Learning objectives
By the end you can:
- Classify any hedge fund strategy into one of five families (equity long/short, event-driven, global macro, relative value, managed futures) and state each family's return driver and its characteristic risk in one sentence apiece.
- Compute and interpret gross and net exposure for a long/short book, and explain, with a worked pair trade, why a market-neutral position's P&L depends on a return differential, not on market direction.
- Price a merger-arbitrage deal spread (the gross annualized spread and the expected-value return once deal-break risk is priced in) and explain the strategy's asymmetric payoff shape.
- Build a full 2-and-20 fee waterfall in Python: management fee, a hard hurdle (no catch-up) and a soft hurdle with 100% catch-up, and a high-water mark, carried through a multi-year path that includes a drawdown, and state precisely why the high-water mark can block an incentive fee even in a year whose return clears the hurdle.
- Explain master-feeder structures, side pockets, gates, and lock-ups as engineered answers to specific problems (tax/regulatory segregation, illiquid-asset ring-fencing, run risk, and funding genuinely illiquid strategies), and compute the numeric consequence of each for an investor.
- State why hedge-fund data is this program's highest AI-over-trust risk (R10) (no public financial statements, self-reported and survivorship-biased performance databases) and name the actual primary sources (Form ADV, SEBI AIF disclosures) that substitute for them.
- Reference, not re-derive, the mechanics this module borrows: covered interest parity and the carry trade (M7.06) for global macro, the credit-spread and priority-of-claims framework (E11.01) for relative-value credit trades, and the option Greeks (delta/gamma: DV1.02) for convertible arbitrage, so you spend your time on what is actually new here: strategy classification, fees, and fund structure.
Prerequisites & connections
Builds on. This is the Alternatives branch's first node and, like every branch-opening node in this Ring, carries no prerequisite, you can start here on day one. That said, the module leans on habits built earlier in the program: Phase 1's financial-statement fluency (a fund's NAV statement is just a very short balance sheet); Phase 3's M3.02 (beta and the CAPM, "net exposure" is nothing but a book's realized beta to the market, expressed in rupee or dollar terms instead of a coefficient) and M3.03 (the cost-of-capital intuition that makes a "hurdle rate" (a minimum return before a manager is paid for skill) feel familiar rather than arbitrary); and Phase 2's discipline of never taking a reported number at face value, which you will need the moment you read a fund's marketed "net return" and ask which investor's high-water mark it was computed against.
Three modules elsewhere in this Ring are referenced here rather than re-taught, exactly as this branch's authoring brief requires: M7.06 (International: FX, Flows & the Dollar System) already builds covered interest parity, the carry trade, and commodities-as-macro-signals from the ground up, this module borrows those mechanics wholesale for the global-macro section and adds only the fund-level lens (sizing, P&L attribution, fee structure). E11.01 (Credit Analysis & the Debt Investor's Lens) already builds the credit-spread decomposition (spread ≈ PD × LGD) and the priority-of-claims waterfall, this module borrows that framework for relative-value credit trades (capital-structure arbitrage, convertible arbitrage's credit component) without re-deriving it. M5.09 (Commodities, Real Estate & REITs) owns the cost-curve and cyclical-earnings lens that a managed-futures/CTA fund's commodity trend signals ultimately trade against; this module uses commodities only as one instrument in a systematic basket, and defers the full asset-class treatment to AL1.02 (Commodities, Real Assets & Infrastructure as Asset Classes), which follows this node. A fourth reference is forward-looking: DV1.02 (Options. Parity, Binomial & BSM + the Greeks) builds delta and gamma properly; this module takes delta as a given hedge ratio and shows only how a relative-value fund monetizes it.
Feeds into. AL1.02 (commodities/real assets, where a CTA's trend signals get their full macro treatment) and AL1.03 (digital assets, where several of this module's fund-structure issues (gates, redemption terms, and unverifiable self-reported performance) resurface in sharper form). It also feeds the portfolio-construction thread in AA1.01/AA1.02 (how much of a portfolio, if any, to allocate to an illiquid, fee-heavy sleeve is a risk-budgeting question, not a strategy question) and PW1.02/PW1.03 (side pockets are hedge funds' answer to the same illiquidity problem that closed-end private-market vehicles solve structurally by simply not offering redemption at all).