Hedge fund examples: 5 core strategies in modern portfolios

Bridgewater’s global macro model, Citadel’s multi-strategy platform, and merger-arbitrage trades around major acquisitions represent materially different exposures even though all operate within the hedge fund category.

The distinction matters because “hedge fund” describes a private pooled investment vehicle, not a single investment method. Managers may use long and short positions, derivatives, leverage, and financing through prime brokers. The result can be low market beta, concentrated event risk, duration exposure, basis risk, or a combination of independent books. A portfolio allocation therefore cannot be assessed from the fund label alone.

The five strategy models below cover the principal ways hedge funds attempt to generate alpha: directional security selection, macro positioning, event pricing, relative-value arbitrage, and diversified platform allocation.

Long/short equity: balancing market exposure and stock-specific alpha

Long/short equity remains the most common hedge fund strategy because it separates two decisions that a conventional equity portfolio often combines: which securities to own and how much exposure to maintain to the broader market.

A long/short manager buys securities considered undervalued and sells short securities considered overvalued. The portfolio may hold 70% gross long exposure and 30% gross short exposure. Its net exposure is therefore 40%, while its gross exposure is 100%. That distinction is fundamental:

• Gross exposure measures the total absolute value of long and short positions.
• Net exposure measures the portfolio’s directional bias after offsetting shorts against longs.
• Beta exposure measures sensitivity to market movements and may differ from the simple net percentage.
• Leverage can increase both gross exposure and the effect of small price movements on fund capital.

A manager with 70% long exposure and 30% short exposure is not simply running a 40% equity portfolio. The fund remains exposed to pairwise dispersion, short squeezes, crowded positioning, borrow costs, financing terms, and the possibility that both sides of the book move against the thesis.

The return objective can be decomposed into several sources:

1. Long alpha: the long book outperforms its relevant benchmark.

2. Short alpha: the short book declines or underperforms the market.

3. Net beta: the residual directional exposure benefits from market appreciation.

4. Spread capture: the long and short positions respond differently to a common sector or factor move.

5. Financing and implementation costs: borrow fees, transaction costs, margin requirements, and trading slippage reduce gross performance.

The practical underwriting question is not whether the manager owns attractive stocks. It is whether the short book is a genuine source of alpha or merely a financing and hedge mechanism. A portfolio can appear diversified by holding dozens of positions while retaining significant factor concentration in growth, momentum, quality, regional banks, semiconductor exposure, or other common risk premia.

Where the model fails

Long/short equity strategies experience IRR compression when the market rewards broad beta and penalizes short selling. In a strong, narrow equity rally, the long book may rise while the short book rises faster, particularly when the manager is positioned against crowded momentum names. The fund can then produce negative absolute returns despite correct relative-value analysis on individual securities.

Short positions also carry asymmetric risk. A long position can lose no more than its invested capital, while a short position has theoretically unlimited loss potential. In practice, risk controls impose stop-losses, position limits, borrow constraints, and gross-exposure reductions. Those controls can protect capital, but forced covering during a disorderly market can crystallize losses at the least favorable point in the cycle.

A long/short label does not establish low risk. The relevant variables are net beta, gross exposure, factor concentration, borrow availability, and the liquidity of the short book.

For portfolio construction, a long/short equity fund should be evaluated against the actual source of return. A low-net fund driven by stock selection has a different role from a 70% net fund that behaves like a leveraged equity allocation with a short overlay.

Global macro: trading the transmission of policy and growth

Global macro hedge funds form positions around changes in interest rates, currencies, commodities, inflation, fiscal policy, and economic growth. The trade may be implemented through government bonds, interest-rate swaps, futures, foreign exchange forwards, commodity contracts, or equity-index derivatives.

The defining feature is not the instrument. It is the manager’s attempt to translate a macroeconomic view into a portfolio of liquid positions with defined risk. A view that central banks will keep policy rates higher for longer can produce a short-duration trade, a stronger-currency position, or a curve steepener. The same view can be expressed through several instruments, each carrying a different combination of duration, convexity, liquidity, and basis risk.

Bridgewater Associates is a prominent example of the scale associated with the strategy; it was reported to manage $126.4 billion in assets in late 2022. Brevan Howard is another established name in macro investing. These examples should not be interpreted as evidence that all macro funds use the same process. Macro portfolios differ materially in time horizon, discretionary versus systematic execution, instrument selection, and tolerance for leverage.

