Allocation Engine
Building sophisticated allocation tools requires more than historical market data. Our Allocation Engine covers comprehensive simulated future paths that feed directly into your asset allocation decision-making systems.
10-year expected return
The simulations are aligned with our expected-return framework, giving teams a coherent forward-looking foundation on which to build their own portfolio models, applications and decision systems.
>>> paths = client.simulate(
assets="all",
horizon="10y", n=10_000)# 10,000 paths × 120 months × 200+ assets
| path | month | equity_us | gov_uk | +200 |
|---|---|---|---|---|
| 0001 | 1 | +0.012 | −0.003 | … |
| 0001 | 2 | −0.004 | +0.001 | … |
| 0002 | 1 | +0.021 | −0.006 | … |
Our API gives investment teams direct access to millions of simulated variables across markets, macro variables and investment horizons, all consistent with each other and the expected returns and risks we estimate today.
Give agents better inputs than historical data. Forward-looking simulated paths provide a robust foundation for agents to analyse portfolios, compare decisions and build increasingly sophisticated investment workflows.
Technology
We provide the simulated future paths behind our allocation technology directly to investment teams. Each path represents a coherent state of the world across asset returns, interest rates and macroeconomic variables, allowing teams to build their own research, portfolio construction and decision tools on a robust forward-looking foundation.
Stochastic simulations are integrated with Allocation Strategy’s expected returns and carefully calibrated to capture current market conditions and forward-looking cross-asset relationships and risk dynamics across horizons. Public and private assets are modelled together, so different parts of the portfolio can be analysed within the same possible future rather than assembled from separate models.
Use the engine as infrastructure for stochastic asset allocation, optimisers, glide paths, liquidity analysis, proprietary research tools or AI agents. We maintain the models and the broad global opportunity set; your team retains control of the investment logic built on top.
Portfolio
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Research
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FAQs
The Allocation Engine API gives investment teams programmatic access to Allocation Strategy's forward-looking modelling infrastructure. It provides expected returns, simulated paths, risk and related analytics that can be embedded directly into proprietary research, portfolio tools and investment systems. Teams use the API to power internal asset allocation analytics. It is designed as underlying investment infrastructure rather than a prescribed end-user workflow.
The API provides quarterly simulated paths for 100+ assets extending up to 30 years ahead, covering returns across a broad asset universe alongside macroeconomic variables and interest rates. The paths are updated monthly.
The engine starts from current market pricing, valuations and expectations rather than simply resampling historical returns. Simulated distributions are calibrated to reflect both where markets are today and a realistic range of outcomes around those expectations.
Risk is dynamic rather than fixed at a single historical volatility or correlation assumption. Volatility and cross-asset relationships can evolve through time and across market environments, producing more realistic distributions of possible outcomes.
No. The objective is not simply to generate large numbers of random paths. Simulations are calibrated so that expected returns, risk, macro conditions and cross-asset relationships remain economically coherent within each future state.
Insights