Back of the Envelope

Observations on the Theory and Empirics of Mathematical Finance

Archive for the ‘Stories’ Category

[Etc] So Long, Marianne

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R.I.P Leonard Cohen

Written by Vineet

November 13, 2016 at 2:01 pm

Posted in Stories

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[PGP-I FM] Efficient markets and behavioural finance

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From the horses’ mouths. Enjoy!

 

And here is the view of a very respected head of a fairly large hedge fund:

Written by Vineet

September 29, 2016 at 5:21 pm

[PGP-I FM] How markets really work

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Enjoy!

Written by Vineet

September 9, 2016 at 9:21 pm

Posted in Stories, Teaching: FM

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[Etc] Finance without spreadsheets

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As part of the syndicated “View from IIMA” series, my article appeared in livemint yesterday . (I just wish the sub-editor had taken a bit more effort to write the blurb than just snipping a sentence off the text, with the first person singular and all!)

Here is the unabridged version with hyperlinks.

Finance without spreadsheets

What is common to Barclays, Fidelity and JP Morgan, other than the fact that they are all large multinational financial institutions? As the regular readers of this daily would probably recognize, all the three have had to face the embarrassment of acknowledging spreadsheet errors amounting to hundreds of millions of dollars.

It has not only been the financial services firms that have been left red-faced due to “Excel mistakes”. MI5, the British intelligence agency ended up bugging hundreds of wrong phones in 2011 due to formatting errors, and the 2012 London Olympics organizing committee oversold 10000 tickets because of wrong ‘data entry’. Such examples abound, just Google ‘spreadsheet errors‘. And by all accounts it seems that people have learned to live with it, and, thanks to regulators, some have even found ways to make money off it.

The Basel Committee on Banking Supervision explicitly instructs banks to have “effective mitigants in place” against errors creeping in due to “manual processes”. The industry has naturally responded, and many risk consulting firms today provide advisory services to manage spreadsheet risk. Not many outside the risk management world would probably be aware, but there even exists a European Spreadsheet Risks Interest Group.

If one looks back at the evolution of spreadsheet software since the days of Lotus 1-2-3, the look-and-feel apart, nothing much has changed in substance. Yes, a user has more tricks up her sleeve and there are web apps to work in groups now, but, fundamentally, the data in Microsoft Office Excel is still organized and analysed in a tabular form.

The first version of Excel dates back to 1985, and what is astonishing is that for almost 30 years much of the corporate world has been using versions of the same software sold by one firm. As a comparison, despite the market share enjoyed by Maruti Suzuki Ltd, its cars today are no longer the obvious choice for most upper-middle class Indians, and one would have thought loyalty would matter more for automobiles where after-sales service network is valued. But in the corporate world, the larger the organization, more prevalent seems to be the use of Excel.

Now lest this piece be seen as a rant against Excel or spreadsheets, let me admit that I am no anti-spreadsheet evangelist. I used to be an Excel user in my earlier job, and continue to use LibreOffice for quick, back of the envelope calculations. There is no denying the utility of a spreadsheet software, and given the ubiquity of Microsoft systems in organizations, perhaps even unavoidable. It remains useful for prototyping, basic data analysis and teaching elementary statistics, but, in my opinion, it is not exactly suited for large projects and serious scientific research.

As Harvard professors Carmen Reinhart and Kenneth Rogoff found out, despite the quality and substance of their research, a couple of avoidable spreadsheet errors unnecessarily diverted attention from the main message of their work. And then there is the famous London Whale incident. As Mint’s readers would remember, it took more than a year for JP Morgan to get that monkey off its back, and not without its CEO Jamie Dimon having to take a huge salary cut.

I can’t speak for other areas, but use of spreadsheets for quantitative finance – by which I mean portfolio analysis, financial engineering and risk management – is just inefficient, if not outright lazy. Even at the basic level, given the quantum and nature of data involved, it just invites too many bad practices – cell references, manual inputs and copy-and-paste habits, virtually unreadable formulas, unwieldy formatting, multiple tabs and resultant humongous file sizes, over-use of colors with clumsy legends, misleading and ugly graphs, and the list goes on. Yes, I know many of these can be obviated, and existing power users are smart about it, but am not sure beginners appreciate the pitfalls until it’s too late.

