Distrust and cross-check

I have piece in today’s Mint arguing that the Volkswagen emission scandal is a wake-up call for all financial regulators worldwide:

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The implications of big firms such as Volkswagen using software to cheat their customers go far beyond a few million diesel cars

The Volkswagen emissions scandal challenges us to move beyond Ronald Reagan’s favourite Russian proverb “trust but verify” to a more sceptical attitude: “distrust and cross-check”.

A modern car is reported to contain a hundred million lines of code to deliver optimised performance. But we learned last month that all this software can also be used to cheat. Volkswagen had a cheating software in its diesel cars so that the car appeared to meet emission standards in the lab while switching off the emission controls to deliver fuel economy on the road.

The shocking thing about Volkswagen is that (unlike, say Enron), it is not perceived to be a significantly more unethical company than its peers. Perhaps, the interposition of software makes the cheating impersonal, and allows managers to psychologically distance themselves from the crime. Individuals who might hesitate to cheat personally might have less compunctions in authorizing the creation of software that cheats.

The implications of big corporations using software to cheat their customers go far beyond a few million diesel cars. We are forced to ask whether, after Volkswagen, any corporate software can be trusted. In this article, I explore the implications of distrusting the software used by big corporations in the financial sector:

Can you trust your bank’s software to calculate the interest on your checking account correctly? Or might the software be programmed to check your Facebook and LinkedIn profiles to deduce that you are not the kind of person who checks bank statements meticulously, and then switch on a module that computes the interest due to you at a lower rate?

Can you be sure that the stock exchange is implementing price-time priority rules correctly or might the software in the order matching engine be programmed to favour particular clients?

Can you trust your mutual funds’ software to calculate Net Asset Value (NAV) correctly? Or might the software be programmed to understate the NAV on days where there are lots of redemption (and the mutual fund is paying out the NAV) while overstating the NAV on days of large inflows when the mutual fund is receiving the NAV?

Can you be sure that your credit card issuer has not programmed the software to deliberately add surcharges to your purchases. Perhaps, if you complain, the surcharges will be promptly reversed, but the issuer makes a profit from those who do not complain.

Can you trust the financials of a large corporation? Or could the accounting software be smart enough to figure out that it is the auditor who has logged in, and accordingly display a set of numbers different from what the management sees?

After Volkswagen, these fears can no longer be dismissed as mere paranoia. The question today is how can we, as individuals, protect ourselves against software-enabled corporate cheating? The answer lies in open source software and open data. Computing is cheap, and these days each of us walks around with a computer in our pocket (though, we choose to call it a smartphone instead of a computer). Each individual can, therefore, well afford to cross-check every computation if (a) the requisite data is accessible in machine-readable form, and (b) the applicable rules of computation are available in the form of open source software.

Financial sector regulations today require both the data and the rules to be disclosed to the consumers. What the rules do not do is to require the disclosures to be computer friendly. I often receive PDF files from which it is very hard to extract data for further processing. Even where a bank allows me to download data as a text or CSV (comma-separated value) file, the column order and format changes often and the processing code needs to be modified every time this happens. This must change. It must be mandatory to provide data in a standard format or in an extensible format like XML. Since data anyway comes from a computer database, the bank or financial firm can provide machine-readable data to the consumer at negligible cost.

When it comes to rules, disclosure is in the form of several pages of fine print legalese. Since the financial firm anyway has to implement rules in computer code, there is little cost to requiring that computer code be freely made available to the consumer. It could be Python code as the US SEC proposed five years ago in the context of mortgage-backed securities (http://www.sec.gov/rules/proposed/2010/33-9117.pdf), or it could be in any other open source language that does not require the consumer to buy an expensive compiler to run the code.

In the battle between the consumer and the corporation, the computer is the consumer’s best friend. Of course, the big corporation has far more powerful computers than you and I do, but it needs to process data of millions of consumers in real time. You and I need to process only one person’s data and that too at some leisure and so the scales are roughly balanced if only the regulators mandate that corporate computers start talking to consumers’ computers.

Volkswagen is a wake-up call for all financial regulators worldwide. I hope they heed the call.

Twitter or Newswires: Are regulators behind the curve?

Last week, I read two stories that made me wonder how regulators are far behind the curve when it comes to new media.

First, Business Insider reported that after the newswire hacking scandal (which I blogged about last month), Goldman Sachs was considering announcing its earnings on Twitter instead of on the newswires. Of course, such reports are often speculative and nothing may come of it, but it indicates that at least some organizations are taking the new media seriously.

Second, was an amendment to the New York Stock Exchange (NYSE) rules on how companies should release news to the public (h/t CLS Blue Sky Blog):

Currently, section 202.06(C) … on the best way to release material news … is outdated as it refers to, among other things, the release of news by telephone, facsimile or hand delivery. Instead, the Exchange proposes … that listed companies releasing material news should either (i) include the news in a Form 8-K or other Commission filing, or (ii) issue the news in a press release to the major news wire services.

The regulators have finally decided to shift from obsolete media to the old media; the new media is not even on the horizon.

Interview in Bloomberg TV

Bloomberg TV carried an interview with me last week. The video is available at the channel’s website. Among several other things, the interview also covered the Amtek Auto episode that I have blogged about in the past. I argued that Amtek Auto is unlikely to be the last episode of distressed corporate bonds in mutual fund portfolios, and we need to be more proactive in future.

Are large fund managers problematic?

Last month, I read four seemingly unrelated papers which all point towards problems posed by large fund managers.

