Monday, April 16, 2018

A VIXing Problem

2017 was a banner year for equity investors across the globe, including in the U.S., as the S&P 500 index gained over 19% (excluding dividends). Moreover, those gains were accompanied by extraordinarily low levels of volatility. 

We are nearly three months into 2018, and to say that things have not been as smooth would be an understatement, as volatility has returned with a vengeance to equity markets. The increase in volatility was especially acute on the day of February 5, 2018, when the CBOE Volatility Index (VIX®) moved more than it ever had in history, closing over 20 points higher from the previous day’s close (rising from 17.31 to 37.32), while equity markets plunged (the S&P 500 fell over 4%).


The 116% spike in the VIX reportedly triggered the implosion of a popular exchange-traded product called the VelocityShares Daily Inverse VIX Short Term ETN (ticker: XIV). XIV enabled investors to bet that low volatility would continue to rule the day. Through XIV, they would essentially be betting against short-term VIX futures. The VIX spike and XIV implosion has piqued the interest of investors, regulators, lawyers and journalists. Interested parties wanted to know the reasons for the volatility spike and whether there was any wrongdoing involved.


Before we consider the possibility of misconduct, we should take a step back to consider what exactly the VIX measures. The VIX is a market-based measure of expected, or implied, volatility. The Chicago Board of Exchange (CBOE) derives the VIX by backing out the volatility that is implied by market quotes for a portfolio of out-of-the-money put and call options on the S&P 500 index (SPX). With the aggregated option quotes we can gauge the volatility for the underlying SPX. 

Back in May 2017, well before all of the recent VIX excitement, researchers Griffin and Shams released a paper entitled, “Manipulation in the VIX?” The Griffin paper details how the VIX settlement process can be gamed by simply posting bids and offers (that may never lead to actual trade executions) to affect the VIX settlement. This possibility is reminiscent of spoofing conduct reported across various markets such as FX, Treasury futures, precious metals futures, and equity index futures, where some market participants are thought to have influenced market prices by posting bids and offers that they have no intention of actually executing.  Griffin concludes that price and volume data patterns are consistent with a trading strategy whose purpose is affecting the VIX settlement. The paper notes: 
“In sum, our findings show that the VIX settlement appears susceptible to manipulation, and that the aggregate evidence aligns itself with what one would expect to see in the case of market manipulation of certain settlements. However, we cannot fully rule out all potential explanations without more granular data.” 
One week after the wild VIX ride of February 5, 2018, a DC-based law firm, Zuckerman Law, released a letter to the SEC and CFTC on behalf of its anonymous whistleblower-client, alleging manipulation of the VIX. The next day, former CFTC Commissioner Bart Chilton noted during a CNBC television interview that, “The VIX has been suspect for at least seven years.” 

And on March 9 of this year, the law firm Cohen Milstein filed a purported class action complaint on behalf of Atlantic Trading USA, LLC against unknown John Does, alleging manipulation of the settlement price for VIX futures and options. The complaint alleges that defendants “caused the monthly final settlement price of expiring VIX contracts to be artificial. They did so by placing manipulative SPX options orders that were intended to cause, and at minimum recklessly caused, artificial VIX contract settlement prices in the expiring contracts.” 

With the VIX being prone to manipulation, and billions of dollars’ worth of derivatives and exchange traded products tied to it, we’d like to see if there might be a better way of calculating expected volatility – a method that is not as prone to the vagaries of potential wrong-doers. 

PF2 consultant Joe Pimbley and PF2's Gene Phillips have done just this in a paper called Fix the VIX, which can be accessed here, courtesy of the Global Association of Risk Professionals (GARP). 

Our investigation finds that three approximation techniques being implemented by the CBOE in “calibrating” the VIX may not be necessary, and may exacerbate errors or increase the VIX’s susceptibility to manipulation or error. Of course, volatility won’t go away. But the VIX will more accurately capture it and describe it, with a couple of … fixes.

Friday, April 6, 2018

Tesla Bonds – Revved Up by Moody’s?

There’s one thing about equity analysts talking up Tesla and getting behind the hype: equity investors enjoy the upside if their optimistic scenarios come true. 

But bonds have only downside, and rating agencies are supposed to analyze various scenarios – the good the bad and the ugly – in coming up with bond ratings.

It doesn’t look like Moody’s did that when rating Tesla B2 and Tesla’s $1.8 billion bond issue B3 in August 2017.   Rather, they assumed as true Tesla’s optimistic production targets (or hopes) for Tesla’s Model 3 and rated Tesla based on those coming true.  To exaggerate how bizarre this approach is, had Tesla said they hope and expect to produce a million cars a day, perhaps Moody’s would have rated them Aaa!  Click, whirr

Crucially, Moody’s provided Tesla, the company and its bonds, ratings based on a picture of its future financial that exceeded its true financial position, before Tesla had met the goals that would warrant the rating.

Moody’s rating rationale reads as follows (with our emphasis added): 

"The B2 CFR reflects Moody's expectation that the launch, production ramp up, and market acceptance of the Model 3 will be successful enough to achieve approximately 300,000 unit sales during 2018 (a full-year sales rate averaging about 5,500 per week) with a gross margin approximating 25%. This level of sales and profitability would enable Tesla to strengthen its performance from sizable losses to an operating position that supports the B2 CFR. The B2 rating is further supported by Moody's expectation than in the event of severe financial or operating stress, Tesla's brand name, production facilities, and product lineup would have considerable value to another automotive OEM or technology firm targeting the electric vehicle and mobility markets."
To use Moody's language, in short, the achievement of the goals "would enable" Tesla to achieve the rating being provided now!  Moody's has assumed a future, rosier picture of the company, and based its current rating on the achievement of this rosy future, rather than waiting for the financial position to warrant the rating provided.  

