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Historical simulation

Strategy Lab

A structured portfolio research workflow for backtesting, optimization, comparison, regime analysis, and interpretation. Historical simulation only.

Research UniverseLookbackBenchmark

Rebalance

Data Source: Polygon/Massive • Delayed

Research Setup

How would a Buy & Hold strategy using Custom Weights have performed over the selected window versus SPY?

Assets

Included assets

SPY, QQQ

Excluded assets

None

Window

2025-06-05 to 2026-06-05

Benchmark

SPY

Rebalance

Monthly

Allocation

Custom Weights

Strategy

Buy & Hold

Data coverage

Estimated after run

Estimated runtime

Usually under 10 seconds

Universe

Manual Universe

Universe / Portfolio Builder

Choose saved holdings or build a manual basket. Disabled universe presets are scaffolded for later.

Saved portfolio

Use portfolio weights, then edit the generated weight table. Eligible equity, crypto, and futures are included; unsupported derivatives are listed as excluded after data checks.

Symbol	Asset Type	Weight	Data Status	Status	Notes
			Ready for historical data check	Included	Ready for historical data check
			Ready for historical data check	Included	Ready for historical data check

Current total: 100.0%

Backtest Assumptions

Define the historical window, cost model, and benchmark.

Start Date

End Date

LookbackRebalanceBenchmark

Initial Capital

Transaction Cost Bps

Slippage Bps

Risk-Free Rate

Actual usable historical window is shown after data fetch in the Results Workspace.

Strategy Rule

Choose a historical signal rule and tune its parameters.

Strategy Rule

Maintains the selected allocation through the test period and rebalances according to the selected schedule.

Allocation & Optimization

Separate the allocation method from the optimization objective and constraints.

Allocation Method

Objective

Use edited weights

Portfolio Constraints

Minimum Allocation per Asset

Maximum Allocation per Asset

Maximum Turnover

Maximum Leverage

Volatility Target

Sector Cap

Asset Class Cap

Long OnlyAllow Cash

Select Optimized to generate an allocation preview.

Run a simulation to generate results.

Athena will calculate performance, risk metrics, drawdowns, rolling statistics, regime performance, Monte Carlo scenarios, and a research memo.

Performance metricsEquity curveDrawdown profileRolling Sharpe and volatilityRegime performanceMonte Carlo outcomesAthena Research Memo

Strategy Comparison

Compare 2-6 historical configurations. Backtest comparisons are historical simulations, not recommendations.

Build a comparison to rank strategies by Sharpe, drawdown, return, and cost drag.

Regime Performance

Performance grouped by Athena's simplified regime classification.

Run a simulation to evaluate performance across market regimes.

Future Outcome Scenarios

Monte Carlo simulation estimates potential outcome ranges from historical return assumptions.

Run a simulation to estimate a range of possible outcomes using historical return behavior.

Athena's Research Summary

Run a simulation to generate Athena's research summary.

Athena will summarize what was tested, main performance driver, main risk driver, drawdown behavior, regime dependency, optimization notes, data limitations, and suggested next analysis after a simulation.

Saved Experiments

Reuse, clone, delete, or compare prior research setups.

No saved experiments yet. Configure a simulation and click Save Experiment to reuse it later.

All Strategy Lab outputs are historical simulations. They are not predictions, recommendations, or guarantees of future performance.