suggested that VaR was only good for simpler products and portfolios, under "normal" market conditions. He said that he had been an advocate of more stress testing for a long time as a complimentary approach to VaR, but also combined with the simpler approach of limits.

It was an interesting debate, particularly with Riccardo's proposal on VaR being too simple a measure based on statistics, and wanting a more "causal" model to be developed. Using the example of June 2007, Riccardo said that everyone knew something big was about to happen but this was not reflected in VaR calculations since they are statistically based and inherently backwards-looking and not predictive. The lack of prediction is a very valid point, but putting forward a counter-view, then I get the argument about economists giving a range of outcomes, but surely these should be fed into the scenario engine rather than trying to develop econometric models of relationships between market variables. Econometric models are just as vunerable as any other to the mis-behaviour of markets (anyone seen a stable correlation lately?).

A few of the other risk managers there expressed other views, from the more buy-side folks who were more comfortable with factor-based modelling, to risk managers who said that VaR was already "structural" with explicit relationships between valuations and interest rate inputs for example. It would be good to understand more of Riccardo's ideas on this, since it appeals from making risk a more "forward-looking" process but I find it difficult to quite grasp what "causal" model you can have of markets that is itself robust to changes in market behaviour.

Posted by Brian Sentance | 11 December 2009 | 4:52 pm

RiskMinds - The Failure of Risk Models

Avinash Persaud of Intelligence Capital gave the opening talk of the morning at RiskMinds (see first of set of posts from last year here) and put forward a lot of the very good ideas that he has contributed to in the recent Warwick Commission Report. Main points that Avinash made:

Regulators were admirably quick in working out where past regulation had gone wrong in focussing too much on micro (individual institution) rather than macro (whole market)/systematic risk.
The regulators then came out with promising papers on counter cyclical regulation and other positive ideas.
These new ideas do not win votes however and do not satisfy the public's desire to punish someone - Avinash called this the "Bad Apple" policy, with "bad bankers, bad products, bad jurisdictions" being the perceived guilty parties.
All past crises have resulted in demands for three things: i) more risk management; ii) more regulation; and iii) more transparency.
These are fine as demands but evidently do not prevent financial crises.
Avinash recalled his work back at JPMorgan in the early 90's when the 4:15 report was produced for Sam Weill, which eventually led to VAR reporting becoming widespread.
He then fast forwarded to the Asian crisis of 97 where he saw the failings of VAR (or rather its widespread use) first hand with all players using VAR which when volatility increased caused an increase in VAR causing JPM (and all) to sell causing markets to fall, increasing vol causing more selling, increasing correlation and leading to what is called the "loss spiral".
In light of the recent crisis, Avinash said the public perception is that bankers created a load of toxic bombs (products), through them at an unsuspecting public and ran away...
...and in his opinion the reality is that banks created a load of toxic bombs and ran straight towards them i.e. this was a failure of risk management where bankers did not understand the risks they were buying and selling.
He then took us back to the 1950's and the formation of modern portfolio theory with Markowitz and Danzig working at the RAND Corporation.
At that time banks and insurers were still separate, with FX and capital controls still in place meaning that not only could the "efficient frontier" of investment portfolios be observed but it could also be acted upon.
Now everyone has the same information everyone can observe the efficient frontier of investment opportunities but cannot exploit or act upon it, since usually everyone moves in (the "herd") and the value observed is changed by this crowded participation in the market. Here he seems to be echoing a lot of what Bob Litterman said at QuantInvest last week over the "crowded trade" and that the barriers to market knowledge and our ability to act on this knowledge have been lowered forever.
Avinash put forward that many of the models we use today assume the statistical independence of decision making process whereas the reality is that the market is homogenous (everyone is thinking/acting the same) and hence these models are invalid in this "crowded" context.
In light of this, the problem of risk management is not about exogenous risk (risks from outside the market, from Black Swan events to normal distributions) but more about endogenous risk i.e. peoples behaviours upon seeing opportunities cause strategic risks. (Interesting given Jean-Phillippe Bouchard at QuantInvest commenting on what makes prices move). Put another way, behaviour is the issue not the financial instruments themselves.
Avinash proposes that risk capacity (the ability of an institution to absorb a particular type of risk) shoudl be thought through more fully, with for example insurance and pension institutions with long-term liabilities having a much greater capacity to absorb liquidity risk than banks, and banks with short term funding being a better position to manage a loan book.
He pointed out that regulation that uses market prices to protect us against movements in market prices is doomed to failure before it starts.
Booms occur due to some perceived "paradigm shift" technolgy leading to dramatically improved risk/return ratios - he cited things such as cars, electricity, rail, dotcom and the mantra from those involved that "This time it is different..." (see "bubble" post from last year)
Avinash thinks the regulators are significantly to blame for the last crisis since they themselves said the latest financial innovations in credit derivatives were making us safer through sharing out risk in the system.
He said that there is no theory for making a complex system "safe" as a whole and that the regulators did not/do not "get" this idea.
Diversity of approach and risks in a large systems (macro financial markets) is our only current defence and regulatory "best practice" has driven conformity not diversity in the market, making systemic risks higher not lower.
So the regulators are themselves creating a homogenised market.
In terms of solutions, he proposes that risk and audit committees need separating so that risk management does not become a "tick box" exercise.
He further proposes that the risk management function is given some capital so that it can place hedges at a macro level for institution (i.e. looking at the resulting risk when divisional risks have been aggregated) - here is proposing moving to risk "management" as opposed to the much more common risk "reporting" found in many institutions.
One risk management indicator idea he proposed was to put a portfolio management model together that was linked to VAR in order to see where the "herd" is moving to (e.g. low vol, high return Asian markets of the past etc) and to move or hedge against this.
He is concerned that applying Basel II regulation to the Insurance industry with Solvency II will mean that all players will be dancing to same VAR tune which will introduce more risk as more institutions are forced to react in the same way to market movements and volatility.
On the same lines, Credit Rating Agency regulation will create barriers to changes in ratings methodology in response to endogenous market risk, again meaning that everyone will be forced to behave and act in the same ways.
He summarised that "endogenous risk" (movements in the market caused by the market) and not statistical distributions that are the key issue and diversity is the only solution.

Entertaining speaker with some interesting ideas that fly in the face of much of what is being done by the regulators today, and generally well received by many of the risk managers present. Behavioural finance and the "crowded trade" (i.e. everyone doing the same thing in the market causing movements within the market) seem to be key themes occuring in a lot of what academics and practitioners have said on risk management recently. Now what to do about it? Not sure that less (not more) regulation will find many fans at the moment...answers on a postcard please!

Posted by Brian Sentance | 8 December 2009 | 10:04 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

Views on Fair Value...

Busy week last week for events in London, this time over at the Goodacre / Six Telekurs on Thursday morning. Guy Sears of the IMA was chair of the event, and the event did have a "buy-side" focus to it. Richard Newbury of Six Telekurs started the event and made the following points on the current state of regulation:

UCITS IV - Richard cited the stats that there are around 37,500 funds in the EU with average value of approximately $180M each as compared to only 8,000 funds in the US with average value over $1B. Richard said that such a proliferation of funds was costly and the more EU could standardise funds and their ability to be transacted everywhere in the EU the better.
Reg NMS - Richard took a little humorous dig at US regulators when he reminded us that Congress authorised the SEC to form a "National Markets System" in 1975 and so this had taken around 30 years to implement. Whilst Reg NMS is often compared to MiFID, he said that Reg NMS had led to consolidation in the US while obviously MiFID has led to fragmentation in the EU.
Hedge Funds - Both EU and US regulators are looking at the hedge fund industry. He mentioned the battle the UK was having with some of the (misguided?) regulation that the EU is trying to introduce with over 30,000 HF related jobs in London. The new regulation is likely to increase reporting requirements leading to more need for regular, standardised fair value reporting.
Credit Rating Agencies - Richard mentioned how there will be more ratings and more ratings types, and the regulation introduced to ensure the CRA do not fall into the conflict of interest trap.
Data Management - He mentioned the importance of data management within what is happening in the industry and noted how the profile of data management was on the increase.

