Systematic strategies, explained and backtested
Plain-language explanations of the classic systematic strategies, each with its rules, its failure modes, a hypothetical backtest on ENSEMBLE, and the prompt that builds it.
A systematic strategy states what to hold, how much, and when to change it. These guides help you turn a research question into an investment allocation model. An allocation is how investments are divided.
Choose a question to investigate
- 60/40 portfolio: how do fixed stock-and-bond weights and a rebalancing schedule behave?
- Risk parity and inverse volatility: what changes when weights depend on estimated risk?
- 200-day moving average: how does a stated trend signal change the holdings?
- Dual momentum: what happens when selection depends on relative returns and an absolute threshold?
Each guide states an illustrative rule, its important choices and the results to inspect. Where a public model card is available, it links to a changing model record. Read its current inputs, window and data date. Public results do not expose their owner's private source code.
Read the evidence in context
A strategy label does not establish the exact implementation. Check the selected assets, signal and fill timing, missing data, backfills and costs. Compare models over identical dates. A longer history can include synthetic extensions that must be distinguished from observations.
Read the allocation and drawdown histories alongside headline metrics. A favorable backtest is one historical result, not a prediction or a ranking of investment merit. See metrics explained for the actual reporting conventions and common mistakes for pitfalls.
Build and maintain your own model
Start with the portfolio walkthrough. Research the assets, create a model, inspect its saved code and result, then test one change while keeping live defaults separate. Review the result before adoption. Scheduled refreshes depend on readiness, data and account limits; verify success and the latest data date.
The web app, a compatible connected agent, REST API and CLI access the same persistent platform. Your saved code, inputs and runs support further investigation, subject to access permissions and data-reproducibility limits.
ENSEMBLE is research software. Backtests are hypothetical and past performance does not guarantee future results.
Guides in this section
- 01Dual momentum: the rules, the evidence, and a backtestDefine relative and absolute momentum separately, inspect a public model, and compare a parameter change. The example explains the research workflow without promising a historical or future result.
- 02Risk parity: how it works, how to size it, and a backtestUnderstand risk contributions and the simpler inverse-volatility weighting rule. Inspect a public model, test one assumption, and distinguish a model specification from a performance claim.
- 03The 60/40 portfolio: rules, variants, and a backtestDefine a stock-and-bond allocation, inspect a public 60/40 model, and test rebalancing or asset changes over matched dates. Learn what the model shows and what it leaves out.
- 04The 200-day moving average strategy: rules, evidence, and a backtestDefine a moving-average allocation rule, specify signal and execution timing, and inspect its tradeoffs in a model run. An illustrative prompt helps you build and compare your own version.
Frequently asked questions
- What is a systematic investment strategy?
- A set of explicit rules for choosing holdings, weights and when to change them. A backtest evaluates an implementation over historical data; a rule alone does not prove a result.
- Are these investment recommendations?
- No. These pages explain specifications and research workflows. ENSEMBLE is research software, and hypothetical results do not establish future performance.
- Can I test a variation?
- Yes. Use an illustrative prompt to build your own model, inspect its implementation, then compare supported inputs or a reviewed revision. Generated implementations and available histories can differ.
Other sections
- BacktestingPortfolio backtesting software for your own investment models
Build and backtest your portfolio in ENSEMBLE. Inspect the code, historical results, and allocations. Start with $100 in metered credit, valid for 7 days; no card required.
- AI agentsAI agents for investment research
Research assets and build, test, and maintain allocation models with a compatible AI client. Inspect saved code, inputs, runs, and current allocations.
- CompareBacktesting tools compared
Factual comparisons of portfolio backtesting tools: what each one does well, where it stops, and when ENSEMBLE is or is not the better fit.
- For advisorsModel portfolios for advisors
Build, backtest, document, and keep model portfolios current from plain language, with Business features for white-label fact sheets and supported broker-format allocation files.
Backtests are illustrative. Past performance does not guarantee future results. ENSEMBLE is a software platform, not an investment adviser.