Quant Memo
Core

Long/Short Equity

The most common hedge fund structure — own the names you like, short the names you don't, and keep some deliberate net long exposure. The shorts fund the longs and dampen the drawdowns, but they also add borrow costs, gap risk and a beta you almost certainly measured wrong.

Prerequisites: Beta (β), Alpha (α)

Long/short equity is what most people mean when they say "hedge fund". Alfred Winslow Jones set the template in 1949: buy the stocks you think are good, short the stocks you think are bad, and use the shorts as a hedge so you can safely lever the longs. Seventy-five years later, roughly a third of hedge fund capital still runs this way. The structure is simple. The bookkeeping around it — gross, net, beta, borrow — is where the strategy is actually won or lost.

Gross, net, and why both matter

Two numbers describe the shape of any long/short book, and beginners routinely quote only one.

  • Net exposure = longs minus shorts, as a fraction of capital. It tells you how much market you own.
  • Gross exposure = longs plus shorts. It tells you how much stock-picking risk you are running, and how much financing you need.

A fund with $100m of capital, $100m long and $50m short is a "100/50" book: net +50%, gross 150%. Another fund could be 200 long and 150 short — the same +50% net, but 350% gross. Same market exposure, wildly different sensitivity to whether the stock picks are any good. Net is the market bet; gross is the alpha bet.

Your net exposure is not your market exposure

Here is the mistake that costs money. Net exposure counts dollars. Markets move portfolios by Beta (β), and long/short managers systematically own high-beta longs and low-beta shorts, because the names they like are growing and the names they hate are tired.

Take the 100/50 book. Suppose the longs average βL=1.1\beta_L = 1.1 and the shorts average βS=0.9\beta_S = 0.9. The book's market exposure is

βbook=100×1.150×0.9100=11045100=0.65\beta_{\text{book}} = \frac{100 \times 1.1 - 50 \times 0.9}{100} = \frac{110 - 45}{100} = 0.65

Sixty-five percent, not fifty. If the market falls 10%, the book loses 6.5% before a single stock pick has been judged. Over a year in which the market returns 12%, this fund books 7.8% of pure beta and can call it alpha if nobody checks.

long book short book stated net beta-adjusted net +100% −50% +50% +65% zero exposure
A 100/50 book. Gross is 150% — that is the stock-picking risk. Stated net is +50%. But high-beta longs against low-beta shorts leave the true market exposure at +65%, and that gap is where "alpha" quietly turns into beta.

Net exposure is a dollar statement; market exposure is a beta statement. Compute βbook\beta_{\text{book}} from position-level betas, not from the net percentage, and hedge the difference with index futures if you want the number you claim to be the number you have.

Where the return actually comes from

Split the 100/50 book into two pieces. The first $50m long is matched against the $50m short — that is the hedged core, and it earns whatever spread the stock selection generates. The remaining $50m long is unhedged and simply earns the market.

Suppose the selection spread is 6% a year on the matched $50m. That is $3m, or 3% of capital. The unhedged $50m earns the market's 8%, another $4m, or 4% of capital. The fund reports 7% and a "long/short equity" label, and 4 of those 7 points were available from an index fund at four basis points.

Then subtract the costs the structure imposes:

  • Borrow. The $50m short book is not general collateral — good short ideas cluster in hard-to-borrow small caps. At an average 90bp fee that is $450k, or 0.45% of capital.
  • Turnover. Rebalance 150% gross at 200% annual turnover with 12bp round-trip costs: 150×2×0.0012=0.36150 \times 2 \times 0.0012 = 0.36, so 0.36% of capital.

Roughly 0.8 points of drag against 3 points of genuine selection alpha. A quarter of the edge is gone before performance fees.

What erodes the edge

Crowding on the short side. Shorts are where long/short books die, because losses grow the position instead of shrinking it. In January 2021, GameStop rose from around $17 to a $483 intraday print in three weeks. Funds with crowded shorts had to cover into a rising market, and covering consumes cash, which forces selling on the long side too — so a short book blow-up damages the longs that were fine. Melvin Capital lost roughly 53% that month.

Everyone owns the same names. In August 2007, quantitative long/short books held near-identical value and momentum positions. One large fund delevered, the shared positions moved, and margin calls forced the rest to sell the same longs and buy back the same shorts. Books lost 20–30% in three days on positions that were, on paper, hedged.

Beta drift. Betas are estimated on trailing data and rise in crises. A book measured at 0.65 in calm markets can realise 0.9 in a selloff, which is precisely when you were relying on the hedge.

Do not judge a long/short manager on total return. Regress the monthly returns on the index, and look at the intercept. Asness, Krail and Liew showed that a large share of reported hedge fund "alpha" is lagged market beta in disguise — illiquid marks make the beta show up a month late, so a naive same-month regression understates it. Use lagged betas as well as contemporaneous ones.

In interviews

Define gross and net separately and say what each one is for. Then immediately make the beta point: net dollars are not net market exposure, and show the βbook\beta_{\text{book}} calculation. Explain how the return decomposes into a hedged core plus an unhedged long stub, and be honest that the stub is beta. Finish with the asymmetry of shorts — losses compound the position size — and why that makes the short book the primary risk-management problem, not the longs.

Related concepts

Practice in interviews

Further reading

  • Jones, The Jones Nobody Keeps Up With (Fortune, 1966) — the original hedged fund
  • Asness, Krail & Liew (2001), Do Hedge Funds Hedge?
  • Chincarini & Kim, Quantitative Equity Portfolio Management (ch. on exposures)
ShareTwitterLinkedIn