Mike Jenkins of Ernst & Young tried his best to make the accountancy treatment of derivatives interesting and didn't do too bad an effort but I only took the following few notes from his talk:

Unlike US GAAP with FAS 157 there is no single standard Fair Value (FV) definition in IFRS, and unsurprisingly IASB are addressing this.
Mike spent some time mentioning Level 1(quoted), Level 2 (observable) and Level 3 (unobservable) pricing inputs for securites, taken from the IASB exposure draft ED/2009/5 (also see Rowe in earlier post)

Matthew Cox of BoNY Mellon Security Services then gave his presentation on the difficulties/challenges of providing a valuation service to their asset management clients:

His division often have a "2 hour" window to produce valuations for NAV reporting, often for a 12 midday valuation
Data exceptions for investigation went through the roof this year due to increased volatility (comment: didn't get chance to ask whether the validations set were "normalised" for market volatility i.e. a price movement threshold would not be fixed but rather be multiplied by a factor relating to recent volatility levels)
Matthew was very complimentary about the efforts his team put in to cope with this increase in data exceptions.
He mentioned how many of his clients of established "Fair Value Committees" over the past couple of years, comprised of staff from compliance, risk management, portfolio management etc.
Matthew mentioned the importance of time zones in valuation and the timeliness of data, with the availability of intraday CDS prices contrasting with bonds who price only from the evening close of the day before.

The panel debate was moderated by Guy Sears, and included the above speakers plus Nigel Reynolds from TD Waterhouse):

Matthew said that his division sometimes shared the "consensus" price from other clients when one client is looking for some guidance.
He mentioned that a key timeframe in establishing FV was establishing what is a "reasonable" time frame for sale of a security.
Nigel Cox said that "suspended stocks" had been a real issue over the past year, where the client "context" (position, situation etc) would very much determine what value a client would want assigned to a holding.
Guy Sears suggested that valuations should be provided with a confidence interval and not just as a single price
Mike of E&Y said that this is what full disclosure now requires, other memberrs of the panel suggested this was realistic but not what clients (humans?) expect to receive - they want a single number.
Guy wondered whether it was an issue that one entity might value an asset at a value X whilst another would value the liability at Y (not equal to X)
Mike of E&Y pointed out that this was an issue in that current accountancy rules allow a security to be reclassified from "fair value" pricing to "historic cost" basis - this discretion is being removed in future rule implementations
One member of the audience pointed out that Bloomberg, Reuters and Markit were all trying to extract more revenue from data used for valuation purposes.
Matthew advocated that the market needed more competition between niche data vendors such as Markit and SuperDerivatives to ensure innovation in service and more competitive pricing.
The audience asked Guy of the IMA whether the association should have offered more guidance on fair valuation process and best practice.
Guy said they have provided some, but he advocated that trade associations should not have opinions, since it was not healthy to have the asset management industry collectively herding towards the same valuations.

Well attended event with some good speakers, particularly Guy Sears as host was funny, knowledgeable and kept the other speakers on their toes. I would say the most interesting point was still that "opinions" form prices, opinions formed in the investment/funding "context" of the party with an interest in valuing a security - conceptually this seem to make the asset servicing companies a little uncomfortable since what they are contracted to do is to provide the "right" set of numbers by their clients. Human beings feel more comfortable fixating on a single number than a range of possible outcomes/results it would seem!...

Posted by Brian Sentance | 17 November 2009 | 10:48 am

It's in the news...

I went along to the Forum on News Analytics over in Canary Wharf on Monday evening, organised by Professor Gautam Mitra from OptiRisk / Carisma at Brunel University. We seem to be in the early days of transforming news articles into quantifiable/machine-readable data so that it can be processed automatically/systematically in trading and risk management. It was a good event with both vendors and practititioners attending so was reasonably balanced between vendor hype and the current state of market practice.

As background on what is meant by news analytics data, then for example you might count the number of news articles about a particular company and look at whether the quantity of news articles might be a predictor of some change in the company's stock price or volatility. Moving on from this simple approach (assuming that you are clever enough to be certain about what news is about what company), then you can then move towards assessing whether the news is negative, neutral or positive in sentiment about a company/stock.

The context here is about having the capability to automatically process/analyse any kind of text-based news story, not just those from research analysts that might be nicely tagged with such quantifiers of sentiment (see http://www.rixml.org/ on xml standards for analyst data). The way in which the meaning of the text is "quantified" uses some form of Natural Language Processing.

The event started with a brief talk by Dan di Bartolemeo of Northfield Information Services. I hadn't heard of him or his company before (maybe I should pay more attention!) but he seemed a very solid speaker with strong academic and practical background in investment management and modelling. He referenced a few academic papers (available via their web site) on news analytics, and how news analytics and implied volatility could provide better estimates of future volatility than implied volatility alone. He also made some good points about how investment "models" are calibrated to history and how such models need to adapt to "today" - he put it as "how are things different now from the past?" and put forward the idea of a framework for assessing and potentially modifying a model to respond to the "now" situation. He also suggested that the market can react very differently to "expected news" (having a range of investment "what ifs" planned for a known earnings announcement) as opposed to unexpected information (we are back into the realms of the Black Swan and the ultimate in uncertainty wisdom from Donald Runsfeld)

Armando Gonzalez of RavenPack then began by explaining how RavenPack had become involved in applying text analysis to finance (it seems the subject has its origins, like a lot of things, in the military). RavenPack seem to be highest profile quantified news vendor at the moment, and whilst Armando is obviously biassed towards pushing the concept that money can be made by adding quantified news data to trading models, he said that not many firms are as yet systematically processing news and most people are relying upon manual interpretation of the news they buy/use. Some of the studies Ravenpack have on market news and prices are very interesting, showing how a news event can take up to 20 mins before the market settles on a new "fair" price level for a stock. Additionally, and maybe an interesting reflection on human behaviour, was that in bull markets there are usually twice as many positive stories about companies than negative, but strikingly in a bear market there was still almost equal amounts of positive and negative news - so humans are basically optimists! (or delusional, or just plain greedy...take your pick!)

Mark Vreijling of Semlab followed Armando and suggested that a lot of their sales prospects understandably desire "proof" of the benefits of adding quantified news to trading, but this was a little ironic since most financial institutions have been paying to receive "raw" news for years, presumably because they perceive beneift from it. Mark also mentioned that the application of quantified news to risk management was a new but growing area for him and his colleagues.

Gurvinder Brar of Macquarie then went into some of the practicallities of quantifying and using news in automated trading. He suggested that you need to understand what is really "news" (containing information on something that has just happened) and what is merely an news "article" (like a "feature" in a magazine etc). Assessing relevance of news was also difficult and he added that setting a hierarchy of what kind of events are important to your trading was a key step in dealing with news data. Fundamentally he suggested that why wait for five days for analysts to publish their assessment of a market or company-specific event when you could react to the event in near real-time.

