Levine on cunning financial engineering: when synthetic becomes real

I think I’ve mentioned before that I’m a big fan of Matt Levine over at Bloomberg View.  He’s experienced and geeky enough to make comments like the following: a certain debt refinance deal, involving transferring CDS premium from sellers to the defaulted entity, is ‘…objectively beautiful.’  Who says modern media must pander to the lowest common denominator?

Anyway, Levine’s latest article excited both my financial geekiness (I agree with this ‘beautiful’ statement) and more real-world geekiness (I frequented RadioShack in my youth, and actually did buy circuit board parts from the back).

One of the key points of the article speaks about how synthetic/esoteric derivatives (such as CDS) can influence ‘real’ markets (such as company loans, keeping the company afloat).  With this week’s quadruple-witching, whereby pretty much all futures/options series make a roll, it’s always worth asking whether the huge swings we’ve witnessed are

• ‘Real’, in terms of folks actually showing dramatically shifting risk tolerance; or
• ‘Synthetic’, in terms of the biggest derivatives houses using this roll period to ensure their exposure is minimised (which, in theory, can be done by manipulating – not necessarily illegally! – ‘real’ underlying markets).

A dire situation…or why it’s very fortunate to live in a reserve currency country

So Russia’s currency fell quite a bit yesterday, but today’s intervention by their finance ministry is stabilising things (so far, -ish) at around 70 RUB to the USD.  For those keeping track, that’s about a 50% devaluation since the beginning of the year.

Care for some RUB? Nyet. Source: Google Finance

OK, 50% seems like a crazy number.  What does it actually mean?  For most of us living in places like the US or UK, the idea of a currency depreciation doesn’t come naturally; unless we travel a bunch or have an export/import business on the side, FX rates aren’t an everyday concern.  But when your country imports 40% of food, for example, the situation isn’t pretty.  The lady quoted in the article is already paying 20% extra, a week into this depreciation.  People are worried what their salaries will buy.  This is sounding like the early stages of hyperinflation, where loss in the faith of a currency as a store of value can get bad, fast.

This is perhaps a concrete reminder of what gold bugs and Tea Partiers and such have been saying is the inevitable fallout from the Fed’s quantitative easing: namely, a dollar worth nothing.  They advocate buying real assets (such as gold, though I’ve already expressed my reservations there) to protect against a big dollar crash.

To be clear, however: the US and UK are very unlike Russia and other emerging countries.  The main difference, in this context, is having wide and deep financial markets denominated in domestic currency.  Let me explain:

• Who really has the power?  Lenders.  As much as we like to define power as military strength, in these days of relative peace the marginal power lay with the lenders.  Pretty much all governments rely on borrowed money to function; even the US government went through a completely idiotic own-goal by refusing to allow itself to borrow (NB: Tea Party, I blame you).
• What do lenders need?  Trust in borrower.  Remember that a lender’s best-case scenario is to receive back his principal + interest.  He can lose all of his principal.  In the case of US or UK, lenders are just fine receiving an IOU; they have faith they’ll be fully repaid.  With Russia and other emerging economies, lenders frequently require collateral; this frequently comes in the form of foreign exchange reserves, so lenders can seize ‘hard currency’ if needed.
• The key difference: domestic versus foreign currency borrowing.  Keep in mind that countries like the US and UK (and Russia) have fiat money, which means the USD and GBP (and RUB) are worth whatever the government and users say it’s worth.  Furthermore, all these governments have printing presses, allowing them to repay domestic currency debt with newly-printed money.  As a lender, then, the question becomes how likely you will be repaid with domestic currency worth anything.  If there’s doubt, the lender will only lend using (a more stable) foreign currency; for example, many emerging countries borrow in USD.  Once the borrower goes the route of foreign currency, the government has lost control of his debt burden; if his local currency devalues, it’s bad news bears.
• An interesting contrast, then.  Even with explicit repayment of government borrowings with newly-printed money (i.e. quantitative easing), the US and UK have rarely seen lower costs to borrow.  In contrast, Russia can’t get enough faith in their currency to keep the ruble alive: they need to intervene in foreign exchange markets to convince lenders that the ruble can and will stabilise in order to obtain debt financing for their government.  This is crucial, as with a low oil price Russia’s government has no hope of funding itself.  The US and UK have adopted almost the exact opposite (indeed, Switzerland adopted the exact opposite) approach: trying very hard to convince folks all the newly-printed money should cheapen their currencies, thereby stimulating demand.

