The first two numbers you compute for any long/short book are gross exposure and net exposure:
Gross exposure = (long positions + short positions) ÷ AUM. Net exposure = (long positions − short positions) ÷ AUM.
What do gross and net exposure tell you?
Gross tells you how much capital (and, implicitly, leverage) the book has at risk in total; net tells you the book's residual directional bet on the market. A fund can be "130/30" (130% long, 30% short, 100% net long, 160% gross) using the short book to fund extra long exposure while still running full market beta. A fund can instead run "market-neutral" (long and short books of roughly equal size, net exposure near zero) in which case its return should come almost entirely from the spread between what it owns and what it shorts, not from the market's direction.
Worked (illustrative, India ₹). Sahyadri Long/Short Fund (synthetic), AUM ₹500 cr: long book ₹350 cr, short book ₹150 cr.
Gross exposure = (350 + 150) ÷ 500 = 100.00%, one full turn of AUM at risk, long and short combined. Net exposure = (350 − 150) ÷ 500 = 40.00%, despite 100% gross, the fund is still a net-long, beta-carrying book at 40% of AUM.
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How does a market-neutral pair trade work?
Now take a single pair trade out of that book: ₹10 cr long Konkan Bank (synthetic), ₹10 cr short Malabar Bank (synthetic), a same-sector, dollar-neutral pair built on the thesis that Konkan will outperform Malabar, with no view on banks or the market generally. Two scenarios, both fully computed in Python (see the Worked Examples section for the identical mechanism spelled out in full): if the market rallies and Konkan rises 8% while Malabar rises only 3%, the long leg gains ₹0.80 cr and the short leg loses ₹0.30 cr (you owe the 3% rise back), netting +₹0.50 cr (+5.00% of the pair's capital). If the market instead falls and Konkan falls 2% while Malabar falls 7%, the long leg loses ₹0.20 cr but the short leg gains ₹0.70 cr, netting the identical +₹0.50 cr (+5.00%). The position made the same money whether the market rose or fell, because what it was actually betting on (Konkan beating Malabar by five percentage points) happened both times. That is what "market-neutral" means mechanically: the P&L depends on the return differential, and the shared market move cancels out of the arithmetic by construction.
{
"skill": "Sanity-checking a long/short fund's exposure claims before trusting a pitch deck",
"use": "Have a chat assistant turn a fund's disclosed long-book and short-book figures (from a pitch deck, a factsheet, or a Form ADV brochure you already hold) into gross and net exposure, and flag any inconsistency with the fund's own stated strategy label (e.g., a fund calling itself 'market-neutral' with a large net exposure).",
"tools": ["Chat assistants — Claude, ChatGPT (fed the actual document, not asked to recall figures)", "Spreadsheet/code tools for the arithmetic itself"],
"prompt": "Here is page <N> of <FUND>'s factsheet, showing long exposure <X>% and short exposure <Y>% of NAV. Compute gross exposure and net exposure, and tell me whether that net exposure is consistent with the fund describing itself as '<STRATEGY LABEL>' on page <M>. Do not use any figures you were not given in this document.",
"verify": "The exposure figures themselves are only as good as the factsheet — trace them to the fund's own investor letter or Form ADV brochure (Guardrail #1, Trace), confirm the reporting date (Guardrail #4) since exposure is a snapshot that can be materially different a month later, and recompute the gross/net arithmetic yourself (Guardrail #3) rather than trusting the model's division.",
"diy": "You must already be able to compute gross and net exposure from raw long/short figures by hand — this section teaches exactly that — before delegating the lookup-and-arithmetic combination to a tool; otherwise you cannot catch the model quietly using the wrong denominator (AUM vs. NAV vs. committed capital all appear in real documents).",
"market": "IN"
}