The event then went into "panel" mode where the following points came out:

Dan thought that a real challenge was integrating quantified news with all of the other relevant datasets (market data, but also reference data etc)
Armando picked up on Dan's point by giving the example news about Gillette which at one point was about Gillette the company but then on acquisition became news about the Gillette "brand" which became a part of Proctor and Gamble.
Dan said that a key problem with processing news was also understanding what news was simply ignored by the news wires i.e. we know what is being talked about, but what could have been talked about, why was it ignored and is it (even so) relevant to trading?
Mark and Armando said that the "context" for the news story was vital and that market expectations can turn many "negative" news stories into positive outcomes for trading e.g. the market likes bad news when it is not as "bad" as everyone thought.
Dan made a very interesting point about trading in terms of categorising trades as "want to" trades and "have to" trades. He gave the example of a trade being observed that seemingly has no news associated/prompting it - so does this mean the trade is occuring because somebody "has to" make the trade (a fund facing an welcome client redemption for example?) or because there has been some information leak to a market participant and such a participant "wants to" make a trade before the news becomes available to the market as a whole.
I think all of the panel members then collectively hesitated before answering the next question from the audience, with Microsoft having one of their "text search" R&D team (think Bing...) asking about news categorisation and quantification.
Dan also mentioned something that I have only recently become more aware of, which is that apart from major markets in the US, most exchanges world-wide do not publish whether a trade was a "buy" or "sell" trade (they just publish the price and transaction size). Obviously knowing the direction of the trade would be useful to any trading model, and Dan referred to this as wanting to know the "signed volume".
A member of the audience then asked whether most quantified news had been based on just the English language and the concensus was that most was based on English, but Natural Language Processing can be trained in other languages relatively easily. A few members of the panel pointed out that all languages change, even English, requiring constant retraining, and also that certain languages, countries and cultures added further complication to the recognition process.
The next question asked was whether the panel could outline the major areas that quantified news is applied in - the answer included intraday (but not quite real-time) trading, algorithmic execution, lower frequency portofolio rebalancing and in compliance/risk/market abuse detection.
A good debate ensued about whether "news" was provided by the official newswires or by the web itself. The panel (and audience) concensus seemed to favour the premise the news wires are the source of news and the web is a reflection/regurgitation of this news. That said, Gurvinder of Macquarie gave the nice counter example of the analysts/news wires not making much of the new Apple iPod, when looking at the web it was possible to see that the public were in contrast very enthusiastic about it.

Overall an interesting event. I think the application of "quantified news" to risk management is interesting - maths and financial theory is very interesting but markets are driven by people's behaviour and if "quantified news" can help us understand this better it has to help in avoiding (some!) of the future problems to be faced in the market.

Posted by Brian Sentance | 12 November 2009 | 12:06 am

Integrated Data and Analytics Management

Xenomorph was one of the sponsors on the “Integrated Data Management” webcast last week, hosted by Inside Reference Data (audio recording available here). There were a number of interesting questions that arose from the Webinar.

One fundamental although somewhat academic question was "What is Integrated Data Management?". Certainly everyone seemed convinced that there would be less "Enterprise Data Management" (EDM) projects in future, given the expense, scope and scale of such projects. The concensus was that whilst the need for data management was better under stood across all financial institutions, data management projects would be bitten off in more manageable chunks by asset type, business function or division (so are silos back in fashion I ask myself?!). Coming back to the original question, I guess my slant on Integrated Data Management is that we are seeing more and more data management projects that have an integrated reference data and market data elements to them, primarily driven by the need to sort out data quality/completeness/depth for use within risk management (in light of the financial crisis).

Related to risk management, a topic I pushed was that given the origins of data management for STP/back office, and given the interest in low latency tick data management/analyis in the front office, there seems to be a market gap (particularly in the US?) on how to manage data such as IR/credit curves, volatility surfaces and other derived data sets. These data sets seem to fall into the gap between what is thought of as market data (primarily just prices) and what is reference data (IDs and terms & conditions). This is another area where a more integrated approach to data management would be beneficial, particularly in making all these datasets available for risk management.

Coming back to a "hobby-horse" of mine, then I also raised the issue that whilst it is fine to be doing great data management (high quality, complete datasets etc) what is the point if all of your data is ignored by the front office and Excel is used to download the data traders and risk managers need from Open Bloomberg. I think the management of unstructured data (spreadsheets, word docs etc) needs to be elevated as an issue since this (unfortunately?) is where most data resides currently, despite what we data management professionals like to think.

I also think that the principles of good data management (centralisation, quality and transparency) could apply to other things and not just raw "data", but what about centralised pricing and valuation, centralised curves and centralised scenarios for risk? Again what is the point of doing good data management if the ultimate "information" (e.g. a valuation) is done using poor quality data, with a complete lack of transparency over the data and model used.

A good question was asked about models, which was that given pricing models and their weaknesses have formed some part of the recent crisis, do we need more complex models. On having a few conversations about this and thought about it some more, then some would say it is complexity that got us into the crisis so this is the last thing we need. My view is that we do not necessarily need more complex pricing models and valuation techniques, but we certainly need more robust ones which does not necessarily imply more complexity. Coming back to a point raised by David Rowe previously, then I think all quants and risk managers should think about a "second means of valuation" for all the theoretical models they use, and that hedgeability (see recent post on pricing model validation) seems to be the common theme in producing more robust pricing models.

Posted by Brian Sentance | 21 October 2009 | 10:32 am

Pricing Model Validation: Mitigating Model Risk

I managed to catch some of the day yesterday at the "Pricing Model Validation: Mitigating Model Risk" conference. I thought it would be worthwhile going along since firstly the past 12-18 months have made model risk very topical (take a look at previous posts from Riskminds, the Modeller's Manifesto and Wilmott/Rowe).

Secondly more of our clients are looking at managing and centralising pricing models/curve calculators in addition to just managing the underlying data (see this Insight Investment client case study for a recent public example). I am calling this "Analytics Management" which is the business-focussed technology stack that combines pricing models/calculators/analytics with all of the "Data Management" underneath. But enough of my thinly-veiled positioning statements...and on with some of the (hopefully) useful content from the conference outlined below - maybe scan the headings in bold below for those talks of interest but I would particularly recommend the ones by Tanguy Dehapiot and Yuyal Millo...

Model Risk 2009 defining and forecasting. First speaker was Professor Phillip Sibbertsen of the University of Hannover on defining and measuring model risk. Phillip started by saying that "Model Risk" was a new category of risk within the confines of "Operational Risk", and that operational risk as defined by the regulators does not yet currently include the "model risk" of market risk and credit risk, nor the "model risk" of the operational risk model itself. (I am sure I could write that up better!...). Phillip put forward that model risk is not formally a "risk" since it has no probability distribution and that he suggested it should be thought of as "model uncertainty". He also clarified that model risk applies both at the large, portfolio scale (e.g. choice of VAR model etc) and at the smaller, instrument level scale (i.e. pricing of derivatives).

Additionally in terms of measuring model risk then he excluded human failure from model risk measurement since in his view this was difficult to quantify - this approach did not meet with the approval of some of the audience were questioning how this could be excluded from a practical point of view. Phillip's colleague, Corinna Luedtke, then presented some work they had done on calibrating different GARCH models to observed data and showing how even a poor model could produce reasonable forecasts of risk if the time period was short. The work was interesting but again the audience highlighted that the human choice (failure?) in choosing the set of models to try was part of "model risk" and should not be excluded from the definition of model risk.

Is a model accurate? Testing the implementation of a model. Second speaker was David Chevance, Head of Equity & FX Model Validation at Dresdner Kleinwort. David outlined the different sorts of model risk: mathematical errors, missing risk factors, divergence from industry practice, model inconsistencies and implementation risk. He then outlined the sources of these risks: bugs, approximations, numerical precision, numerical boundaries and limitations on numerical methods (e.g. Sobol numbers in high dimension monte-carlo simulations).

David said a key area to start with in validating a model implementation was the front-office documentation of the product, its inputs and payoffs, its pricing model but also details of calibration methods used/needed etc. He made the point here that the documentation can sometimes specify just the deal, but sometimes can express the pricing methodology and pricing parameters. The emphasis was on completeness, accuracy and making use of all of the information available in the documentation. Obviously the ability to review the code used to implement the model was also necessary.

He discussed the trade-offs between a simple validation approach in terms of speed and efficiency of resources against the more time-consuming, resource hungry but more accurate approach of full replication of the model. He also suggested that in choosing a method of validation it was important to balance resource demands against what is actually being validated: payoffs from a single trade, a type of pricing model or a family of financial products. Desired accuracy of the validation was also important, given the trade-off between accuracy and effort, and the fact that small bugs are much more common than large.He finally discussed model version control, the necessary discipline of documenting changes and regression tests for new models, and the regular cycle of model review. Overall it was an interesting talk with a good practical focus.

