Research Note / Portfolio Construction
Systematic Trading Strategies: An Allocator's Map
The main families of systematic strategy, what each tries to earn, when each tends to struggle, and how an allocator screens and combines them.
- Audience
- Allocators, family offices, diligence committees
- Scope
- Six strategy families, overlap and screening
Systematic strategies fall into a few families, trend following, carry, mean reversion and statistical arbitrage, systematic macro, execution-sensitive short-horizon trading and machine-learning-driven models, and each earns its return from a different source and struggles in different conditions. An allocator's job is to know which family a program belongs to, what role it plays in the existing book, and whether two programs are really different.
This note is a map for choosing and combining, not a ranking and not a recommendation. It states no returns and makes no performance claims. It is educational, written for professional investors, and is not an offer or solicitation.
What does an allocator need from a systematic strategy?
An allocator rarely wants “the best strategy”. The questions are narrower:
- What return source does this program rely on, in plain words?
- How does it behave when markets are calm, trending, choppy or stressed?
- Does it overlap with what the book already holds?
- Can it be implemented at the size and with the liquidity the mandate needs?
- Can the record be verified from sources the manager does not control? See how to verify a quant track record.
The families below are a way to answer the first three.
Six families at a glance
The descriptions are general and use “tends to” because outcomes differ by manager, market and period.
| Family | What it tries to earn | Conditions that tend to favor it | Conditions that tend to hurt it | Role in a book |
|---|---|---|---|---|
| Trend following | Persistent price moves across many markets | Sustained directional moves | Range-bound, reversing markets | Return source that does not depend on markets rising |
| Carry | The payoff for holding an asset or position that pays a premium | Stable markets where the premium is collected | Sudden unwinds when many hold the same positions | Steady-looking income with tail exposure to be understood |
| Mean reversion and statistical arbitrage | Small, repeated pricing gaps that tend to close | Orderly markets with stable relationships | Regime breaks where relationships stop holding | Market-neutral style return source |
| Systematic macro | Rules-based views on rates, currencies and commodities | Clear macro trends and dislocations | Rapid policy-driven reversals | Diversifier across asset classes |
| Short-horizon, execution-sensitive | Very short-lived inefficiencies captured at speed | Liquid markets with stable microstructure | Rising costs, changing market structure, limited capacity | Small-capacity return source; depends heavily on implementation |
| Machine-learning-driven | Patterns found by models trained on data | Stable relationships between the data and returns | Shifts the training data never contained; overfitting | Varies; the hardest to judge from outside, so evidence matters most |
A single manager can combine families. A program label such as “multi-strategy” says little until the sleeves and their weights are known.
How should an allocator choose and combine strategies?
Look for overlap, not just labels
Two programs from different families can still share a common driver, for example the same markets, the same signal horizon or the same crowded positions. Ask each manager what the program is exposed to when markets fall sharply, and compare the answers rather than the names. Correlation between programs should be measured over a stated window from data you can verify, and read as a description of the past, not a promise.
Match the strategy to the size and the mandate
Capacity matters for every family and most for short-horizon trading. A program that works at a small size can fail at a larger one. Ask what size the strategy can reach before its own trading erodes the return, and how that capacity is shared among investors. For the trading-cost side, see microstructure feasibility.
Separate the return source from the delivery format
How you hold a strategy changes its transparency and control, not its return source. A separately managed account puts the account in your name at your own broker, with the manager holding trading authority only. A pooled fund holds the assets in a vehicle the manager controls. The investor guide compares the structures, and the Swiss actively managed certificate note covers a third route. None of them makes a program safe or profitable.
A screening sequence that works across families
- 01Eligibility and fit. Does the mandate allow this family and this structure?
- 02Evidence. Is the record traceable to independent sources? Backtests are simulations, not records.
- 03Method. How were the rules chosen, and how many variants were tried? See backtest overfitting and placebo tests and combinatorial purged cross-validation.
- 04Implementation. Execution, risk limits, custody and counterparty.
- 05Live observation. A pilot with real capital before the allocation scales.
- 06Fit with the book. What the program adds that the book does not already hold.
Each family has its own failure modes and its own question set; those are set out in quant due diligence questions by strategy type.
Common mistakes
- Choosing the family that did best most recently. Conditions rotate, and recent results describe the past.
- Counting two programs as diversified when they share a signal horizon or crowded positions.
- Accepting a label such as “market neutral” without asking what the program is exposed to under stress.
- Skipping implementation questions because the backtest looks clean.
- Treating a pilot as proof. It confirms execution over a finite window and cannot cover every regime.
How does this connect to the Apex Marketplace?
Qlumina, a BVI FSC approved investment manager, admits programs to the Apex Marketplace only after a quantitative review, an operational review and a live pilot allocation, and delivers them as separately managed accounts. The review process is set out on the quant fund diligence page. You can browse the Apex Marketplace or the program catalog; program statistics unlock after investor verification. Related reading: how allocators find and connect with systematic managers and all research notes.
Frequently asked questions
What are the main types of systematic trading strategy?
The main families are trend following, carry, mean reversion and statistical arbitrage, systematic macro, short-horizon execution-sensitive trading and machine-learning-driven models. Each earns its return from a different source and struggles in different conditions.
How should an allocator combine systematic strategies?
Look for what the programs are exposed to rather than their labels, check overlap in markets, signal horizon and crowded positions, and read any measured correlation as a description of the past drawn from verifiable data.
Is trend following the same as systematic macro?
No. Trend following uses price persistence across many markets. Systematic macro uses rules-based views on rates, currencies and commodities that may draw on economic data. Some managers combine both.
Why does capacity matter?
A strategy's own trading costs and market impact can erode its return as assets grow. A program that works at a small size can fail at a larger one, so a stated capacity should come with the assumptions behind it.
Does a separately managed account change a strategy's risk?
It changes who holds the assets and what you can see, not the return source or the risk of the strategy. Performance, risk and suitability still depend on the mandate and the manager.
Risk and eligibility
Investing involves substantial risk of loss. The value of investments and the income derived from them can fall as well as rise, and investors may not recover the amount originally invested. Past performance is no guarantee of future returns. This note is for professional investors only and is not an offer or solicitation of any kind. Qlumina is a BVI FSC approved investment manager. See the risk disclosure.
Apex Marketplace
Programs Admitted on Evidence
Professional investors can browse the live programs on the Apex Marketplace. Program statistics unlock after investor verification.
Research notes are published for professional readers. Not an offer or solicitation. Risk disclosure