Yet in its own press release, Moody’s rating analyst Bruce Clark (Senior VP) notes that "The major challenge facing the company during the next twelve months will largely be the considerable execution risks associated with the rapid ramp up in production of a totally new vehicle." 

So, why not see if Tesla can execute before rating Tesla B2, if the B2 rating is contingent on execution at a level far beyond what Tesla has ever yet achieved?   The answer, unfortunately, is that had they looked at Tesla’s actual then-current balance sheet, they would never have rated them B2, but probably in the Caa range.   And Tesla might have gone elsewhere for its second rating (it landed up getting a B- rating from S&P) or scratched the idea of issuing this bond. In fact, Moody’s essentially acknowledges this pressure, which to us seems to be a potential conflict of interest: “Without the proceeds from the [proposed] note offering, Tesla's liquidity position would be stressed.”

Moody’s didn’t exactly mark Tesla to market did it? Moody’s marked them to an optimistic future. 

It does make one wonder where the Moody’s opinion lies if Moody's is simply going to take Tesla's management’s assumption as a given.  A good job, if you can get it, but hardly an insightful opinion. 

As it happened, towards the end of March Moody’s noticed that Tesla was still far away from achieving its optimistic goals, having suffered some production hurdles and delays not atypical for a young company producing a new vehicle.   

Moody’s downgraded the so-called “long-term” ratings in March 2018, a little more than half a year after the bonds were issued.  The long-term ratings were ultimately based on very short-term expectations.  Click, whirr. 
"[Moody’s downgrade of] Tesla's ratings reflect the significant shortfall in the production rate of the company's Model 3 electric vehicle. The company also faces liquidity pressures due to its large negative free cash flow and the pending maturities of convertible bonds ($230 million in November 2018 and $920 million in March 2019). Tesla produced only 2,425 Model 3s during the fourth quarter of 2017; it is currently targeting a weekly production rate of 2,500 by the end of March, and 5,000 per week by the end of June. This compares with the company's year-earlier production expectations of 5,000 per week by the end of 2017 and 10,000 by the end of 2018." 
Oddly, now Moody’s is no longer hinging its rating to Tesla's current expectations: “The rating could be raised if production rates of the Model 3 meet Tesla's current expectations and if the company maintains good liquidity.” 

Bondholders ought to be frustrated. They have bought into a B2 corporate family rating of a company which clearly wasn’t yet B2 at the time of the issuance. They may well have taken Caa-like risk, but only been compensated for the taking of single B risk. 

Tesla has already been downgraded, and it is arguable whether the new B3 rating is well-founded, too. The bonds have been downgraded from B3 to Caa1 and have lost roughly 3% in value on the day of the downgrade. Altogether, the bonds are down roughly 10% in price terms since issuance. 




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PF2 would like to thank Joe Pimbley for his contribution to this article.

Monday, February 26, 2018

Florida Shootings Require Cultural & Mindset Changes

Our failure to prevent the Florida school shooting illustrates a pervasive problem in modern societies: we often have access to ample warning signs but all-too-frequently fail to leverage this information to avoid disaster. The issue not only impacts law enforcement agencies, but our financial institutions as well. To more effectively handle all the intelligence available to them, organizations will require major structural and cultural change. 

The FBI and local law enforcement reportedly had more than enough information to legally disarm and detain confessed school shooter Nikolas Cruz before he killed 17 people at Parkland High on February 14. This is not the first such intelligence failure, and won’t be the last. Consider these examples:
  • 9/11 could have been prevented had the CIA and FBI done a better job of sharing and handling intelligence.
  • Russian intelligence warned the FBI about Tamerlan Tsarnaev long before he carried out the Boston Marathon bombing.
  • In France, authorities failed to act on multiple clues that would have enabled them to prevent the Paris bombings that claimed 130 lives in November 2015. 

In the financial industry, rating agencies and bank risk management teams failed to act in their or their clients’ best interests when they continued to create and sell residential mortgage-backed securities, despite the deterioration in mortgage lending standards, and the increasing and disturbing amount of mortgage fraud being reported by the FBI in its annual mortgage fraud reports.

A well-operating risk-management function, with a voice, would most likely have limited the potential for the cultural failures seen at the Royal Bank of Scotland, as detailed in the recently published report commissioned by the Financial Conduct Authority. The extraordinary activities of the gung-ho Global Restructuring Group at RBS in London could immediately have been stymied, as they posed reputational and business risks far outweighing the group's short-term revenue-generating interests. As the report explains: 
“GRG enjoyed an unusual independence of action for a customer-facing unit of a major bank. It saw the delivery of its own narrow commercial objectives as paramount: objectives that focused on the income GRG could generate from the charges it levied on distressed customers. In pursuing these objectives, GRG failed to take adequate account of the interests of the customers it handled and, indeed, of its own stated objective to support the turnaround of potentially viable customers.” 
These assorted failures suggest that we have a systemic problem with risk monitoring, or a failure to incorporate it appropriately within institutions. And because the problem is systemic it won’t be solved by firing a few bad apples. Instead, we need to understand and address the root cause. 

One feasible argument is that jobs involving risk monitoring and mitigation generally come with a relatively low social status and thus do not necessarily attract the most motivated applicants.

This phenomenon is epitomized by our (often unfair) stereotype of security guards: that they are ineffective and prone to sleeping on the job. Because security jobs are low paying, they don’t often attract type “A” individuals. The job itself is quite boring: most of the time nothing happens. While a more proactive security guard could find and act upon many clues during the course of his or her day, almost all of the extra effort will be for naught. At least 99 times out of 100 that suspicious backpack won’t contain an explosive device. 

