Strategy is the source of return, not the asset label
Two funds can both trade equities and have entirely different strategies. One may buy a small number of companies for several years, another may maintain hundreds of market-neutral long and short positions, and a third may trade index options around volatility dislocations. The useful way to classify a strategy is by its return source, instruments, horizon, portfolio construction, catalyst, and failure mode.
Fundamental equity strategies
Long-biased or concentrated long–short equity begins with business and security analysis. The team studies the company’s industry, competitive position, management, financial statements, valuation, and catalysts. A concentrated fund may accept meaningful market exposure and allow a thesis to develop over several quarters. A market-neutral team may pair longs and shorts, limit factor exposures, and require a more explicit near-term path for estimates or price to change.
The return can come from earnings growth, a change in expectations, multiple re-rating, capital return, a strategic event, or a short thesis becoming visible. Failure can come from being wrong about the business, paying too much, underestimating financing or dilution, being early relative to the fund’s loss limits, or expressing the view in a security whose technical behavior overwhelms the fundamental case.
Event-driven strategies
Event-driven investing focuses on a defined corporate or legal process: merger arbitrage, spin-offs, restructurings, recapitalizations, liquidations, tender offers, litigation, bankruptcies, or index changes. The analyst estimates probability, timing, consideration, financing, legal conditions, regulatory risk, and the value if the event fails.
A merger-arbitrage spread isn't free money for waiting. It compensates the investor for deal-break risk, delay, financing, market movement, and uncertainty about the contractual outcome. A restructuring claim requires understanding priority, collateral, intercreditor rights, recovery, and the operating value available to distribute.
Credit strategies
Credit analysis begins with contractual claims and downside. Performing-credit teams assess cash flow, coverage, leverage, covenants, maturity, refinancing, and relative value. Distressed teams examine the entire capital structure, legal rights, restructuring alternatives, liquidity runway, and recovery. Structured-credit teams analyze pools of assets, waterfalls, triggers, prepayments, defaults, and model risk.
Unlike common equity, credit often has capped contractual upside but material downside if the borrower can't pay. The investor therefore spends considerable effort on what happens under stress, what assets support the claim, and where the security sits in the priority structure.
Global macro
Macro strategies express views on growth, inflation, monetary policy, fiscal policy, balance of payments, geopolitics, and market positioning through rates, currencies, commodities, equity indexes, and volatility. A macro thesis needs a transmission mechanism: not merely “inflation will fall,” but how falling inflation changes central-bank policy, yield curves, currencies, real incomes, or risk assets relative to what the market already discounts.
Macro portfolios can be discretionary, systematic, or hybrid. Timing is difficult because the economic thesis may be correct while positioning, policy reaction, or market pricing produces the opposite short-term move.
Relative value and arbitrage
Relative-value strategies trade pricing differences between related instruments: cash versus futures, one part of a capital structure versus another, one maturity versus another, convertible bonds versus the underlying equity, or similar securities across markets. The apparent spread must be evaluated after financing, borrow, hedging, optionality, liquidity, and model error.
These strategies can look low risk in normal periods but become vulnerable when leverage is reduced, financing terms change, or relationships that were assumed stable break simultaneously.
Systematic strategies
Systematic funds convert hypotheses into reproducible signals, portfolios, and execution. Families include trend following, carry, value, quality, mean reversion, statistical arbitrage, market making, volatility, cross-sectional ranking, and machine-learning approaches. A strategy isn't complete until it specifies the data, universe, timestamps, signal, rebalance, portfolio constraints, costs, execution, capacity, and monitoring.
The main failure modes are data leakage, overfitting, multiple testing, nonstationarity, unrealistic fills, ignored costs, crowding, capacity limits, vendor changes, and production bugs.
Activism and engagement
Activist strategies acquire meaningful positions and seek changes in governance, capital allocation, operations, strategy, or ownership. The investment case includes the standalone business, the proposed changes, shareholder support, legal mechanics, campaign cost, management response, and time. Engagement can range from private dialogue to public proxy contests.
A strategy comparison frame
| Strategy | Primary question | Typical evidence | Core risk |
|---|---|---|---|
| Fundamental equity | What is the market mispricing about the business? | Filings, customers, competitors, estimates, valuation | Thesis error, timing, factor and liquidity exposure |
| Event-driven | What will happen, when, and under which legal terms? | Agreements, filings, approvals, financing, case law | Break, delay, adverse ruling, financing failure |
| Credit | Will the claim be paid, and what is recovery if not? | Cash flow, covenants, collateral, maturity, capital structure | Default, refinancing, subordination, illiquidity |
| Macro | How will an economic force transmit into market prices? | Economic data, policy, positioning, cross-market prices | Policy reaction, timing, regime change |
| Relative value | Why should related instruments converge? | Pricing model, hedge ratios, financing, liquidity | Model error, basis widening, forced deleveraging |
| Systematic | Does a repeatable signal survive realistic implementation? | Timestamped data, validation, simulation, live monitoring | Leakage, decay, costs, capacity, production failure |
A course should teach these as operating systems, not as a list of labels. The next question is always how the fund’s people, data, trading, and risk functions are arranged around the strategy.