In sum: the life of everyday Russians is getting worse and worse as their currency goes down the toilet.  Though the same problem could happen in the US or UK, in theory, the latter governments’ reliance on domestic-currency borrowings suggest nothing like the Russia situation in the foreseeable future.

A cold winter lies ahead for Russia

Anybody got a bid? Ruble versus USD. Source: thinkorswim by TDAmeritrade.

Remarkable move in the Ruble… Low of 78 to the USD today, which is about a 40% depreciation (is it fair to use the world ‘devaluation’ here?) in the past week.  The relevant quote from Bloomberg:

“Our traders are informing me that we see no bids to buy rubles,” Per Hammarlund, chief emerging-markets strategist at Skandinaviska Enskilda Banken AB, said by e-mail from Stockholm. “I thought 17 percent would give them at least a month of breathing space. We next have to look at the experience in 1998-1999. We are also one big step closer to capital controls.”

Yikes.  What impact will this have on the powers that be in Russia?? I presume most of the aristocracy are very much USD-liquid, so this crash in rubles will likely be a bigger problem for the masses.  Not good.

Let there be…vol?

Will there be calm, or more party time? Source: Google Images

So this is probably the last ‘serious’ week for financial markets of 2014.  Some thoughts:

1. Is oil done?  The news seems more bent on $40/barrel oil, or at least $50, so another 10-15% down move from here.  I’m sure many recognise that the media is generally way late to the party, so perhaps today’s slight recovery to above $58 is putting in the near-term floor.  My momentum models don’t care about the debate, and are staying well-short.
2. Which is right: VIX or S&P?  Last week’s rise in the VIX, from about $12 to about $19, was an outlier move – similar to what happened last October.  So are we due for an exciting, proper sell-off in the S&P?  Or is this morning’s resilience in the index (up about 1%), combined with VIX selling off (down about 3%), the more relevant fact?  On Friday I reloaded on my old favourite UVXY trade, so I’m clearly hoping the latter.
3. I feel bad for being long grains.  My same momentum models have me long soybeans, which has been a pretty good trade so far.  However I can’t ignore the oversupply, which I hear from family in the Midwest.  Another example of how the biggest enemy to a systematic trading approach is probably manual intervention.

In sum: I’d like a quiet week.  My models would prefer a chaotic week – or at least a continuation of that lovely oil trend.  With the remaining economic news of 2014 released this week, combined with rolls/option expiry, I’m guessing there will still be plenty of action.

No Christmas for oil producers

Yeesh.  This is what capitulation looks like.  Oil just can’t catch a bid:

Look out below!!! Source: thinkorswim by TDAmeritrade.

Must be Christmas… a nice list of free quant trading tools

Happy Christmas, you quanties. Source: Google Images.

Every once in a while a look through my LinkedIn feed unearths a juicy(?) nut.

Thanks to Mr Madan for posting this quite impressive list of open-source trading platforms.  

Perhaps a good time for a slight tangent: a few years ago, when I started developing quant strategies, I was pleasantly shocked to find out about open-source software, and particularly how deep these offerings were.  It’s frankly AMAZING that, for just about any software developing requirement I’ve ever heard of, there’s a free open-source solution.  Hence my love for languages such as Python and R, databases such as MySQL, and tools such as Spyder and Sequel Pro.  Oh, and stackoverflow: not only are the tools free, but the tech support is free and generally kind.  Oh, and Quandl for free data.

In sum: always look for the open-source alternative if you come across a software need.

Ignore John Bogle???

I was reading this Marketwatch piece this morning, and find the topic quite interesting. There is plenty of opinion out there that equal-weighted indices outperform market cap-weighted indices.  And when you look at RSP versus SPY, you indeed see the result.

Why would you choose RSP over SPY?

1. Why index? The conventional reason folks choose stock indices (especially broad-market indices, such as SPY) is to diversify away specific company risk.  We know that holding equity should pay a return in the long run; we just don’t want to get unlucky choosing a bad equity.  So we invest in everything, looking to average returns.  RSP, by investing equal amounts in each of the S&P 500 constituents, has more diversification than SPY.
2. What about rebalancing? The recent article by Campbell Harvey et al. is instructive here.  It turns out that regular rebalancing increases risk versus keeping a static portfolio.  So perhaps RSP pays more than SPY because it’s taking the extra risk.  Indeed, this is reflected by RSP’s 1.11 beta versus SPY: the former takes roughly 11% more risk than the same $ investment in SPY.  At least for the past year, the return of RSP has been about 1.11x SPY, so I guess the risk/return level is about commensurate.  Anyway, I could just suggest buying more SPY than buying RSP.
3. What about momentum? See the same article.  SPY, like other market cap-weighted indices, implicitly take a momentum approach to the market. Because there is no rebalancing in SPY, the fund will automatically allocate more capital to stocks with higher returns (and thus higher market cap).  Given momentum is a lasting source of return, you’re essentially getting a trading strategy for free in choosing SPY over RSP.