Although bank risk managers and FBI call handlers undoubtedly have higher social status than security guards, they are most likely to be subordinated within their organizations. At a bank, monitoring credit risk is much less glamorous and lucrative than acquiring or merging companies, underwriting deals or trading securities. And, as with the case of the seemingly suspicious backpack, most clues won’t lead anywhere anyway: for every legitimate call law enforcement departments receive there are many that lead nowhere; a missed charge card payment, similarly, often doesn’t presage a mortgage foreclosure. 

Ideally, we should elevate the status of risk monitoring jobs and make them more exciting. More attention from senior management may help. Although most money-center banks took massive losses during the financial crisis, Goldman Sachs came out relatively unscathed. A major reason is that the bank’s Chief Financial Officer reviewed daily risk management reports and held a meeting in his office to call for immediate action once its was detected that mortgage backed securities had begun to underperform in 2006. Goldman is also an exceptional case in that it rotated fast-track talent between moneymaking and risk management roles, and it empowered risk management staff to veto certain trading activities. 

Although more high-level attention might help those charged with receiving and sifting through raw intelligence, the job is still a tedious one – akin to looking for a needle in a haystack. 

Conviction Dilemma 

In addition to the possibility that risk monitoring personnel are as a group less motivated, risk personnel tend to be a more introverted type than their front-desk colleagues. This may manifest in their being apprehensive when expressing themselves to their comparatively more aggressive colleagues, and potentially come off as being indecisive or speculative.  Leaders often like a strong, definitive opinion: “hedge this risk!” and may shun or ignore a more complex opinion coming from a more cautious analyst. 

In short, the personalities hired into risk-management roles often suffer from what we will term the “conviction dilemma,” which emanates from the work of Philip Tetlock and others, who studied predictive expertise. Tetlock's research findings informed his commentary that those whose expertise was valued and sought out, for example pundits on TV shows like The McLaughlin Group, were those who had vocal, unequivocal opinions, that could be articulated with utter conviction – but were often wrong. 

Altogether, even strong and motivated risk experts may be introverted and may be indecisive when expressing themselves. Playing a function that is considered as subordinated in management’s eye, they might struggle to make convincing and resolute “do this!” arguments, and management might therefore be less likely to take them seriously, and act on them expeditiously. 

Applying Technology 

In the 21st century, we have learned to assign boring or laborious jobs to computers. We can identify potential attackers earlier by entering all the clues law enforcement receives into shared databases, and we have state-of-the-art data science tools built for analyzing this mass of information. This approach need not violate privacy: social media posts, calls from tipsters and prior arrests are all legitimately available to law enforcement today. 

Palantir is among the most prominent of companies offering software that enables intelligence agencies to find needles in the haystacks of raw data they receive. Unfortunately, Palantir is not an inexpensive solution, and may thus be beyond the budgets of smaller law enforcement agencies. 

Governments and NGOs may wish to invest in the development of free, open source data analysis. Aleph is an open source tool that can analyze large volumes of unstructured data. Although designed for investigative journalists, it could be customized for use by law enforcement of for counterparty tracking. Whether they use licensed or open-source solutions, law enforcement and intelligence agencies should establish and apply technical standards for data sharing. Because financial firms are overtly competitive, data sharing of financial intelligence may be less appropriate between competing firms, but may be more prevalent within institutions. 

Often the information needed to prevent mass killings is hiding in plain sight. By improving organizational structures and leveraging technology, financial firms and law enforcement agencies can harvest more actionable data from legally available information. Armed with this data, they can prevent certain future acts of carnage. While no single policy solution – VaR levels or gun control included – can ever guarantee endless success, we need to be thoughtful and dynamic in going about limiting the frequency or even the magnitude of these catastrophes, and we would do well to use our tools effectively in pursuing the goal not only of making money, winning clients and awards, but also of limiting the downside.


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This piece was co-written by Marc Joffe, who consults for PF2, and members of PF2’s staff. For more on this topic, visit our 2016 piece on the detrimental impact of short-term thinking patterns on conduct with financial firms. Among other things, we recommend a re-thinking of the design of incentive structures: “The approach we put forward here is the studious linking of profit-sharing to successful and honest risk-taking and business practices.”

Marc Joffe is a Senior Policy Analyst at the Reason Foundation and a researcher in the credit assessment field. He previously worked as a Senior Director at Moody’s Analytics. 

Tuesday, February 20, 2018

Apple or the United States: Which is the Stronger Credit?

In blogs like this, we sometimes like to begin discussions. 

Today, we're going to present an interesting situation. Moody's holds that the US is a Aaa credit, while Apple Inc. is rated Aa1 (both its debt and its corporate family ratings are Aa1). 

Aside from some recent hiccups, Apple is a growing company (see the chart). Its debt level sits at 44% of its annual revenues, and the expense of its debt is somewhat moderate, at 1.2% of its annual revenues. The US is growing its revenues too, albeit at a modest clip. The expense of its debt, however, is approaching 8% of annual revenues. 

Recent developments make us wonder whether the US is truly the stronger credit. This blog takes you through some of the bigger picture here, including elements of the credit rating processes that might be supportive of the rating agency's stance, despite the numbers perhaps telling a different story. We don't take a position here, as much as pose the question.  And we look forward to your thoughts.

Comparing Apples & Oranges? 

Recent fiscal developments have us thinking again about the US's credit rating.

February 9th’s budget and spending caps agreement tipped next year’s budget deficit over $1 trillion, according to the Committee for a Responsible Federal Budget, despite the fact that we are almost nine years into the current economic expansion and with the official (U3) unemployment rate at just 4.1%.  That bipartisan debt binge, in the wake of last year’s $1.5 trillion tax cut (over ten years), has some prudent budget-watchers scratching their heads. 