The capital stack of a macro position

A macro trade should be analyzed through four layers:

This structure explains why macro funds can generate returns in both rising and falling markets without implying a reliable hedge in every quarter. Directional exposure may be limited, but the portfolio can still carry substantial duration, currency, or volatility risk. A trade that is economically correct can lose money if the position is sized incorrectly, the market moves before the catalyst, or the chosen derivative exhibits unfavorable convexity.

Macro funds also face a timing problem. Interest-rate and currency positions are often marked continuously, while the economic thesis may require months to develop. If the fund is financed with short-term margin and the position incurs interim losses, the manager may be forced to reduce exposure before the thesis is realized. The difference between investment insight and realized return is therefore determined partly by financing architecture.

For institutional allocators, the key diligence points include the concentration of risk by asset class, the use of leverage, liquidity under stressed conditions, collateral arrangements, and the relationship between historical returns and major rate or currency regimes. A fund that performed well during a particular inflation or volatility cycle may not retain the same profile after the dominant macro factor changes.

Event-driven strategies: pricing corporate actions and restructuring outcomes

Event-driven hedge funds trade around corporate actions that can alter the value or timing of securities. Mergers and acquisitions, bankruptcies, restructurings, spin-offs, recapitalizations, and litigation-related events can create price dislocations because the market must estimate both an outcome and a probability.

Merger arbitrage is the most accessible example. After an acquisition is announced, the target company’s shares often trade below the proposed offer price. The discount reflects the probability that the transaction will fail, be delayed, require modified terms, or face financing, regulatory, or shareholder obstacles. An arbitrageur may buy the target and, in a stock-for-stock transaction, short the acquirer’s shares according to the exchange ratio.

The spread is not free yield. It is compensation for deal risk and time risk.

The expected return depends on several variables:

• The size of the spread between the market price and the consideration offered.
• The probability of deal completion.
• The time required to close.
• The financing cost and borrow cost.
• The probability and severity of a break.
• The legal, regulatory, and shareholder approval process.
• The correlation between the target and acquirer when stock consideration is used.

Trades associated with Microsoft’s acquisition of Activision Blizzard and Cisco’s acquisition of Splunk illustrate the type of announced transactions examined by event-driven managers. The trade construction, however, depends on the transaction documents and market prices at the relevant time; a deal name alone does not define the opportunity.

Deal spread is a probability-weighted return

Assume a target trades at $95 after an offer of $100 per share. The gross spread is $5, or approximately 5.3% relative to the purchase price. If the deal closes, the investor receives the consideration, before fees and financing. If the deal breaks, the target may fall materially below $95. The correct analysis is not “5.3% available.” It is the expected value of completion, break loss, time to close, and carrying costs.

A simplified framework is:

1. Estimate the value received if the transaction closes.

2. Estimate the target’s value if the transaction breaks.

3. Assign probabilities to each outcome.

4. Adjust for time, financing, borrow, and transaction costs.

5. Test the result against a delayed-close and adverse-break scenario.

This is why merger arbitrage portfolios are often diversified across transactions. A single broken deal can erase the gains from several successful positions. Diversification reduces idiosyncratic event risk but does not eliminate market-wide risks such as regulatory hostility, funding stress, or a broad withdrawal of acquisition financing.

Bankruptcy and restructuring strategies introduce a different layer of complexity. The manager analyzes the capital structure, collateral, priority claims, recovery values, and the incentives of each creditor class. Senior secured debt, unsecured bonds, preferred securities, and equity can respond differently to the same restructuring proposal. The relevant return is determined by recovery value and legal priority rather than by the issuer’s historical earnings alone.

In event-driven investing, the spread is the visible output. The underwriting work is the probability distribution behind it.

Relative-value arbitrage: isolating a mispricing without removing risk

Relative-value strategies seek discrepancies between related securities or instruments. The manager is not necessarily predicting that the entire market will rise or fall. The objective is to capture convergence, carry, or statistical deviation between positions with an identifiable relationship.

Convertible arbitrage provides a standard example. The manager buys a convertible bond and shorts the underlying equity, seeking to isolate the bond’s embedded optionality, credit exposure, and pricing relationship to the stock. A Tesla convertible bond trade in 2014 is an example of the type of security relationship used in this strategy.