So what to choose? If capital were no issue, I’d probably just buy more SPY than going smaller in RSP.  I like the lower management fees (yes, I do agree with John/Jack Bogle on that point), and appreciate the implied momentum returns of SPY.  If capital were an issue, I’d think of RSP like IWM: a way to achieve higher returns for the capital than SPY, mainly due to overweighting smaller companies.

Autonomous agents and genetic algorithms…oh my!

Input = binary. Output = $$. Source: Google Images.

The latest book I’m reading is Professional Automated Trading: Theory and Practice by Eugene Durenard.  I’m about a quarter through; in the words of my dad, it’s way cool.

The book has that certain exoticism which probably appeals to a wide range of financial geeks: lots of mentions of hard sciences; passionate disregard of prevailing ‘rule of thumb’ approaches to valuation and trading; and the creation of a robot-army, led by a robot general, to achieve trading success in a landscape filled with chaos and complexity.  If this gets your interest piqued, I suggest purchasing a copy.

OK, back to Earth for a second.  Having not read the full book yet (but the early summaries give a pretty comprehensive overview of what’s to come), I wonder how much of the theory can and does get put into practice.  From the veneered description above, I clearly want to believe the secret to endless trading profits is a fantastically-engineered army of automatons.  However, it’s been my experience from reading more practical trading literature, as well as working in various trading shops, that higher complexity = higher disappointment.  The development cycle I’m accustomed to runs a bit like:

1. I test a basic hypothesis, such as ‘the oil price trends’.
2. I come up with a trading rule, having verified #1.  Perhaps a basic breakout strategy.
3. The basic strategy in #2 looks OK-ish, but I notice a few really bad apples among the backtested trades.  So I create a filter rule to ensure trades like them don’t happen.
4. I test #3 with the same data.  Perfect.  So now I test out-of-sample data.  Guess what? #3 stinks compared with #2.
5. Repeat #3 and #4 until I finally give up trying to find a filter rule, and stick with #2.

The idea of continuously-evolving trading robots, or a static robot army led by a continuously-evolving general, sounds a bit like an in-line version of the above sequence.  Maybe, after enough trials, the robot general will beat my logic and analysis – I’m open-minded.  Perhaps that’s why I’m keeping with the book.

In sum: the financial markets offer numerous ways to get very complicated and technical.  Sadly for yours truly, I haven’t yet found a complex ‘golden nugget’ strategy which consistently outperforms more simple trading implementations.  But I keep searching…

From Cournot to Bertrand equilibria: OPEC giving discounts

Dusting off my old economics lessons, I recognised a couple concepts from today’s Bloomberg article on Iraq joining Saudi Arabia in giving oil price discounts.

In particular, oligopoly behaviour can frequently be modelled by quantity-based competition (Cournot, and old OPEC) or by price-based competition (Bertrand, and what we see today in OPEC).  The key point, as this Brown University lecture note states very well, is:

We conclude that in a Bertrand equilibrium, in the homogeneous good case, under the assumptions we have made, firms 1 and 2 will charge the same price, and the price will be equal to marginal cost. But this means that the duopoly market, in the Bertrand model with a homogeneous good, looks just like a competitive market. In particular, there is no inefficiency (no loss of social surplus) in the duopoly market. 

So go ahead and call up your local OPEC representative and thank him/her for providing a market-clearing, maximum efficiency price for oil consumers.  WTI oil has broken $63/barrel recently, which surely means $1.75/gallon gas for US drivers at some point??

Yes, I would pay 2 and 20

Who is dumb enough to pay 2 and 20? Me, actually. Source: Google Images.

The alternative investment world (namely private equity and hedge funds) has grown fat on the 2 and 20 fee structure.  For those unaware, that means 2% p.a. management fees, plus 20% of all investment gains, paid by the investor.  Sounds steep, right?  It is.  With the poor relative returns of alts the past five years (versus a screaming S&P 500, I mean), there has been much vitriol over the old fee structure.  A watershed moment may have been Calpers’s decision to close its hedge fund portfolio; I say watershed mainly because of the publicity generated, rather than the impact on the alt investment business.  With $4bn in hedge funds, Calpers wasn’t close a huge hedge fund investor.