Last month, Reuters reported that “China’s Dagong Global Credit Rating Co, one of the country’s most prominent ratings firms, on Tuesday cut the local and foreign currency sovereign ratings of the United States, citing an increasing reliance on debt in the world’s largest economy.” Dagong cut the US’s sovereign rating to BBB+ (from A-), with a negative outlook. 
“Deficiencies in the current U.S. political ecology make it difficult for the efficient administration of the federal government, so the national economic development derails from the right track,” Dagong said. “Massive tax cuts directly reduce the federal government’s sources of debt repayment, therefore further weakens the base of government’s debt repayment.”
Looking at the numbers as of fiscal year-end 2016 (the most recent year with complete figures), Apple’s debt as a percentage of revenue and its interest expense as a percentage of revenue are much lower than the US’s corresponding levels.

Strictly based on the debt/revenue and interest expense/revenue ratios, an entity with US’s metrics would likely garner a below-investment-grade rating: according to Moody’s' ratings methodology for diversified technology companies, a negative EBIT/Interest Expense equates to a rating of Ca (the lowest rating on the subfactor scale), all else equal.

US’s Primary Balance/Interest Expense, our proxy for US’s EBIT/Interest Expense, is negative. We don’t have a proxy for the US’s EBITDA (earnings before interest, taxes, depreciation, and amortization), but let’s take our proxy for the US's EBIT and magically add back $2 trillion(!) worth of imaginary “depreciation and amortization.” Doing so gets us to an “EBITDA” of $1.7 trillion. In this hypothetical, its Debt/EBITDA is still over 10x, which would correspond to a rating of Ca (all else equal) for a diversified technology company.

Even in the rosiest possible proxy for EBITDA, in which we suppose USA has zero expenditures(!), and thus its EBITDA would simply equal its revenue, the hypothetical Debt/EBITDA would be 3x, which maps to a rating of Ba, all else equal, for a diversified technology company.

Viewing the US’s long-term fiscal situation with a more critical lens, we might consider the future fiscal impact of Social Security and Medicare – which are underfunded by $46.7 trillion over the next 75 years (per the Fiscal Year 2016 Financial Report of the U.S. Government jointly produced by the US Treasury and the Office of Management and Budget of the Executive Office of the President). 

Yet, Moody’s and many of the other rating agencies don't seem overly concerned, rating the US Aaa (stable outlook).

Into the finer details, now, there are several quantitative factors that might be equally or more relevant to these entities’ respective ratings (e.g. EBITDA margin or FCF/Debt for Apple; Interest Expense/GDP or Inflation for the US), but we tried to highlight metrics in this chart which are most comparable between the two debt issuers. 

Keep in mind that there are also key qualitative characteristics that Moody’s considers when rating corporates and sovereigns. For example, Moody’s gives significant weight to considerations such as management financial policy (“management and board tolerance for financial risk”) for diversified technology corporations, and institutional strength (specifically, “government effectiveness”, “rule of law”, and “control of corruption”) for sovereigns.  

Notably: 
  • The United States government has the legal authority to compel its “customers” (i.e. taxpayers) to pay more, if necessary (although political willingness might be another matter), while a corporation has no such relationship with its customers.
  • Apple lacks a printing press, whereas the USA can print its own currency. 
  • The US has a central bank that has the ability to monetize federal debt, whereby the Federal Reserve can essentially finance fiscal deficits by purchasing as much government debt as the federal government issues, although technically the Fed maintains its independence from political interference. 
  • (Moody’s does consider inflation as an important ingredient in its sovereign ratings, so the rating itself might suffer in a scenario in which the country printed its way of a fiscal hole, but there technically would still be no default.)
Altogether, Apple’s revenue is growing faster than the US’s (99% vs. 31%, over 5 years), it has much less debt than the US (relative to revenue: 44% vs. 304%), and its interest expense is much lower (relative to revenue: 1.2% vs. 7.7%).

So the question is, are the US’s other strengths or advantages -- its ability to raise more revenue through taxes if truly needed, and its unique ability to service its debts by either printing more of the world’s reserve currency or having its central bank purchase its debt -- enough to justify a Aaa rating?  In deciding this, one must consider not only the US's current trillion dollar deficits at a point in the economic cycle that does not beg for drastic fiscal stimulus, but also the fact that we have a Social Security and Medicare funding gap of nearly $47 trillion, in present value terms, that is only growing worse. (At this juncture, it seems that our elected officials have chosen to do nothing about the funding gap.)

Remember, the question is not whether or not the US will default, or how it may grow itself out of the current situation -- but whether the likelihood of there being an issue here is so remote as to warrant a Aaa rating, a rating higher than that of Apple's debt, which is currently well-supported.

It is worth considering Stein’s Law as we end this blog: "If something cannot go on forever, it will stop" or "Trends that can't continue, won't."  Interestingly, Stein meant this in the sense that there is no need for action or a program to make it stop, much less to make it stop immediately; it will stop of its own accord.

Lisa Benson Editorial Cartoon used with the permission of Lisa Benson, the
Washington Post Writers Group and the Cartoonist Group.  All rights reserved.