The structure is not a mechanical hedge. The convertible contains credit risk, interest-rate risk, equity volatility exposure, call and put features, and liquidity risk. The short equity position introduces borrow costs and can become difficult to maintain if the stock rallies sharply or borrow availability contracts. The manager must hedge more than the stock delta when the position’s gamma, vega, credit spread, or interest-rate sensitivity changes.

Statistical arbitrage applies quantitative models to identify historical relationships between securities. A pairs trade involving Coca-Cola and Pepsi, for example, may take a long position in one stock and a short position in the other when the observed price relationship deviates from a model-defined range.

The weakness is model dependency. A spread can widen because of temporary dislocation, or because the economic relationship has changed. A model trained on stable historical behavior may not account for a permanent change in earnings quality, regulation, supply chains, capital allocation, or investor composition.

Relative value through the risk committee lens

A relative-value book requires more than a correlation matrix. Underwriting should address:

• Economic linkage: why should the securities converge?
• Hedge ratio: whether the position is neutral to beta, duration, credit spread, or another intended factor.
• Liquidity mismatch: whether one leg can be exited without materially moving the market.
• Funding duration: whether the trade can survive a prolonged period of divergence.
• Crowding: whether multiple funds may be positioned in the same convergence trade.
• Model instability: whether the relationship holds across different regimes.
• Tail behavior: what happens when volatility, correlations, or financing spreads move outside historical ranges?

Leverage is common because the expected spread on an individual trade may be small. That leverage increases the importance of financing terms and collateral calls. A strategy that produces stable returns in ordinary markets can incur rapid losses when spreads widen simultaneously across many positions.

The principal distinction between a robust relative-value strategy and a fragile one is the treatment of non-convergence. A manager must have a defined exit rule, sufficient liquidity, and capital reserves to maintain positions during temporary dislocations. Otherwise, the fund is not monetizing a mispricing; it is financing a forecast.

The multi-strategy platform: allocating capital across independent books

Multi-strategy hedge funds allocate capital across multiple teams operating under a common platform. Citadel, Millennium Management, and Balyasny Asset Management are examples of firms associated with this model. The platform can combine equity long/short, macro, quantitative trading, fixed income relative value, event-driven, and other specialist books.

The central advantage is not simply diversification by asset class. It is diversification by decision process, time horizon, and return driver. A macro team may express a rate view over weeks or months, while an equity market-neutral team trades shorter-term factor dislocations. An event-driven team may carry deal exposure that is largely independent of a statistical-arbitrage book.

Capital allocation is therefore the operating core. The platform determines:

• How much capital each team receives.
• What gross and net exposure limits apply.
• How losses affect future risk limits.
• Which positions may be held through stressed markets.
• How prime brokerage and financing are shared.
• How correlations are monitored across apparently separate books.
• How performance fees and internal compensation influence risk-taking.

Citadel generated a reported $16 billion in earnings in 2022, a result that illustrates the potential earnings scale of a successful multi-strategy and quantitative platform. It does not establish a forward return expectation. Platform performance depends on the quality of its teams, the efficiency of its technology and execution, the stability of financing, and the ability to withdraw risk before independent books become correlated.

Why platform diversification can be overstated

A multi-strategy fund may list numerous teams while retaining common exposures to liquidity, volatility, funding, or crowded trades. A market shock can cause different strategies to reduce positions simultaneously. This creates correlation precisely when diversification is most valuable.

The platform also introduces governance risk. Risk limits can reduce blow-up probability, but they may also force rapid de-risking after a temporary loss. The resulting turnover can produce realized losses, market impact, and IRR compression. Conversely, loose limits can allow a supposedly independent team to accumulate hidden factor exposure that overwhelms the diversification benefit.

Investors should distinguish between:

1. Strategy diversification: multiple investment methods.

2. Risk diversification: low sensitivity to the same underlying factors.

3. Financing diversification: access to more than one source of liquidity and collateral.

4. Operational diversification: sufficient systems, personnel, and controls to manage separate books.

Only the second and third categories directly address portfolio drawdown risk. A fund can be diversified by strategy name but concentrated in the same financing environment.