Practical aspects of valuation model control process. One of the most entertaining and interesting speakers of the day was Tanguy Dehapiot, Head of Validation and Valuation, Group Risk Management at BNP Paribas. He started by referring to a few documents "Supervisory guidance for assessing banks’ financial instrument fair value practices", April 2009 (BCBS 153) which was then implemented within “Enhancement to the Basel II framework” (BCBS 157). The first part of his presentation was around these documents and what the regulators expect to be in place, so I guess the best approach is to read them (the BCBS 153 document content is only 12 pages long, quite short for a regulator!)

Tanguy pointed out that in his view "Mark to Market" and "Mark to Model" are often misleading as both are often required. He prefers the term "Valuation Methodology". He proposed four valuation modes: Direct Price Quotation, Use of Similar Instruments, Risk Replication, Expected Uncertain Cashflows (NPV) and categorised a useful hierarchy/matrix of which financial products fit into which valuation mode and for what purposes. Within model risk, he split off judgemental errors (choice of model etc) as part of market risk and credit risk and operational errors (model implementation and coding) as more definable and avoidable parts of operational risk.

He had some interesting slants on data, saying that he had been surprised that even getting all of the static data necessary to price simpler instruments like bonds had proven difficult. He outlined how model parameters are often stored across a variety of systems (curve definitions in one place, pricing methodology somewhere else) implying to me that this is sometimes difficult to pull together and needs some centralisation to improve transparency around this.

His opinion on market parameters (both observed prices and derived data such as implied volatility surfaces) were often stored in a larger central database but warned that this market parameter database needs to be reviewed as part of the model validation process since some of its data is derived (i.e. calculated, maybe using a model!) and as such should not be taken as perfect for all time and for all purposes. He said that it was important to categorise the origin of data and suggested the following types:

Quoted on an active exchange
Actual private transaction in an active market
Tradable broker quotes
Consensus prices from market makers
Non-binding indicative prices from market makers
Counterparty valuation, collateral valuation
Actual transactions in inactive market

Tanguy proposed that there should a valuation matrix for each instrument, where there might a different valuation methodology used for end of day valuation verses intraday, for risk or for trading, for pricing individually or within a portfolio reval. I guess here the rational is appropriateness, efficiency and transparency about what needs to used when. He also added that he disliked the term "Model Validation" since it seemed to imply that a model was "valid" and preferred "Model Approval" to cover the decision to use a model and "Model Review" to cover model analysis. He said he found managing the "stock" of existing models (and keeping up with when to review them) more difficult than managing the "flow" of new models and products.

Overall Tanguy was a very interesting and funny speaker with lots of practical insights and a fair amount of opinion thrown in, which is always good in my view.

The usefulness of inaccurate models: Financial risk management "in the wild". This talk was given by Dr Yuval Millo of the London School of Economics and he focussed on the evolution of the use of the Black Scholes Merton (B-S-M) model at the CBOE and how the model came to be the means by which the whole options market "communicated". Yuyal is a social scientist and prefaced his talk by stating that "Social Sciences are good at predicting the past"

First thing I didn't know (amongst the many things I do not know...) is that the B-S model was not published until a couple of weeks after the CBOE started trading stock options in April1973. Yuyal said that initially the B-S-M derived prices were not accurate at all (around 25% off the market price on CBOE) and that the model was based on assumptions that plainly were not the case on the exchange (only calls available, no short selling, no continuous trading). The model was used by local Chicago trading firms and the story goes that Fischer Black sold large paper "sheets" of option pricing matrices to these traders (there being no calculators/PCs/mobiles around at the time).

As the markets developed, larger East Coast banks entered the market with stocks being held and traded in New York and options being traded in Chicago, so trading became geographically dispersed. This started the need for "early morning meetings" to discuss the market and the B-S-M model and its parameters became the "lingua franca" or means of communication of options market participants.

He described the first years of the Options Clearing Corporation (OCC) which was set up to ensure that the financial obligations of options and buyers were met. Around 1979-80 the OCC worked overnight to calculate margin requirements, based on the (now?) arcane idea that different margin amounts should be associated with different option strategies (straddles, butterflies etc) and the job of the OCC was to take a portfolio of Option and optimise which combination of strategies would minimise the margin required for the whole portfolio. He said that there were disputes between traders and the OCC around margin levels and difficulties for the SEC with updating their Net Capital Rules as each new option strategy was created. Eventually, the OCC adopted the B-S-M model and implied volatility as the means of calculating margin against market value which enabled them to move away from the operational difficulty of strategy optimisation.

So the B-S-M became the way in which traders communicated about the market but also the model became vital operationally within clearing for the market. By 1987 B-S-M had become the de-facto standard for the market, with the model driving the market in turn driving use of the model. During the Oct '87 crash the model proved to be very innaccurate but the use of the model did not diminish - maybe pschologically the market participants needed a model (even a wrong model) to make communication easier.

I found this talk very interesting and members of the audience asked whether any similar analysis was going to be done on the Gaussian Copula model used to price CDOs. Yuyal said that one of his colleagues was undertaking this research currently. Given that he seemed to be very positive about the use of the B-S-M model within options markets I asked whether he had any opinions on Taleb's criticism of fiancial engineers and modelling. Yuyal said that he and Nassim were friends and agreed to disagree on certain topics...

Stress testing modelling parameters. Next up was Peirpaolo Montana, Head of Model Validation at West LB. Having joined the finance industry out of a career in mathematics and then at a regulator, Pierpaulo began by saying that back in the heady days of 2004 the banks thought that their own risk management systems and practices were well ahead of the regulators. He said that in light of the crisis this proved not to be the case but he now feels that this is now more evenly balanced (not sure I would agree, still lots of catchin to do for some institutions I would suggest).

He said that whilst regulators require the validation of risk models and pricing models, and that stress testing of a portfolio is required, that the stress testing of a pricing model is not a requirement and has received much less attention and in his view was not done to much degree before 2007. His point here was that pricing models should work under stress too, otherwise they are a weak foundation for building other risk measures such as stressed VAR.

Whilst focussing on pricing models, he mentioned that risk models also need to be carefully chosen and appropriate to the institution and the types of trading activities it undertakes. As an example he put forward that a simple VAR calculator might be appropriate for a long only equity fund but completely innappropriate for a relative value portfolio.

He said that stress testing had recently received much more attention as a risk management tool and cited the BIS document "Revisions to the Basel II market risk framework" where stressed VAR is introduced as part of the regulatory capital charge calculation. He also mentioned that in order to avoid "standard model" treatment of complex securitised products an institution must be able to demonstrate that its VAR model can cope with these products under times of market stress.

Pierpaulo then described the stress testing of base correlation in CDO pricing, and how even moving the base correlation from its usual level of 70% to 99% would not have predicted the valuations observed in the recent crisis. In this way he says that stress testing of models can detect implementation problems and some model weaknesses, but it cannot assist in coping with structural breaks in the market. He also discussed how the B-S-M model is used everywhere (even places it should not really be valid for) since it is a robust model based on the no-arbitrage hypothesis - in contrast the CDO base correlation and other models are not so robust since they are not arbitrage free.

(end of post!)

Posted by Brian Sentance | 18 September 2009 | 5:30 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 | 7:02 pm

Debt hides volatility from Taleb

Nassim Nicholas Taleb and one of his colleagues are back in the FT today with an article on the "evils" of debt and why the only solution to the economic system's woes is (start the fanfare, this is scary stuff!) the "immediate, forcible and systematic conversion of debt to equity". The main points of the article are that:

Debt and leverage lead directly to fragility in the system whereas equity is robust at absorbing extreme variations in the system.
The economic system is experiencing more extreme events (more "Black Swans") than ever before rendering mainstream economic forecasting useless.
Debt hides volatility as a loan does not vary outside of default whereas an equity investment has volatility but its risk is more visible and as a result more manageable.