1. Ben-David, Franzoni, Moussawi and Sedunov (The Granular Nature of Large Institutional Investors) show that the stocks owned by large institutions exhibit stronger price inefficiency and are also more volatile. They also study the impact of Blackrock’s acquisition of Barclays Global Investors (which the authors for some strange reason choose to identify only as “a mega-merger between two large institutional investors that took place at the end of 2009”). Post merger, the ownership of stocks which was spread across two fund managers became concentrated in one fund manager. The interaction term in their regression results show that this concentration increased the volatility of the stocks concerned. On the mispricing front, they show that the autocorrelation of returns is higher for stocks that are held by large institutional investors; and that stocks with common ownership by large institutions display abnormal co-movement. They also show that negative news about the fund manager (increase in the CDS spread) lead to an increase in volatility of stocks owned by that fund.

2. Israeli, Lee and Sridharan (Is There a Dark Side to Exchange Traded Funds (ETFs)? An Information Perspective) find that stocks that are owned by Exchange Traded Funds (ETFs) suffer a decline in pricing efficiency: higher trading costs (measured as bid-ask spreads and price impact of trades), higher co-movement with general market and industry returns; a decline in the predictive power of current returns for future earnings); and a decline in the number of analysts covering the firm. They hypothesize that ETF ownership reduces the supply of securities available for trade, as well as the number of uninformed traders willing to trade these securities. Much the same factors may be behind the results found by Ben-David, Franzoni, Moussawi and Sedunov.

3. Clare, Nitzsche and Motson (Are Investors Better Off with Small Hedge Funds in Times of Crisis?) argue that on average investors were better off investing with a small hedge fund instead of a large one in times of crisis (the dot com bust and the global financial crisis). They speculate that bigger hedge funds might attract more hot money (fund of funds) which might lead to large redemptions during crises. Smaller hedge funds might have less flighty investors and more stringent gating arrangements. Smaller hedge funds might also have lower beta portfolios.

4. Elhauge (Horizontal Shareholding as an Antitrust Violation) focuses on problems in the real economy rather than in the financial markets. The argument is that when a common set of large institutions own significant shares in firms that are horizontal competitors in a concentrated product market, these firms are likely to behave anticompetitively. Elhauge discusses the DuPont-Monsanta situation to illustrate his argument. The top four shareholders of DuPont are also four of the top five shareholders in Monsanto, and they own nearly 20% of both companies. The fifth largest shareholder of DuPont, the Trian Fund, which did not own significant shares in Monsanto, launched a proxy contest criticizing DuPont management for failing to maximize DuPont profits. In particular, Trian complained that DuPont entered into a reverse payment patent settlement with Monsanto whereby, instead of competing, DuPont paid Monsanto for a license to use Monsanto’s patent. Trian’s proxy contest failed because it was not supported by the four top shareholders of DuPont who stood to gain from maximizing the joint profits of DuPont and Monsanto. I thought it might be useful for the author to compare this situation with the cartelization promoted by the big investment banks in 19th century US or by the big banks in early 20th century Germany or Japan.

Negative interest rates wreak havoc with finance textbooks

By assuming non negative interest rates, finance textbooks arrive at many results that are false in a negative rates world. Finance theory does not rule out negative rates – theory requires only bond prices to be non negative, and this only prevents interest rates from dropping below −100%. In practice also, early 2015 saw interest rates go negative in many countries. The BIS 2015 Annual Report (Graph II.6, page 32) shows negative ten-year yields in Switzerland, and negative five year yields in Germany, France, Denmark and Sweden in April 2015.

Let us take a look at how many textbook results are no longer valid in this world:

• The formula for the present value of a perpetuity PV=1/r yields the absurd result that the present value is negative when r is negative. In fact, the present value is infinite (the geometric series diverges for negative r).

• Interestingly, the formula for a growing perpetuity PV=1/(r−g) is still valid under the text book assumption that r>g. But this requires negative g in a negative rates world. That is why the 1/r formula for the zero growth case fails.

• It is no longer true as the textbooks claim that an American call option on a non dividend paying stock would never be exercised prematurely and is therefore the same as a European call. If the call is sufficiently deeply in the money, the holder would want to pay the exercise price as early as possible to avoid the tax (of negative rates) on cash holdings.

• The opposite text book claim about puts is now false. The textbook result is that a deep out of the money put could be exercised early to realize the cash flow early. In a negative rates world, we want to postpone the realization of cash (and avoid paying negative rates on that cash). Consequently, in a negative rates world, American puts would never be exercised early. Even the non dividend paying assumption is not needed for this result.

• It is no longer true that the modified duration of a bond is slightly less than the duration; with negative rates, the modified duration of a bond is slightly more than the duration. Modified duration is given by MD=D/(1+r); if r is negative, the denominator is less than unity and the ratio is therefore more than the numerator.

• Negative rates have not so far generally translated into negative coupons. For example, the Swiss Government and German Government have sold bonds with non negative coupons at a premium to par to achieve negative yields. If this trend continues, then in a negative rates world, there will be no par bonds and no discount bonds, and the concept of a par bond yield curve becomes problematic.

• Over a period of time, probably negative coupon bonds will emerge. Warren Buffet’s Berkshire Hathaway sold a convertible bond with a negative coupon way back in 2002. With negative coupons, it is no longer true that the duration of a bond cannot exceed its maturity. It is also not true that for the same maturity, the zero coupon bond has the longest duration. For example, a simple calculation shows that a ten year par bond with a −1% coupon and a −1% yield has a duration of 10.47 years.