Basis Risk, Alpha Factories, and Being too Clever for your own Good
The beauty of a robust financial market is that you can make exactly the bet you want to make. Suppose you’re an American investor and you’ve found a really great company in, say, Argentina. You buy the stock, it rises 50% — but it’s priced in Argentine Pesos, which are down a little more than 35% in the last year, so in dollar terms you’ve lost.

The natural response is to hedge, and many investors do. Why make two bets when you’re only betting on one thing?

This is usually sensible, but not always. Consider the case of investing in an exporter located in a country that’s dependent on exports. In this case, the currency is a natural hedge: a lower Yen is bad for unhedged US investors, but it’s good for the companies they invest in. Put another way, investing in Japanese stocks and hedging out currency risk is equivalent to betting on a Yen devaluation and doubling down.

That’s precisely what WisdomTree’s DXJ ETF did: they bought Japanese stocks and hedged their Yen exposure. From November 2012 to May 2013, the Yen was devalued from 80 to 102, Japanese exports promptly rose, and DXJ’s assets under management rose about 18x. DXJ turned into one of the hottest funds, not because it made superior stock picks (it’s a purely passive vehicle), but because it “hedged” in a way that actually constituted doubling down on its bets.

DXJ hasn’t done terribly for subsequent investors, but they’ve missed out. Since that rise, it’s up another 38% or so, but it’s underperformed US equities and other ETFs, and lost around three quarters of its assets.

There’s a useful lesson for investors there: a “hedge” that doesn’t address the underlying risk of an investment can produce misleadingly good results, at least for a while.

Hedging as a Way of Life

DXJ is a retail-facing product. An institutional investor taking a view on Japanese equities and FX would probably trade the underlying index and hedge manually, rather than paying WisdomTree almost 50 basis points per year to execute some straightforward currency trades.

However, some risks are harder to hedge. An investor in airlines, for example, is taking a view on:

Consumer spending

Corporate spending

Oil prices

Short-term rates (if the airline issues floating-rate debt)

Long-term rates (if they use fixed-rate debt)

The dollar (planes and oil are priced in dollars, but some plane tickets might be priced in pounds or Euros)

Local elections (which can delay or accelerate new terminal openings)

National elections (which can affect who gets to compete with them)

Global warming (snow causes frequent delays in New York and Boston airports)

Long-term growth in credit card spending

The airline itself

The two schools of thought here are to either to evaluate these risks one airline at a time or one risk at a time. The classic stock-picking approach is to do this at the airline level; to model each company’s quarter based on its idiosyncratic risks, and to demand higher returns from companies with more hard-to-model risks and lower returns from the ones that are hedged. On oil, for example, a low-cost carrier with an inefficient fleet faces relatively more oil risk, and gets its valuation penalized accordingly. Delta owns an oil refinery, which reduces some of their oil risk; United has a Houston hub, which hedges their oil risk because whenever United is paying extra for oil, Exxon is buying more seats on their planes.

If you don’t want to take these risks, one approach is to divide the entire universe of investable equities into little clusters that are subject to similar risks, then invest in a balanced long/short portfolio within these sectors. In other words, instead of being positive or negative on airlines, you’re picking two or three to be long and three or four to short. You repeat the same process for semiconductor stocks, natural gas companies, auto manufacturers, and banks.

Any one of these portfolios will be extraordinarily boring. There just aren’t a lot of reasons for one company to out- or under-perform its immediate peers. But there are some reasons, and in theory the risk of such a portfolio is minimal, which allows investors to lever up. Often, they can lever up a lot: 6–8x equity is a good range to think of.

Call it the “alpha factory” approach. Set the allowed level of beta in each portfolio to zero — no profit or loss from any predictable source of randomness. And then lever up what’s left to produce streams of uncorrelated profits.

By taming the portfolio’s exposure to volatile, hard-to-predict factors, this strategy lets companies produce healthy risk-adjusted returns. With outcomes less dependent on luck, funds can be more meritocratic, i.e. they can fire faster. If you’re evaluating a long-only portfolio manager who is down this year, you can argue about which vagaries of the market were responsible. If you’re looking at a PM who spends 100% of his time on luxury goods companies, always runs a balanced portfolio, and lost money last month, it’s probably that PM’s fault.

But there’s a hidden factor exposure here: what if all the balanced, market-neutral, factor-neutral funds end up making the same trades? In the short term, this is great; if you’re long X and short Y, and someone else makes the same trade, both legs of your portfolio outperform at the same time. If your competitors are raising more capital, they slowly ease into the same trades you’ve already made, so your portfolio shows smooth appreciation.

Until, suddenly, it doesn’t.

Quant Quakes and Invisible Factors

September 1998 and August 2007 were very different times, but one thing they had in common was that they were months in which every correlation went to 1. In 1998, Italy/German bond spreads, US corporate high yield spreads, and the discount for announced-but-unconsumated mergers all moved together. In 2007, value stocks, momentum stocks, and complicated CDOs all traded the same way.

What had happened was that investors were levering up uncorrelated bets, but since they were all looking at the same historical data, they all made the same uncorrelated bets. A measurably low correlation will always equal 1 in a crisis, because the natural bettors on that relationship are all liquidating at the same time.

In hedging, we’d call it “basis risk,” i.e. the risk that the instrument you’re using to hedge doesn’t match the performance of the thing you’re hedging. 90% of the time, if you own shares of company X and you short shares of their closest competitor, you’re hedged. But sometimes that means owning IAG, shorting Ryanair, and suddenly realizing that the most important thing going on at Ryanair is that their competitor, IAG, is facing strikes.

Levered, hedged approaches based on backwards-looking correlations are a way to manufacture higher correlations in the future. You don’t have to know exactly where those risks will come from to know that they’re coming.

Premium Beta

One of the perennial debates in active management is over what counts as value-added alpha and what represents beta, i.e. the results anyone could get from market exposure. Over time, the definition of alpha has gotten more restrictive. Fund managers used to be able to take credit (and charge!) for things like momentum or value. Now, those are commodities, easily available in ETF form.

The usual definition I see is that if your returns can be matched by writing a simple list of rules based on a widely-available data feed, it’s beta. Buying stocks that are cheap relative to tangible book value: beta; buying stocks that are cheap relative to intangible brand value: still alpha, for now, but as soon as SurveyMonkey spins up an API that lets you instantly ask a thousand random Americans what kind of premium they’d pay for WD-40 or Hershey over the brand-X competitor, that strategy instantly collapses into beta.

But I’d argue for an even stricter definition of beta. Beta is the extent to which one fund’s performance can be predicted entirely on the basis of how a handful of their competitors are doing. You may not correlate with the S&P, or with any of the Fama-French factors, but if you correlate with somebody, neither of you will be able to charge high fees.

This isn’t uniformly terrible news for asset managers. Investors are risk-averse, so they hate to lose money. On the other hand, they’re generally not losing their own money, so they care about reputational risk. Going long this kind of beta means making a hedged bet: yes, you might lose money, but so will all of your peers; you’ll be embarrassed and collect a low bonus, but you won’t get fired.

However, as discussed, that’s just temporary. In the long term, all the easy hedges accumulate future risk, and the probability of a blowup asymptotically approaches 1.
['Byrne Hobart']
['Economics', 'Business', 'Quant', 'Finance', 'Investing']