I think the last point on debt hiding volatility is quite profound - on a personal basis I would put it into the category of one of those things that you know but it becomes clearer when expressed in a different way, usually (in my case!) by somebody else. Its implications are illustrated particularly well in the following extract from the text:

"Thus debt is the province of both the overconfident borrower who underestimates large deviations, and of the investor who wants to be deluded by hiding risks."

The article is dramatic (as is usual with Taleb, see post) and short on detail of how such a fundamental conversion of debt to equity should happen from a practical point of view. It is nonetheless thought-provoking, particular around the use of flawed economic models being used to get us out of a crisis that the underlying maths helped us to get into, and the consequent proposal that we shouldn't try to model and control the risks of the system but instead endorse equity as the defensive, stabilising shock-absorber of choice. Maybe I should call my insurance broker, I think I need to increase my cover...

Posted by Brian Sentance | 15 July 2009 | 6:21 am

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 | 12:28 pm

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 | 7:00 am

Risk as Sales Support?

Article in FTFM yesterday saying that the risk function is being ignored by asset managers when formulating new financial products.This seems consistent with some recent comments from one risk manager who said that their role was a lot to do with sales support i.e. to convince potential investors that the asset manager has good risk management capability. Given all the discussions on the sell side about the role of risk managers and the risk function, sounds like the debate should open out more onto the buy-side too.

Posted by Brian Sentance | 30 June 2009 | 7:00 am

Liquidity Risk

Our think-tank friends at JWG-IT organised a great event yesterday, with several of the top banks coming together to share their thoughts on what is currently causing them the most pain in implementing the FSA liquidity risk requirements (see FSA Consultative Paper CP08/22 for background).

A few points I took from the meeting:

FSA is moving from a "principles" based approach to regulation to "outcomes" on to "proof of judgement" as the basis for assessing financial institutions
What liquidity stress tests the FSA wants the financial institutions to perform is still far from clear
The above uncertainty is not helping when combined with an implementation deadline of this October
Whether liquidity risk must be managed at the branch or group level is a key unanswered question which has enormous implementation implications
The data requirements are enormous and since a group-wide issue requirements greater central access to data across all departments - unlike traditional market risk which is currently more siloed within each business division
The granularity of data required (down to transactions, detailed cashflows for complex derivatives) is very challenging
Management of intraday liquidity requires real-time cash transaction reporting which is currently not being done/is difficult to do
"Ownership" of liquidity risk implementation typically resides within a bank's treasury function but awareness, ownership and involvement of all departments (e.g. market risk) could be greatly improved

A lot more interesting issues and detail on this meeting plus survey results will be available from JWG-IT soon (see their liquidity risk site)

Posted by Brian Sentance | 22 May 2009 | 3:41 pm

Data Quality and the Future of Risk

A new survey from the Economist Intelligence Unit (sponsored by SAS) of over 300 financial institutions world-side has put data quality and availability as a key issue to be resolved if risk management is to be fit for purpose following the financial crisis:

"Culture, expertise and data are weak points in current risk management"

A summary of the survey report is available here.

Posted by Brian Sentance | 8 May 2009 | 10:31 am

Less risk on the buy-side?

Interesting but counter-intuitive survey results discussed on the Advanced Trading blog, suggesting that risk function has lost status at buy-side institutions.

Posted by Brian Sentance | 6 May 2009 | 10:13 pm

High Performance Spreadsheets

Another article about the operational risk generated by the usage of spreadsheets within the financial markets (see earlier posts), appeared in the April issue of Waters Magazine.

The articles highlights how spreadsheets are largely used within financial institutions and suggests that the current regulation requirements for more transparency and ad-hoc risk management might push the proliferation of spreadsheets even further. The articles also refers to the progress and improvements made by Microsoft in recent versions of Excel to increase the security of spreadsheets.

Xenomorph has worked closely with Microsoft on hosting its time series database within SQL Server 2008. The case study we have written together describes how SQL Server 2008 offers integration within Office Excel 2007 so that whilst the spreadsheet is still the end-user viewing tool, operational risk is reduced by engaging Excel 2007 as an analytics and reporting tool and not as a mean of storing data.

Our TimeScape solution offers more than 700 easy to use add-in functions to Office Excel 2007 and we are currently working on the use of Excel Services, part of Microsoft Office Share Point Server 2007, to further enhance the centralized approach to spreadsheet.

If you are interested in how Xenomorph solves the problem of spreadsheet management, then take a look at our (newly updated) website. Here we explain how to solve the problem and how Xenomorph Spreadsheet Inside technology can bring unstructured spreadsheet data and complex calculation within a centralized data management system, increasing transparency and reducing operational risk.

Posted by Brian Sentance | 8 April 2009 | 2:35 pm

Capital requirements for Asset Managers

Article in the FT today saying that the Financial Services Authority (FSA) has criticised asset managers for poor risk management, and that these failures might force it to impose higher capital requirements on some institutions.

The Investment Management Association (IMA) countered by saying that the FSA guidelines on capital requirements for asset managers were unclear, but also added that as asset managers did not hold client-owned assets on their balance sheets they did not need to hold capital against these assets unlike the banks.

I understand this last point by the IMA, but surely given an institutions fees (aka revenues) derive mainly from fees for managing these assets, surely the IMA is not doing itself any favours by effectively suggesting that the (currently volatile) value of these assets are not relevant from a institutional risk point of view? Poor investment performance leads to redemptions, leads to reduced fees, leads to concerns over institutional stability, leads to more redemptions etc, etc.

Anyway, interesting that this is receiving some regulatory attention and maybe buy-side risk management will soon be moving beyond helping to market and sell the latest investment product...

Posted by Brian Sentance | 30 March 2009 | 11:38 pm

Regulatory Camouflage

My faith in government institutions and the people working for them has been restored by Martin Wolf of the FT when he pointed out an excellent paper "Why Banks Failed the Stress Test" by Andrew Haldane of the Bank of England. Reading this is a complete contrast to my experience at the FSA presentation on stress and scenario testing the other week (see earlier post).

The paper ends by putting forward five proposals for improving risk management:

Better Scenario Definition - Regulators defining multi-factor scenarios for the industry that are truly representative of extreme tail events.
Regular Scenario Evaluation - A common set of scenarios evaluated and reported upon to the regulators on a regular basis.
Second-Round Stress - Making sure that the consequencies of stress testing for individual institutions can be evaluated for system-wide risk.
Active Management of Risk - Ensuring that management take and can explain actions that provision for the risks identified, and do not simply passively report on risk levels.
Transparency - Access to institutional stress testing results by regulators and potentially by the market as a whole through annual report and accounts.

In addition to solid content, Andrew Haldane writes a good story, and I love the usage of "regulatory camouflage" in the serious point below:

"...is that stress-testing was not being meaningfully used to manage risk. Rather, it was being used to manage regulation. Stress-testing was not so much regulatory arbitrage as regulatory camouflage."

Posted by Brian Sentance | 23 February 2009 | 7:11 am

A lottery of bonuses

Another application in an FT article of the long-dated option strategy (see earlier post) this time to discredit the UK Government's attempts to limit the risk of the short-term bonus culture in financial markets. The article is funny and makes a lot of sense, but the need to "do something" for the outraged public will unfortunately mean that not many politicians will take any note of it.

Posted by Brian Sentance | 20 February 2009 | 5:12 pm

Data management, derivative analytics and the spreadsheet

Interesting article out doing the rounds on the newswires announcing a forthcoming report called "The Enterprise Spreadsheet: Pushing towards Transparency" by the analyst firm the Tabb Group. It is great to see an analyst firm acknowledging the importance of spreadsheets within the markets, particularly in the area of combining data and analytics together in OTC derivatives management (see earlier post).