Thursday, February 8, 2018

Market Trading Investigations - Layering, Spoofing, Front-Running, Stop-Loss Triggering

Adding to our prior compilations of valuation issues, questions of fairness in market executions, and fee disclosure concerns, we are adding a new set that looks at investigations into, and allegations of layering, spoofing, front-running, barrier-running and stop-loss triggering in the financial markets.
  1. Jan 2018: Spoofing - Precious Metals; S&P Futures. CFTC Files Eight Anti-Spoofing Enforcement Actions against Three Banks (Deutsche Bank, HSBC & UBS) & Six Individuals 
  2. Jan 2018: Front-running - FX. HSBC front-running victim (Prudential Plc) 
  3. Jan 2018: Front-running - FX. Barclays front-running of HPQ in $8.3bn FX options trade 
  4. Oct 2017: Front-running - FX. U.S. jury finds ex-HSBC executive guilty of fraud in $3.5 billion currency trade 
  5. Aug 2017: Spoofing - Treasury Futures; Eurodollar Futures. CFTC Finds that The Bank of Tokyo-Mitsubishi UFJ, Ltd. Engaged in Spoofing of Treasury Futures and Eurodollar Futures 
  6. Jul 2017: Spoofing - Commodity Futures (multiple). CFTC Orders New York Trader Simon Posen to Pay a $635,000 Civil Monetary Penalty and Permanently Bans Him from Trading in CFTC-Regulated Markets for Spoofing in the Gold, Silver, Copper, and Crude Oil Futures Markets 
  7. Jun 2017: Spoofing - Precious Metals. CFTC Finds Former Trader David Liew Engaged in Spoofing and Manipulation of the Gold and Silver Futures Markets and Permanently Bans Him from Trading and Other Activities in CFTC-Regulated Markets 
  8. Mar 2017: Spoofing - Equities (cash and contracts for difference). Ex-DBS Trader Convicted in Singapore's First Spoofing Case 
  9. Jan 2017: Spoofing - Treasury Futures. CFTC Orders Citigroup Global Markets Inc. to Pay $25 Million for Spoofing in U.S. Treasury Futures Markets and for Related Supervision Failures 
  10. Dec 2016: Stop-Loss Triggering - FX. Australian Securities and Investments Commission (ASIC) accepts Enforceable Undertaking from Commonwealth Bank of Australia (CBA) for triggering FX customer stop-loss orders 
  11. Dec 2016: Spoofing - Futures (equity index; crude oil; natural gas; cooper; VIX). Federal Court Orders Chicago Trader Igor B. Oystacher and 3Red Trading LLC to Pay $2.5 Million Penalty for Spoofing and Employment of a Manipulative and Deceptive Device, while Trading Futures Contracts on Multiple Futures Exchanges 
  12. Nov 2016: Spoofing - Equity Index Futures. Federal Court in Chicago Orders U.K. Resident Navinder Singh Sarao to Pay More than $38 Million in Monetary Sanctions for Price Manipulation and Spoofing 
  13. Jan 2015: Layering & Spoofing - Equities. Canadian Man Charged in First Federal Securities Fraud Prosecution Involving 'Layering' 
  14. Jul 2013: Spoofing - Commodity Future (multiple). CFTC Orders Panther Energy Trading LLC and its Principal Michael J. Coscia to Pay $2.8 Million and Bans Them from Trading for One Year, for Spoofing in Numerous Commodity Futures Contracts 
  15. Dec 2012: Spoofing - Wheat Futures. CFTC Files Complaint in Federal Court against Eric Moncada, BES Capital LLC, and Serdika LLC Alleging Attempted Manipulation of Wheat Futures Contract Prices, Fictitious Sales, and Non-Competitive Transactions 

Monday, January 8, 2018

Blog 1 of 2018 / Markets for Consumer Data & User-Beware

Hello readers, and thanks for joining us for our first blog of the new year.

This year, in addition to our typical musings on financial markets, we'll be writing a little more on consumer data.

Hacks have been all the rage for a while already (Equifax and Yahoo! more recently; Target in 2013, Sony Playstation in 2011 and TJ Maxx in 2007 are not too-distant memories).

But our interest lies somewhere else: in what is happening behind the scenes with our data.

hiQ v LinkedIn

hiQ is a San Fran-based startup which was doing something pretty interesting: it was scraping data from LinkedIn and then selling that data or analyses done using that data.

LinkedIn didn't much like this, with hiQ's automated robots ("bots") bypassing LinkedIn's security measures to scrape the data, which LinkedIn felt undermined LinkedIn’s privacy commitments to its members.

They battled it out in court, with the court finding in August, probably reasonably, that LinkedIn could not stop hiQ from scraping the publicly-viewable information from LinkedIn's website.  In fairness, LinkedIn doesn't own its users' data -- it's our data! -- and therefore couldn't limit hiQ's ability to access or study it.

The ruling is interesting for several reasons, including some of the First Amendment-type arguments made by hiQ to support its right to scrape.  
“To choke off speech and the precursor of speech, the gathering of facts and the analysis of information, is a dangerous path down which we should not go,” 
         -- Harvard law professor Laurence Tribe, representing hiQ, reportedly told                 the judge.    
“hiQ believes that public data must remain public, and innovation on the internet should not be stifled by legal bullying or the anti-competitive hoarding of public data by a small group of powerful companies, ... It is important to understand that hiQ doesn’t analyze private sections of LinkedIn – we only review public profile information. We don’t republish or sell the data we collect. We only use it as the basis for the valuable analysis we provide to employers. ”
            -- hiQ said in a statement 

Okay, meh. But how about what happens next?  Like Microsoft (which owns LinkedIn) firms like Facebook, Amazon, eBay and Google, control and study copious amounts of customer data (and they sometimes get hacked and lose control of it).  But importantly they also sell it (as does hiQ).  We might like to think that they only sell aggregate data, but how would we know? 

