Systematic
relative return.

Systematic relative return strategies use rules-based, quantitative models rather than discretionary human judgment to outperform a specific benchmark or index rather than targeting positive returns in isolation, as absolute return strategies do. Algorithms overweight or underweight assets and instruments versus a target benchmark – such as Bitcoin – aiming to generate alpha while retaining meaningful exposure to the market’s overall direction.

Performance is measured relative to the target benchmark: beating it in a downturn still counts as performance, even with a negative return. This means investors can experience a loss in absolute terms even while the strategy outperforms its benchmark. This approach suits investors seeking disciplined, model-driven outperformance within familiar market exposure, rather than independence from it, and – as with any model-driven strategy – results depend on the underlying model’s design and robustness.

Benefits

FAQs

Investments

Benefits.

Familiar exposure, actively managed.

Unlike absolute return strategies, relative return strategies retain meaningful exposure to a benchmark’s overall direction. Investors gain disciplined, model-driven outperformance within markets they already understand, rather than a fully independent, direction-agnostic approach.

Benchmarked to a known standard.

Measuring performance against a specific benchmark, like Bitcoin, gives investors a clear and familiar reference point for evaluating results. Outperformance is defined relative to that benchmark, not an abstract or zero-based target.

Removes discretionary bias.

Rules-based, quantitative models execute according to predefined logic, not human sentiment or reaction. This enforces consistency across market conditions, though performance still depends on the underlying model’s design, calibration, and robustness.

FAQs

Who are relative return strategies typically designed for?

Professional investors who want disciplined, model-driven outperformance while retaining exposure to a specific market or benchmark, rather than seeking independence from market direction. They tend to suit investors comfortable with benchmark-relative performance, including the possibility of a net loss during a broader market downturn.

What is the typical fee structure of a relative return strategy?

Commonly charge a management fee (typically a percentage of assets under management) alongside a performance fee (typically a percentage of profits generated), often subject to a high-water mark, and sometimes benchmarked to outperformance rather than net profit. Exact fee terms vary by strategy and should always be confirmed prior to making an investment decision.

What is the typical lock-up period of a relative return strategy?

Lock-up periods vary widely depending on the strategy’s liquidity and underlying instruments, ranging from no lock-up with regular redemption windows, to fixed lock-ups of several months or longer for less liquid strategies. Investors should review the specific redemption terms, notice periods, and any gating provisions prior to making an investment decision.

What are the technical risks of an on-chain relative return strategy?

On-chain execution introduces risks distinct from traditional infrastructure including but not limited to: smart contract vulnerabilities or bugs, oracle failures or manipulation, blockchain network congestion or downtime, and risks specific to blockchain protocols a strategy interacts with (such as liquidity pool exploits or protocol-level failures).

What are the non-technical risks of an on-chain relative return strategy?

Non-technical risks include but are not limited to: regulatory uncertainty as digital asset rules continue to evolve across jurisdictions, counterparty risk where a strategy interacts with third-party protocols or platforms, valuation and pricing risk in less liquid markets, and operational risks related to fund managers’ governance, controls, and decision-making processes.

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