How the five models differ in a portfolio

The following comparison is more useful than ranking strategies by historical return. Each model has a different role, risk transmission mechanism, and dependence on financing.

This table also explains why liquid alternatives are not interchangeable with traditional hedge funds. Liquid alternative funds generally provide more frequent liquidity and operate under additional regulatory or portfolio constraints. Those features can make access easier, but they can also restrict leverage, shorting flexibility, position concentration, or the ability to hold less liquid instruments. The result may be a different return distribution and a different level of implementation drag.

Fees, leverage, and the net return delivered to investors

The traditional hedge fund fee reference is “2 and 20”: a 2% annual management fee on assets under management and a 20% performance fee on profits, usually subject to negotiated terms and, in some structures, a hurdle or high-water mark. The model is not universal. Institutional investors may negotiate lower management fees, performance fees, capacity terms, or enhanced reporting rights.

Fees matter because they increase the hurdle required to justify complexity. A strategy producing 6% gross returns with meaningful leverage and operational demands may deliver a substantially lower net return after management fees, incentive compensation, financing, and trading costs. The investor must assess the return relative to the liquidity offered and the risks retained.

Leverage is similarly ambiguous. It can increase capital efficiency when positions are liquid and hedges are reliable. It can also magnify mark-to-market losses, collateral requirements, and forced selling. A fund with moderate net exposure may still carry high gross exposure and significant financing risk. Public disclosures often do not provide the leverage ratios used by individual multi-strategy platforms, so the analysis should focus on observable liquidity, redemption terms, margin arrangements, and historical behavior during volatility.

The relevant performance metric is not headline CAGR alone. Review should include:

• Gross versus net returns.
• Return contribution by strategy and factor.
• Maximum drawdown and recovery period.
• Liquidity terms relative to the liquidity of underlying positions.
• Use of derivatives and collateral.
• Exposure during rate shocks, equity selloffs, and volatility spikes.
• Fee-adjusted returns and performance persistence.
• Correlation with the existing portfolio.

A 15–25% CAGR may indicate a strong operating model, but it does not identify the risk taken to generate that result. The same return can arise from unlevered security selection, concentrated event exposure, or a highly financed convergence book. Those are not equivalent assets.

The institutional allocation decision

Family offices and institutional portfolios typically use hedge funds for one or more of four purposes: return enhancement, equity-risk reduction, diversification, and access to specialist trading capabilities. Each purpose requires a different evaluation.

If the objective is equity-risk reduction, a long/short fund with persistent 60% net exposure may not provide the intended hedge. If the objective is crisis diversification, a macro fund that depends on stable rates-market liquidity may fail at the same time as other liquid portfolios. If the objective is return enhancement, a multi-strategy platform may offer a broad opportunity set but impose fee and financing costs that reduce net yield.

The allocation should therefore begin with the portfolio role, not the manager’s brand or reported return. A suitable process maps each fund’s exposures into the existing capital structure of the portfolio:

1. Identify the strategy’s primary return driver.

2. Separate gross, net, and factor exposure.

3. Analyze financing and collateral requirements.

4. Test liquidity under redemption and market-stress scenarios.

5. Review drawdown behavior across different regimes.

6. Measure fee-adjusted returns against the specific portfolio function.

7. Assess whether the fund adds a return source or duplicates existing exposure.

The central question is whether the fund improves the portfolio after costs and under stress. A strategy that produces uncorrelated returns in normal markets but becomes correlated through leverage, liquidity, or crowding may offer less protection than its historical statistics imply.

Final assessment

The strongest hedge fund examples are operating models, not promotional case studies. Long/short equity isolates stock selection from market beta. Global macro converts changes in rates, currencies, and commodities into financed positions. Event-driven investing prices the probability of a corporate outcome. Relative value seeks convergence while carrying model and funding risk. Multi-strategy platforms allocate capital across specialist teams but must control hidden correlation and forced deleveraging.

Each model can generate alpha. None removes the need for underwriting.

The decisive variables remain the same across the category: the source of return, the leverage supporting it, the liquidity available when the thesis fails, and the loss that can be sustained before the portfolio is forced to exit. Exit multiples are not the relevant issue in liquid hedge funds, but the principle is equivalent: headline performance has limited value unless the capital structure supporting it can survive the next regime change.