More than reflecting problems with any particular spreadsheet software, what these examples illustrate is a lack of context of the scale and scope involved in the choice of computing environment. Working in large projects, with interconnected data and modern techniques, is best done in an environment which facilitates efficient separation of raw data, its organization, analysis and output. A spreadsheet software is simply isn’t up for it.

Perhaps Newton’s first law of motion has something to do with it too, but this inertia in the industry has meant that many business schools continue to predominantly use spreadsheets for quantitative courses. While jobs in the data science and analytics world has meant more acceptance of the programming languages R and Python in ‘elective’ courses, much of the basic curriculum still relies on spreadsheets.

All this, of course, goes back to the more fundamental issue of whether a business school curriculum should be proactive or reactive. As far as the choice of computing environment in curricula is concerned, most business schools have been in the reactive mode, likely because of placement pressures. The students, of course, do not have an incentive to shift and prefer the status quo, as most naturally want to ‘blend in’. The question is whether these arguments hold water in today’s environment of easy availability of MOOCs on all kinds of things quantitative, including free training courses in Excel, R and Python. Not in my opinion.

When it comes to doing complex quantitative analysis and using cutting-edge methods, spreadsheets simply lack the statistical sophistication of R and the power of Python. In fact, both today come with their web apps – Shiny for R and Jupyter for Python – that makes illustrating and sharing applications a cinch, and fun.

An unfortunate response to lack of ability of spreadsheets to do modern statistical analyses in finance has been to purchase proprietary/black-box software, many of which often simply adapt and package the existing freely available open-source programs. This not only results in an inefficient use of a business school’s money, but also leads to perpetuation of bad habits, as for commercial reasons most software try to give their software the look-and-feel of spreadsheets. It is also problematic from a pedagogical standpoint as one is implicitly telling students to rely on someone else’s implementation without worrying about the details. The more courses use such software, stronger this reinforcement to rely on black-box software. To say that ‘my teacher used that’ or ‘US schools do that’ is, at best, naive.

A common refrain against switching to R/Python is that their use requires programming and ‘I am not from engineering/science background’. It is like saying that I do not want to learn English because I studied in a school where the medium of instruction was vernacular. Yes, as with any new language, no denying there is a set-up cost involved, but not more than about a week from an interested user.

Although we still have a long way to go, I believe that among Indian business schools, IIMA is at the forefront of introducing open-source computing environment to its students, both at our post-graduate and doctoral programs. We have done away with our compulsory Excel course in the first year, and many of us use R and Python in the classroom regularly. A few of us in the finance area have not only completely shifted to open-source environment for our research and teaching but have also completely ditched the proprietary operating systems in favor of Ubuntu, or even Arch Linux. Now that’s a topic for another day.

Written by Vineet

March 15, 2016 at 1:01 pm

Posted in Computing, Stories

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[Etc] Boss at SXSW

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It’s that time of the year, so this goes out to the class of 2013-15. I don’t know how many of you are into this kind of thing, but give it a ‘ear, and listen to what the boss sez, coz “you suck!”

All the best, and do well.

Written by Vineet

March 22, 2015 at 9:39 pm

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A blogroll

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I have been asked by a few of you on a blog-readings list towards preparation for your summers. There are a great many financial markets blogs out there (and you should separately search for each asset class), but if you are going to prioritize a few that allow you to track the overall developments in the global markets, you can’t go wrong with these:

  1. FT Alphaville: If there is only financial daily you can read in a day, it should be FT and if there is only one blog you can read in a day, this should be it
  2. Money Beat: As the name says, from the people at the Wall Street Journal
  3. Across the Curve: Chronicling the bond markets
  4. Calculated Risk: One of the top and most reliable blogs out there on economic data and developments
  5. The Big Picture: Another great resource for, well, getting the big picture

All the best!

Written by Vineet

November 3, 2014 at 10:05 pm

Posted in Stories, Teaching: FM

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[FM] Psychology and Markets

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On the role of psychology in financial markets (and society)

Below is an honest-sounding and almost self-effacing interview with one of last year’s winner of Nobel in Economics (dated Feb, 2014; starts after a minute of ads etc.)

PS: With reference to our discussion in the class, this note prepared by the Nobel Committee summarizes the contributions of all three 2013 Nobel Laureates in Economics for their work in asset pricing in a non-technical way.

Written by Vineet

September 6, 2014 at 5:18 pm

Posted in Stories, Teaching: FM

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