Personal, Personnel Information

What interests us is that hiQ sells information about LinkedIn users to those LinkedIn users' bosses, including information, generated from scraping LinkedIn, about the likelihood of an employee leaving. hiQ's clients reportedly include companies like CapitalOne and GoDaddy, and hiQ's products include their Keeper product, which identifies, for employers, when their employees are at risk of leaving for another job. (For example, when employees are "looking around," they tend to make connections on LinkedIn.)

So that's a sale not necessarily of the more obvious, vanilla, personal information (name, address, date-of-birth), but user/employee/personnel's tendencies and movements. But it's almost certainly not aggregated: if it were aggregated, it would be worthless.  Sure, they're not selling the individual's vanilla data itself but they've done a basic analysis of individual's behavior and are selling the analysis.  Aggregated, it is not. 

hiQ would have no greater ownership interest in our data than LinkedIn would have.  Through hiQ's bots, we just have a simple work-around (imagine, for example, that LinkedIn were simply to buy a stake in hiQ).  If we knew that LinkedIn could "tell on us" to our employers -- and make money doing so -- would we have signed up?

We have the Latin expressions caveat emptor and caveat venditor to connote the short-hand principles of buyer-beware and seller-beware, when entering into transactions.  In 2018, the awkward expression caveat utilitor -- user-beware -- might just become part of our lexicon.

The value of Johnny's house, or Sandy's choice of handbags, is information that would help advertisers target Johnny or Sandy more appropriately.  If Johnny's house price is on the low end, all else equal one wouldn't push Maserati ads at him.  If Sandy is buying Louis Vuitton bags, well, maybe she would like this newly-released Prada bag or another Louis Vuitton bag.  But whose data is that, and do companies have a right to sell and profit from that information?  And how do we separate data, the sale of which may be limited on an individual basis, from analysis of data, which seems to be fair game.  Are these two both analyses?

  • Johnny's house was purchased for $200K this year
  • Last year, Sandy bought two of Brand X's bags and three of Brand Y's bags.

All the best for 2018.  Keep watching the Watchmen.

~ PF2

Monday, December 11, 2017

Al Franken's Complex Legacy and the Credit Rating Business

Al Franken’s announcement of his pending resignation completes his descent from Progressive Saint to something of a pariah figure. But like others whose stars have fallen during this moment of reckoning for alleged sexual harassment, Franken is neither all good nor all evil. Instead, he leaves a complex legacy with both pluses and minuses. Such was his impact in the realm of financial regulation, where he correctly diagnosed an important problem but misunderstood its genesis, putting forward an ill-conceived solution.

Before being outed as a serial groper, Franken built a reputation as an entertainer, a pundit and finally a serious-minded US Senator. Although fans of the free market rarely liked his political positions, it is hard to deny that he brought a quick wit, keen intellect and passion for justice to his work.

When deliberating over the 2010 Dodd-Frank Act, a measure intended to remedy the causes of the 2008 financial crisis, Franken recognized that it didn’t adequately address credit rating agencies. He realized that these firms triggered the crisis by assigning gold-plated AAA ratings to thousands of low quality mortgage-backed securities. These rating errors attracted excess capital into the housing finance market, driving down the cost of getting a home loan and inflating the home price bubble.

Importantly, Franken understood the complex interplay in the market, recognizing that the bad ratings were a byproduct of the credit rating business model, in which the agencies are compensated by bond issuers rather than investors. In the oligopolistic rating market – dominated by three firms – bond issuers could pit rating agencies against one another, offering to hire the agency willing to apply the lowest credit standards to their bonds. Until this business practice changed, the economy would remain vulnerable to another financial crisis.

Franken’s diagnosis was buttressed by the fact that rating agencies have made many other errors. (As I discuss in a forthcoming Reason Foundation study, rating agencies also assigned inflated ratings to Enron, Worldcom, and municipal bond insurers like Ambac and MBIA, among others.)

Although Franken’s analysis was correct, his proposed solution was flawed. His idea was to break the nexus between bond issuers and rating agencies by inserting government as a middleman. Rather than select rating agencies on their own, bond issuers would have to ask a government bureau to select raters on their behalf. This so-called Franken Amendment to Dodd Frank was stripped from the bill, so we cannot be certain how this solution would have worked.  But with all likelihood, the core problem would remain, and the “selection agency” function would similarly be exposed to capture by the industry, not to mention any other number of unintended consequence. Likely, there would have been multiple unintended consequences including the eventual capture of the selection agency by industry interests. 

The issue with the rating model is that the government is involved, unnecessarily, and not in a way that advances or incentivizes accurate measurement.  The solution, then, is not to increase government involvement.

We can easily identify a better solution by understanding how the credit rating business became distorted and then removing the causes of this distortion. In the early 20th Century, Moody’s and its competitors were small firms that sold rating manuals to investors. After Depression-era bank failures and the inception of federal deposit insurance, bank regulators began using the ratings manuals to determine which companies banks could lend to. Since the 1970s, regulations based on credit ratings were extended to other financial players, and the SEC began to license and regulate rating agencies.
These interventions created barriers to entry for competitors while making the ratings themselves valuable to bond issuers – since the ratings determined whether many types of investors could buy certain bonds. As a result, credit rating agencies had been handed a powerful and exclusive tool – one they could monetize by selling ratings to bond issuers.

Instead of adding more bureaucracy as Franken proposed, a better solution is to dismantle the entire regulatory apparatus. Let’s allow anyone to issue credit ratings on a level playing field and divorce these ratings from all financial regulation. It will then become the investor’s responsibility to choose which rating agency to trust, giving credit raters – both incumbents and disruptors – the incentive to provide better ratings.