As I was walking today I reflected on the fee structure.  Why did it happen, and why or why not pay that amount?  My notes:

• Genesis: I imagine a smart guy working for a big bank or asset manager.  Suppose he comes up with a great strategy:
  • Will the bank or asset manager compensate his for this luck/skill?  Maybe: it definitely worked for a guy like Andrew Hall.
  • But maybe not: what does this guy do then?  Perhaps he starts trading his own money, or those of a close circle: thus begins prop firms, which are ubiquitous in the business.  Especially for strategies that are low-capital outlay and/or high ‘edge’ (e.g. discretionary macro or HFT market making, respectively).
  • Finally: he decides to start his own fund, managing public money.  He needs enough capital to do 2 things, preferably simultaneously:
    • Pay the bills: office expenses, Bloomberg feed, etc.
    • Incentivise the manager: this guy supposedly has a great idea, so he wants to be compensated for making others rich.
• Why 2 and 20? How about some quick and dirty math:
  • Yearly office expenses, including hiring a couple guys to make the fund viable (I have in mind a CRO/COO and a CFO/CLO, with ~$150k salary each) probably runs $500k-$1m.  Starting capital for a fund is frequently targeted at around $25-50m.  So 2% of this amount pays the office expenses.
  • Of course the strategy type matters here, but let’s imagine the expected gross (pre-fees) performance of the strategy is 15% p.a. The owner of the fund company (the guy who came up with the strategy) gets 20% * (15% – 2%) = 2.6% of AUM p.a. in incentive fees.  With $25-50m AUM, and a successful year, the strategy owner makes $650k-$1.3m for managing the fund.  So our guy with a great idea made a million bucks (assuming he gets all the performance fee).
  • Hopefully this quick illustration shows why 2 and 20 is so ‘standard’: at reasonable startup AUM, this is the sort of fee structure needed to pay office expenses + give enough incentive to the guy with the strategy in the first place.
• Where did/does it go wrong?  I think 2 and 20 can be contrasted with a group like Vanguard (pre the news this morning that the latter may have used taxpayer funds to subsidise its operations).
  • As AUM swells, the 2 becomes a larger and larger profit centre for the fund.  At some point, the 20 becomes just an upside call, with 2 being the prime focus.  That’s when fund volatility drops, institutional investors (wanting low volatility and lower fees for high-AUM checks) are in charge, and hedge fund performance starts dragging.  I don’t think I’m unique in spotting that hedge funds relying on the 2 frequently begin to ‘calm things down’ to protect assets.
    • Aside: I recall being on the road, listening to long-time clients saying ‘please don’t drop your volatility target…I am paying you for the volatility’.  Thankfully there were enough of those investors to keep AUM at a sustainable level, so the target didn’t need to be compromised.
  • Groups like Vanguard instead use the higher AUM to spread their office expenses wider and thinner… management fees as a % drop as AUM increases.  Though this frequently happens with hedge funds as well (fee discounts become more and more common), the Vanguard model is more explicit and mechanical, and benefits investors equally.
• OK, back on point.  When would I pay 2 and 20?
  • I believe in the strategy.  Clearly.
  • I’m convinced the 2 is used to pay office expenses.  That means the organisation running the fund needs that fee level to sustain operations.  I don’t want the smart guy with the strategy fretting whether to buy a data set because the check will bounce.
  • The fund owner(s) are satisfied, but a bit hungry, with the 20%.  I want my asset manager rich, but I want him to keep trading my money.  So not too rich to do silly things, nor so rich that he/she walks away.  Also, not making so little that his/her opportunity to go back to the bank/big firm becomes the right choice.  To be clear, having a high-water mark is a necessity: no multiple bites!
  • I’m convinced the fund will hang around, and be consistent with strategy.  One of the issues with small funds is their unfortunate tendency to blow up – hence why institutional investors tend to prefer large, steady return streams of big hedge funds.  As a small private investor, I want the ‘juice’ of the strategy in as pure and concentrated form as possible while keeping the business alive.  I will not pay 2% a year for a strategy expected to return 5% net of fees, for example.  If it’s expected to return 15-25%?  Now we’re talking…

End soapbox.