Adam Sussman of the Tabb Group reckons that despite its shortcomings, Excel is a valuable tool: “Spreadsheets, either alone or in conjunction with other components, can meet the same requirements as a business application.” In this he seems to be agreeing with the UK Regulator the FSA, who have been recently advocating that spreadsheets and spreadsheet data needs actively managing as an institutional resource. The findings of the Tabb Group on management also seem to echo a recent report called "Buy-Side Data Management in a Changing Landscape" done by Lepus for Asset Control (registered link to report here).

Spreadsheets are a great tool and fulfil a real need in the market to pull together pricing models and data quickly, easily and with a timeframe that is meaningful to the business (see earlier post for some work by Xenomorph in this area). Spreadsheets are a big problem to manage, but they are also the symptom of failings in core systems that are not able to rapidly support new instrument types and pricing models. An institution that ignores analytics, spreadsheets and spreadsheet data within any EDM transparency initiative has already failed before it begins, and so to paraphrase the author Aldous Huxley:

"Spreadsheets do not cease to contain data because they are ignored."

Posted by Brian Sentance | 13 February 2009 | 2:54 pm

The Respect Scenario from the FSA?

The presentation by the FSA last night on their consultative paper called "Stress and Scenario Testing (CP 08/24)" was a real disappointment last night. The presentation was at best average, not adding any more value than what you could get from scanning their paper. However, what was worse was the Q&A session at the end, with a variety of questions from the audience being answered by the FSA representative with "Thanks, that was a very good question and I will get back to you on it...".

The organisers (ISDA and PRMIA) had managed to get around 200 risk managers to attend which was an impressive turn-out with only standing room left as the event started. I would suggest if the FSA want more feedback from the industry it would be better if they would send someone along who is at least able to add value to the conversation. Their representative last night was doing his best but was just too junior, too inexperienced and lacked the confidence to answer questions in a meaningful manner.

Regulators are telling everyone to "raise the bar" on standards at the moment - they would find it helpful if they would apply this mantra to themselves and the people they put out as representing their views and expertise.

Posted by Brian Sentance | 11 February 2009 | 10:07 am

The "Bubble Index" Cometh...

Seems like my idea of detecting and hedging against future economic price bubbles via a "bubble index" (see last paragraph of earlier post) is maybe not so stupid as I might have thought judging by a letter in the FT today. If only innovation were more popular at the moment, it might have commercial legs!

Posted by Brian Sentance | 4 February 2009 | 12:16 pm

Risk Proposal from Roubini

Article in the FT today by Lasse Pedersen and Nouriel Roubini (somewhat accurate predictor of some of our current problems) on regulatory captical and prevention of another crisis. Pedersen and Roubini say that current regulation focuses too much on individual bank risk and does not consider the systematic risk that could be caused by the failure of an individual bank. They propose the introduction of a new systemic capital requirement and systemic insurance programme, although in this article do not present too much detail on the mechanics of the "systemic risk" calculation. More detail can be found at their NYU Stern project on restoring financial stability.

Posted by Brian Sentance | 30 January 2009 | 2:18 pm

Underrated, Overrated

More flak for the ratings agencies in the FT today with the article "Warning: rating agencies can do you harm", suggesting that agencies have moved from under-assessing risk (and causing financial damage in the process) to now cautiously over-assessing risk (and causing financial damage in the process).

The recent downgrading of Greece, Spain, Portugal (and potentially Ireland) won't gain them any political friends in the EU review of their role in the markets - all recent news seems to lead to "tails you lose, heads you lose" for these institutions and points to further trouble ahead...

Posted by Brian Sentance | 23 January 2009 | 3:31 pm

Happy Birthday Spreadsheet!

Article on PCMag saying that the spreadsheet is 30 years old. Whilst wishing it a happy birthday, the author, John C. Dvorak, has a good rant about how spreadsheets have been the major weapon in the rise to power of the accountant in business.

Good job he did not spend too much time looking at their usage in financial markets or else his rant would have been much longer, given past issues with spreadsheets in financial markets. The spreadsheet (which means Excel at the moment) is a great tool that is:

a calculator;
a report writer;
a database

In my view it is the latter usage of desktop spreadsheets to store data where the problems mainly reside, not its usage as an analysis tool. Faced with inflexible trading and risk management systems that do not allow instrument and trade data to be represented quickly or correctly, it is unsurprising that traders, portfolio managers and risk managers resort to spreadsheets as the "pressure relief valve" for their business activities.

Delivering systems that can support both complex and non-standard instruments and trades in a transparent manner should be a focus in a world where that the lack of transparency over credit derivative pricing has been such an issue. The inappropriate usage of spreadsheets is a very small part of the current problems we are experiencing in the markets, but addressing this would be a positive step in creating a data management foundation that encompasses all data used by a financial institution, not just that data that is easy for software vendors to represent in their systems.

Anyway, enough of my spreadsheet hobby-horse, for some light relief and to celebrate 30 years of summing rows and columns, take a look at the Eusprig web site for a list of the most notable spreadsheet failures.

Posted by Brian Sentance | 15 January 2009 | 6:42 am

Financial Modeler's Manifesto...

Echoing all of the recent focus on model risk at the RiskMinds event before Christmas (see earlier post), Emanuel Derman and Paul Wilmott have put together "The Financial Modeler's Manifesto" as their serious but amusing guide to how financial modeler's must conduct themselves in future.

I particularly like the self-effacing summary oath for financial model-makers everywhere:

The Modelers' Hippocratic Oath

~ I will remember that I didn't make the world, and it doesn't satisfy my equations.

~ Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.

~ I will never sacrifice reality for elegance without explaining why I have done so.

~ Nor will I give the people who use my model false comfort about its accuracy.
Instead, I will make explicit its assumptions and oversights.

~ I understand that my work may have enormous effects on society and the economy,
many of them beyond my comprehension.

Posted by Brian Sentance | 14 January 2009 | 3:47 pm

Libor no more...

Following the ongoing story of Libor diverging from the OIS rate (see earlier post), Risk magazine reports that Libor risks losing its place as a funding benchmark. Spreads against the OIS have tightened recently (see recent article in the FT), but Mustafa Chowdhury, head of US interest rate research at Deutsche Bank in New York, says that Libor is becoming less relevant as a benchmark due to banks accessing other sources of funding such as Federal Reserve Funds.

Time to change all of those benchmark yield curves across the entire institution and understand all of the pricing differences? Ouch! Maybe wait a while yet...

Posted by Brian Sentance | 14 January 2009 | 2:38 pm

RiskMinds - DB on reforming the financial markets

Hugo Banziger, CRO of Deutsche Bank, gave a presentation on his ideas on how best to reform "The Global Financial Architecture".

He started by emphasing:

The economic imperative to resolve the current crisis for the benefit of all people, not just the financial markets.
That the current crisis is very close to the crisis of the 1930s (he did his PhD on the Great Depression, so he should probably know).
He has been involved in the rescue of 3 banks recently, and said that one major German financial institution was only 6 days away from insolvency before it was saved.
His opinion that letting Lehman go was a bad decision that has worsened the crisis.
That without goverment help the financial markets would have gone into meltdown and that this state of affairs is totally unacceptable for the industry.