Although Franken was a smart legislator, his policy positions may have been compromised by a worship for power, just as the various groping allegations appear to have been the result of an abusive exercise of power.  Likewise, increasing financial power through regulation – as Franken proposed to do – creates opportunities for abuse. Rather than concentrate power we should be trying to disperse it – in Washington, on Wall Street and beyond.  In this way, we can prompt financial market participants to be more accountable for their own investment decisions, and more directly responsible.


Marc Joffe is a Senior Policy Analyst at the Reason Foundation and a researcher in the credit assessment field. He previously worked as a Senior Director at Moody’s Analytics. This article reflects his personal opinion, and not necessarily those of PF2 Securities.

Friday, November 17, 2017

Developments in FX and US Treasuries Litigation

An interesting week. Two developments emerged concerning possible behind-the-scenes activities in two of the largest markets – foreign exchange (FX) and U.S. Treasuries (bills, notes and bonds). 

The New York Department of Financial Services (NY DFS) fined Credit Suisse $135 million for FX wrongdoing. And plaintiffs in a class action alleging manipulation in the U.S. Treasuries market filed a new complaint with additional allegations.


ForEx

The NY DFS consent order presents its findings that Credit Suisse engaged in a myriad of transgressions in the FX market – including: 
  • Efforts to manipulate prices around the “fix” and improper sharing of customer information with traders at other banks, e.g.: 
    • "... Trader 1 discussed with Trader 4 an effort to “unload” ammunition. Trader 1 stated “get ready unload on nzd,” to which Trader 4 replied, “I am. Nearly hit it last time.” As the fix drew near, Trader 1, referring to an unidentified co-conspirator, remarked “if he can’t get it lower we may be in trouble.” After apparent success, Trader 1 remarked “come to poppa,” while Trader 4 retorted, “phew.” "
  • Attempts to front-run customer orders, e.g.: 
    • " In one instance in February 2013, a Credit Suisse trader, Trader 1, disclosed potentially confidential information obtained from the Credit Suisse sales desk about FX trading associated with a pending merger and acquisition: “I think there’s some lhs2 action today at the fix on the back of tht massive m+a . . . massive caveat, info is from sales desk . . . but 4 o clock. . . . 16 yrds . . . something to do with the equity leg is going thru today . . . that’s the reason they saying the spot will be done.” "
  • Collusion with other banks to maintain wide bid-offer spreads
  • Price manipulation on behalf of certain customers, e.g.: 
    • " On September 7, 2012, a Credit Suisse customer (“Customer 1”) enlisted the assistance of a Credit Suisse trader, Trader 18, in seeking to push down the price of the U.S. dollar/Turkish lira pairing. Customer 1 asked Trader 18, “can you walk down usdtry for me pls.” Trader 18 replied, “Yeah, no problem.” Customer 1 then stated, “just offer 1 at like 72 . . . just walk it brotha,” to which Trader 18 replied, “No sweat.” Customer 1 cheered on Trader 18, saying “come on . . . just walk it,” to which Trader 18 replied, “Collapsado.” Apparently upon achieving success, Customer 1 stated, “thks [Trader 18] for walking it down . . . great job . . . you really shellacked it.” Trader 18 quickly replied, “pleasure.” "
  • Abuse of last look via its electronic platform
  • Deliberately triggering (and front-running) customer stop-loss orders
This last item is particularly noteworthy – not because Credit Suisse is the first to be accused of intentionally triggering stop-loss orders (it’s not), but because the bank apparently wrote an algorithm to calculate the likelihood of successfully triggering stop-loss orders that were potentially ripe for targeting.  In so doing, the bank seems to have systematically developed a system for deciding which stop-loss orders to target.

The penalty imposed by the NY DFS is the first FX-related regulatory fine imposed against Credit Suisse. In contrast, Swiss competitor UBS has settled with the CFTC, Federal Reserve, FINMA (Swiss regulator) and FCA (UK regulator), as well as class action plaintiffs in the U.S. and Canada, for a total of nearly $1.3 billion. 


U.S. Treasuries 

In the consolidated complaint, styled In Re Treasuries Securities Auction Antitrust Litigation (1:15-md-02673), plaintiffs indicate that they have evidence in hand, such as chats and emails, which shows bank traders sharing customer order information with traders at other banks (but by our reading they don't seem to have produced said evidence). 

According to the complaint: 
“Plaintiffs have obtained documents relating to the DOJ’s ongoing investigation, which confirm that such trader communications occurred. These materials include online chat transcripts in which the Auction Defendants shared the identities (often using code phrases) of their indirect bidder customers, the details of those customers’ order flow, and other private customer information.” 
Interestingly, plaintiffs have broadened the scope of the complaint, to include wrongdoing in the secondary market.  Plaintiffs allege, anew, that dealer banks have conspired to boycott trading platforms that would enable market participants to trade with each other on anonymous all-to-all platforms, such as eSpeed and Direct Match: the theory being that all-to-all trading platforms could be a threat to the status quo of dealer dominance of the secondary trading market, potentially putting dealer trading revenues at risk. 

The boycotting allegations are similar to those made against interest rate swap and credit default swap dealers in cases such as In Re Interest Rate Swaps Antitrust Litigation (1:16-md-02704) and Tera Group, Inc. et al v. Citigroup, Inc. et al (1:17-cv-04302).


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For more detailed coverage of these matters, visit our piece here.

Monday, October 30, 2017

The Cost of NOT Investing

Asset price bubbles are a tricky thing. 

Recognizing a bubble may be tough enough.  Predicting its bursting is another story altogether.  Like earthquakes, both the timing and magnitude of a pop is difficult, if not impossible, to measure.  And then there are the after-shocks, similarly difficult to quantify, although we may think we know a thing or two about them.

Now once you think you're seeing a bubble -- after all, a bubble is a bubble -- does that mean you should not invest?

Welcome to the Land Down Under

We're not going to take a position on whether the Australian housing market is in a bubble or not.  But we'll tell you that its an ongoing debate.  And this debate has been, err, ongoing for well over 15 years.

Earlier this month, the Economist put out an interesting article that included this diagram.  Wow, or booya, it sure looks like a housing bubble, doesn't it?


But, on deeper investigation, the blue line was also disconnected from population growth or per-person-GDP way back in 1990.  Wouldn't that mean it was a bubble already in 1990, or certainly 2003.  Well...

In May 2003, the Economist magazine put out a story called House of cards, in which their economics editor explained that:
"Over the past few years, house prices have been booming almost everywhere except Germany and Japan. Since the mid-1990s, house prices in Australia, Britain, Ireland, the Netherlands, Spain and Sweden have all risen by more than 50% in real terms. American
house prices are up a more modest 30%, but that is still the biggest real gain over any such period in recorded history. Commercial-property prices in some big cities have also been looking rather frothy."   
... and ...  
"This survey will conclude that the latest housing boom has inflated bubbles in several countries, notably America, Australia, Britain, Ireland, the Netherlands and Spain. Within the next year or so those bubbles are likely to burst, leading to falls in average real house prices of 15-20% in America and 30% or more elsewhere over the next few years, in line with average price declines during past housing-market busts."

Looking back at this now ... more than 14 years later, it has been one-way traffic in Australia.  Had you invested a dollar in Australian housing in May 2003, it would be worth over $2.1 dollars today.  You would have more than doubled your money.  And the biggest one-year dip in house prices, according to an index that weights the eight largest Australian cities, was approximately at the 1% mark.  Hardly a 30%+ correction.

In June 2005, the Economist would continue with an article called In come the waves explaining that "America's housing market heated up later than those in other countries, such as Britain and Australia, but it is now looking more and more similar."  In this article, the Economist would not quite call Australia a bubble, but worse, would allow that inference based on a diagram and some "compelling evidence" and also would misdiagnose a correction in Australia.

"The most compelling evidence that home prices are over-valued in many countries is the diverging relationship between house prices and rents. The ratio of prices to rents is a sort of price/earnings ratio for the housing market. Just as the price of a share should equal the discounted present value of future dividends, so the price of a house should reflect the future benefits of ownership, either as rental income for an investor or the rent saved by an owner-occupier."

"Calculations by The Economist show that house prices have hit record levels in relation to rents in America, Britain, Australia, New Zealand, France, Spain, the Netherlands, Ireland and Belgium. This suggests that homes are even more over-valued than at previous peaks, from which prices typically fell in real terms. House prices are also at record levels in relation to incomes in these nine countries."

"The rapid house-price inflation of recent years is clearly unsustainable, yet most economists in most countries (even in Britain and Australia, where prices are already falling) still cling to the hope that house prices will flatten rather than collapse."

Looking back at this one now ... had you invested a dollar in Australian housing in June 2005, it would be worth over $2.0 dollars today.  Doubled your money.  And no flattening and certainly no collapse.

Conclusion

Our point is that, sometimes you can decide a bubble is a bubble, but if you don't invest you might protect against a chance of losing 30% (if the economists are right, which they more regularly are not), but you've also lost the chance of making 100% in this example. 

Australia is an unusual case: they have had 26 years of pretty much unabated growth without a recession, although they have come close.  The story Australia helps tell, though, is important. 

It's easy to constantly call a bubble, and maybe one day you'll eventually be right.  But in the meanwhile ... is losing 30% by investing any worse than missing out on making 30% by not investing?

Wednesday, August 30, 2017

A Three Hour Trading Day ... or Two

The equity markets are open from 9:30 am to 4:00 pm Eastern.  Trading does occur after-hours, but it's really a 9:30 to 4:00 pm job, or trip, or whatever we want to call it.

It used to be 10 am - 4 pm, until 1985, when NYSE voted to start half an hour earlier to accommodate overseas buyers.  Californians weren't happy: they would now start trading at 6:30 am local time.

But the game is a-changing.  Markets are different to what they once were, and a good portion of trading is done electronically, and often by automated "bots."    And nowadays, many traders sit idle during long stretches between market opens and market closes, during which there is a typical flurry of activity (40% at market close, on average, last week).


Which leaves us to propose two alternatives. 

 A shorter trading day, say 1 pm - 4 pm.  Or splitting the trading day into two trading windows, say 9:30 - 10:30 am and 2 pm - 4 pm.

Here are the many advantages, including several social benefits.
  1. The markets would be more liquid.  Always. (Reducing costs, adding efficiency.)
  2. There would be more "off-trading" hours for companies to release earnings reports and any other news items that might "shock" markets.  (Traders wouldn't have to stick around till 6 or 7 pm to watch Apple release its earnings reports.)
  3. Traders could spend more time on research & strategy, and less time glued to their ever-changing screens.
  4. Some traders, if they're only performing a pure trading function, would become cheaper for firms, creating an efficiency.  They could take part-time work outside of trading hours, or walk their kids to school.
  5. Traders could leave the office for lunch with their colleagues without worrying about the market moving on them, promoting healthier working relationships, and driving business to nearby restaurants.  Or they could go to gym midday, lowering healthcare costs.
  6. The west coast traders would no longer have to wake up before the sun rises to start trading, creating more stable family relationships out west.  (We acknowledge we're making several conclusory assertions here!)
There would be some losers, like the exchanges (perhaps, although arguable) and those overseas traders.  But they can work from home these days, and keep trading after dinner, or set up their robots to take care of things!  

We welcome any pros or cons to be added to our list: we're know we're missing many ideas.