He proposed action in three areas:

Monetary Policy - Governments and central banks should pay more attention to the interaction between monetary policy and global capital flows. Central bank policy should also consider targetting how to prevent asset price bubbles as well as more standard measures such as inflation (Comment: maybe my bubble index idea wasn't so stupid?). Emergency liquidity provision also needed a rethink in light of past failures.
Regulation and Supervision - Capital requirements should be increased and capital calculations need redesigning to reduce pro-cyclical aspects so as to provision in the good times for the bad (Spanish regulator had already done this apparently). Capital calculations should be calculated over longer time periods (30 yrs?) using the worst of events from the past. Scenarios need adding into the capital calculations so they are not just probabilistic in nature. Regulators should insist upon better transparency and disclosure, in particular on valuation methods and the methods of the Credit Rating Agencies. Ultimately, regulation needs be co-ordinated on a global basis given the global nature of the markets.
Private Insitutions (the Banks) - Appalled by the lack of integrated risk management at many banks, and clear governence of the risk is essential. IT systems should be robust and centralised access to data to calculate exposure is essential. A typical cost of $200m to implement Basel II indicates to him that basic technology infrastructure is not in place and good risk management cannot be being done. Having data in spreadsheets and reporting to regulators with a 3 month timeframe is not good enough and the industry needs to get the infrastructure in place to properly handle and report in a timely manner upon the risks it is taking. He proposes that each bank needs to get a diversified and stable funding base in place - DB issued long term funding recently to reduce dependence on short-term sources and has $65b in reserves, so (maybe at the risk of sounding smug) he believes DB is well positioned.

Interesting talk, Hugo risked coming across as a little smug in the presentation but did admit that DB had faced problems too (but just not as bad as most other institutions though!).

Posted by Brian Sentance | 11 December 2008 | 1:37 pm

RiskMinds - insurers on the crisis, risk managers (and suicides...)

Panel debate amongst CROs from some of the big insurers and the FSA. Main points:

Summarised the current crisis as "A collective failure of imagination over the scenarios of what is possible by risk managers and regulators"
Insurers are doing better than the banks in the current crisis, and this is due to learning from the bad experience insurers had in 2002 following the collapse of the dot com bubble.
Quants are not to blame for the current crisis - they are involved but the current liquidity crisis is not a quant issue (Comment: but surely the collapse in asset prices from poor modelling is what led to the collapse in confidence and onwards to the liquidity crisis)

Joachim Oeschlin, CRO of Munich Re said that at a recent panel event he asked a group of risk managers what had been the failings of risk management, was it:

Risk managers enjoyed the credit party like everyone else?
Risk managers did not see the bubble coming?
Risk managers did not have enough power?

The response from the risk managers was the latter (unsurprisingly!) but he favours the first two explanations above. Joachim said that Munich Re had been looking at how their company performed in the Great Depression of the 1930s. It seems that we should be thankful that we have personal bankruptcy laws these days, as one thing he noted was a great increase in suicides in the 1930s as people who owed too much money simply killed themselves...maybe we haven't got it so bad after all. Crisis? What crisis?

Posted by Brian Sentance | 11 December 2008 | 1:24 pm

RiskMinds - Model Risk and Variable Dependency Assumptions

Professor Paul Embrechts gave the opening talk this morning on quantitative risk management. Main points:

Paul thinks the largest recent failing is to take VaR for granted - he says that it is only a statistical estimate that has a range of values based upon what assumptions are made.
Related to the above, whilst improving quantitative risk management is vital he states that risk management is about human judgement.
He sees "pricing model uncertainty" - the risk that a model for pricing an instrument is badly formed or based on poor assumptions - as a key risk to be addressed going forward (echoing VaR post yesterday)
On pricing model uncertainty, he pointed out what the regulators are proposing with the recent consultative document from the Basel Committee on fair value calculation practices (click here). This covers things like assessing model sensitivity under periods of market stress, challenging of models, understanding of suitability and appropriateness etc.
On the incremental risk capital charge guidelines from the Basel Commitee (click here) he raised concerns that a calculation for market risk with a VaR of 99.9% over one year was both very difficult to model and very difficult to backtest (without lots of good data being available, which is not usually the case).
He ended by spending some time on the re-occuring theme of variable dependency (leading to a lack of expected diversification) and illustrating it with a simple example concerning summations of VaR levels from different business lines at a bank.

Good speaker - main points/concerns were the validity of pricing models and dependency assumptions between variables.

Posted by Brian Sentance | 11 December 2008 | 12:55 pm

Stress-Testing Consultation by the FSA

The FSA published a consultation paper on stress-testing yesterday (click here to view).

Posted by Brian Sentance | 11 December 2008 | 5:39 am

RiskMinds - VaR is not dead at Citi

Very good and refreshingly open presentation given by Alan Smillie of Citi Group on whether Value at Risk (VaR) has been discredited as a risk management tool (see earlier post for Taleb on VaR).

He started by generically describing VaR as being composed of both:

A statistical model of the market
Pricing models/sensitivities to translate the market movements to P&L

He said that much of the recent losses/write downs at Citi are in ABS CDOs at levels of 10x/100x larger than those predicted by the VaR models that they use. He summarised by saying that whilst VaR has not performed well, it should not be dismissed since their experience is that their losses (and inaccuracies in VaR calculation) were not (mainly) due to failings in the statistical model of the market, but rather in major failings in the pricing methodology for pricing ABS CDOs.

It seems that the traders and risk managers at Citi regarded ABS (Asset Backed Securities, mainly mortgages) as equivalent to a bond, and so they regarded an ABS CDO as equivalent to a CDO of bonds. In fact the ABS was itself a securitised product, so effectively they were dealing with a CDO of CDOs (CDO^2). This did not offer the diversification of risk to justify the AAA rating given to the ABS CDOs - apparently the ABS prices in each CDO were 90% correlated. Alan clarified that given the problem was in the pricing model, not in the model of the market, better scenario analysis would not have helped Citi to avoid these losses either.

Alan refered back to an article in Risk magazine in 2006, saying that banks were not experiencing any "exceptions" (breaches of the VaR loss level) at the level that should be expected (2 to 3 per year for 99% VaR). The article suggested that banks were therefore being charged too much regulatory capital and this should be reduced. He said that Citi experienced 20 VaR exceptions in 2007, and expected much more in 2008 and as such VaR is not working well given the current market volatility.

He expects that future risk capital calculations required by the regulators will be based upon VaR combined with subjective, non-probabilistic stress testing (apparently something that Deutsche Bank have been doing internally for years according to a later speaker). He didn't seem to address the issue of how to avoid pricing model risk, but it was a good talk with a lot more openness over Citi's losses and problems than I expected.

Posted by Brian Sentance | 10 December 2008 | 5:29 pm

RiskMinds - Robert Merton

Robert Merton gave the opening talk this morning on the subject of sovereign wealth funds...and immediately digressed into talking about the current credit crisis. As with Shiller yesterday, he is advocating more and better financial theory that has learnt from recent problems rather than saying the mathematics is invalid. He was heavily critical of the pricing models used for CDOs and the like (more of which in a later post).

An interesting point was that he reminded the audience that vanilla loans and mortgages contained embedded put options on the assets of the issuer, and that as a result the recent dramatic decrease in value of this kind of instrument is not purely due to ten sigma movements in markets, but rather lower movements in market variables but combined with greatly increased sensitivity (delta) to these inputs as markets decline and become more volatile. Put another way, he does not hold with the fashionable premise of the Black Swan of extreme events explaining all that we have been experiencing.

On sovereign wealth funds, he suggested that they should concentrate on their unique advantages as investors/counterparties in the market, such as credit worthiness and access to liquidity, and focus much less on stock picking and timing to allocate investment (he cited recent investments in US investment banks by CIC as an example). He proposed that sovereign wealth funds should sell that which costs them nothing (e.g. liquidity) and that others needs. He ended his talk by suggesting the sovereign wealth funds may (only may) step in to fill the gap left by the dramatic downturn in hedge fund activity in the market, as he classified both types of institution as "lightly regulated" and able to get around the "institutional rigidities" faced by the banks. So maybe the sovereign wealth funds are not the international bogey-men that the press have been making out recently?...

Posted by Brian Sentance | 10 December 2008 | 3:48 pm

RiskMinds - from Blame to Bubble Indices...

I am attending the RiskMinds Conference in Geneva this week. Given what has happened over the past year, its somewhat intellectual name seems less appropriate than it once did, but I guess not many of us are smelling of roses on that point...

Seems to be very good attendance with the main hall full to overflowing for the first full day of the conference - unsurprisingly I think many people are looking for answers (from "what did I do wrong?" to "who can I blame?"). From a quick survey of the attendees, there seems to be no doubt that regulators and the credit rating agencies seem to be the favoured candidates to blame.

Robert Shiller (author of Irrational Exuberance) gave the openning talk on the current credit crisis and what to do about it. He made the point that behavioural finance (stock market pyschology) is becoming much more integrated with financial markets theory, and put forward the positive point that financial theory needs to be expanded to encompass what we have experienced over the past year, not that all financial theory should be thrown away (a jibe at Taleb on this point?)

Much of Professor Shiller's talk was spent on illustrating various "bubbles" in real asset prices in various markets against long run trends, usually involving a comparison with the data of the Great Depression of the 1930's, and an occaisional mention of his book (I haven't read it (yet) but I would guess it spends a lot of time on bubbles too). He is very keen on the democratisation of finance, more particularly of financial advice (it would seem that the FSA has been listening in the UK, with the recent action against commission-based financial advisors).

He also proposes greater usage of macro economic indices and related derivatives to make risks of house price falls, inflation, economic growth, employment etc more transparent to all and to allow easier hedging of these risks. He raised some eye-brows of many banking staff by proposing mortgages whose payments went down when these factors moved against a house owner (with the originator hedging these risks using futures on the indices he proposes). He was not so clear what should happen when these factors went in favour of the house owner!

One thought struck me though the talk, is that if it is relatively easy to illustrate/calculate these real asset price bubbles illustrated by Professor Shiller, then why not go further than just having indices on direct macro-economic variables and have indices based on these "bubble" calculations? If everyone could see that the "bubble" index for a particular risk factor was high then you could hedge your "irrational exuberance" or at the very least there would be a transparent indicator that a market was moving into dangerous price territory. Stupid idea? Maybe, but if it has legs please remember you heard the nickname"Aero" for the cocoa index here first!...

Posted by Brian Sentance | 9 December 2008 | 10:42 pm

A couple of rants and a bit of humour...

Busy day on the FT yesterday. First Taleb continues his campaign against VaR and mainstream financial mathematics (see earlier post). Second the CDS market is damned by John Dizard. And on a lighter (but related) note, Jonathan Davis updates us on the behaviour of the fickle "Mr Market family".

Posted by Brian Sentance | 9 December 2008 | 6:30 am

Unstructured Data Management Anyone?

Good example on Finextra this week of another spreadsheet debacle, this time involving Barclays and Lehmans (see article).

Not sure when the financial markets will get serious about managing unstructured data and spreadsheet usage. We can all apply Enterprise Data Management until the cows come home, but if the "real" business is being managed in spreadsheets then really why bother with grand aims like EDM?

Even the regulators are not totally against the usage of spreadsheets (see presentation), then simply want unstructured data to be managed properly as part of an institution's formal processes and not ignored until the inevitable problems arise...

Posted by Brian Sentance | 20 October 2008 | 6:05 am

Sue the VaRists!

I have just come across an interesting post by Nassim Nicholas Taleb (author of the Black Swan). Taleb thinks that everyone involved in promoting Value at Risk (VaR) as a valid risk management tool should be sued by investors who have lost money in the current financial crisis.

Taleb has been raging against VaR since the mid nineties (click here for more). He says that the widespread acceptance of VaR in the market has encouraged more risk-taking through its weakness in modelling extreme events and their effects. He implies (putting it mildly!) that the VaR "number" has become a surrogate for understanding.

He says he is only too willing to testify in court on behalf of investors againsts anyone involved in developing risk measures for the market - seems like the enemies of the VaRists are at the gates...

Posted by Brian Sentance | 12 October 2008 | 4:00 am

Here today. Where tomorrow?

These may be the words on the lips of many bankers today, as they survey the continuing turmoil in global financial markets. In fact, this was the incredibly apposite tagline on a recent magazine advertisement for a major bank which (maybe unsurprisingly) was subsequently nationalised.

In the fluid (many would say “bloody”) landscape of financial services, with the next merger or acquisition just around the corner, it means that now, more than ever, data integration is a growing challenge. Accompanying this activity is the ever-growing need for consistency, accuracy, transparency and control of both the data itself and the movement of that data.

Data architecture itself is an evolving discipline and one approach worth looking at is data federation – deftly described in an article by Dain Hansen. Basically, the approach is to leave the data where it is but aggregate it into a single view, available as a service to your applications. It is an approach that Xenomorph has advocated for many years, going back to our founding days in the mid-90s, with the normalized database driver approach implemented in our Connectivity Services.

Hansen’s article explains both the advantages (simplicity, no need to copy or synchronize) and the disadvantages (performance) of this approach, and argues for a solution that incorporates both federation and consolidation of data. He shows that it is possible to architect a system that will provide consistency and control as well as agility.

It’s difficult to say whether better data management would have assisted the world’s banks in avoiding their current troubles, but greater transparency of where exactly their exposures lay would certainly have helped.

Posted by David Winson | 1 October 2008 | 6:28 pm

No market concensus for Libor?

The debate on how to set/define Libor continues:

http://www.ft.com/cms/s/0/9b89fe4e-301a-11dd-86cc-000077b07658.html?nclick_check=1

Posted by Brian Sentance | 2 June 2008 | 2:52 pm

Crashmetrics for Greenspan?

Interesting article by Alan Greenspan in the FT today (http://www.ft.com/cms/s/0/edbdbcf6-f360-11dc-b6bc-0000779fd2ac.html). One of a number of recent articles pointing at weaknesses in the modelling of risk re: the recent credit crisis - in particular taking putting forward that the human sentiment (e.g. greed or fear of loosing market share in bull market) may well be irrational, but it is systemic and observable and should be considered as a "factor" within risk and economic models.

Greenspan is critical of statistical modelling for risk, saying that the seemingly stable correlation relationships between different assets collapse under times of extreme market stress. Seems like he and a number of other commentators are talking about Paul Wilmott's crashmetrics ideas on correlations - see http://paul.wilmott.com/crashmetrics.cfm for some background.

Posted by Brian Sentance | 17 March 2008 | 3:28 pm

Higher quality data from the front office?

Sungard had a good event on Thursday night, with four risk managers taking the stage for a "thought leadership" seminar entitled "Regulatory Impact of Market Events" (if the advert is still around on their site, see http://www.sungard.com/ADAPTIV/default.aspx?id=4678&formAction=takeit&formid=48)

The Dresdner risk manager (Ted Macdonald, good speaker) was emphasising that data quality is a real issue for risk management, and that all participants thought that risk managers should spend more time on risk and less on validating/cleaning data (no great surprises there then but interesting to hear it validated again as an issue).

He suggested that more pressure should be put on the front office to get data right first time (as opposed to leaving everyone else to sort out the mess!), even going so far as to suggest that charging the front office for each wrongly-booked trade in the trading and risk management systems - not sure how that would go down with the trading desks, but sounds a good approach if you could agree (and unambiguously measure) these mistakes!

Seems like transfer-costing is becoming a re-occurring theme - also recently mentioned by a grid computing specialist from Credit Suisse about "metering" each desk for the amount of compute power used...anyone retraining as a management accountant out there? - sounds like the banks will be hiring soon!

Posted by Brian Sentance | 17 March 2008 | 3:08 pm

« Back to recent posts

Contact us if you have comments. All rights reserved. Trademarks, copyright and legal. Whole site ©1995-2010 Xenomorph Software Ltd. Registered in England and Wales, Reg no: 03235432, Reg at: Waverly House, 7-12 Noel St, London, W1F 8GQ. VAT no: 672584016 - sitemap

Categories

Posts categorized "Risk Management"