Trustorment applies predictive modelling to decades of market data, giving location-independent professionals a disciplined way to evaluate strategies before committing capital.
Trustorment's model ingests historical pricing, volatility, and macroeconomic indicators, then tests candidate strategies against a range of past market conditions, including periods of contraction. The objective is not to predict a single outcome, but to quantify how a strategy has behaved when conditions changed.
Each output is accompanied by its backtested history, so the reasoning behind a recommendation remains visible rather than treated as a closed system.
Illustrative: reviewing a backtested strategy report prior to allocation.
Each module is designed around the constraints of remote work: limited time for manual review, reliance on digital tools, and the need for recommendations that scale with changing circumstances.
Assesses downside exposure before upside potential. The module cross-references volatility, correlation between holdings, and historical drawdown periods, surfacing the conditions under which a strategy has previously underperformed, not only when it has succeeded.
Drawdown-aware modellingContinuously ingests market and portfolio data, recalculating relevant metrics as conditions shift. Analysis is refreshed on an ongoing basis rather than produced as a static report, so a decision made this week reflects current, not historical, context.
Continuous data ingestionRecommendations adjust to portfolio size and risk tolerance rather than applying a single model uniformly. This allows the same methodology to remain relevant whether capital is modest and growing or already diversified across several instruments.
Adjusts to portfolio scaleRather than presenting a single accuracy figure, Trustorment documents the process used to arrive at each backtested result, so the method can be assessed on its own terms.
Pricing, volatility, and macroeconomic data are gathered from ASX-listed equities, global indices, and relevant economic indicators across multiple market cycles.
Candidate strategies are run against historical conditions, including periods of contraction, to observe behaviour under stress rather than only favourable conditions.
Results are compared against relevant passive benchmarks, such as broad market indices, to establish whether the strategy added measurable value over time.
Findings, including periods of underperformance, are recorded alongside the strategy so the full historical range remains part of the record.
The dataset underpinning each model spans multiple economic conditions rather than a single favourable period. This is deliberate: a strategy that has only been tested during growth is difficult to assess with confidence.
Backtested performance is reported alongside maximum historical drawdown and benchmark comparison, rather than as an isolated percentage. This keeps the range of past outcomes, including weaker periods, visible to anyone reviewing a strategy.
The process is designed to fit around existing tools and limited review time, rather than requiring a dedicated research setup.
Connect existing brokerage or market data feeds. Trustorment ingests the relevant data on an ongoing basis, without requiring manual uploads or spreadsheet maintenance.
The predictive model processes current conditions against backtested strategies, surfacing recommendations with their associated risk profile and historical context.
Review the recommendation and its supporting analysis, then act through your existing brokerage or investment platform. Trustorment supports the decision; execution remains with you.
Common questions from remote-first professionals evaluating the platform before committing capital.
Data connected to Trustorment is encrypted in transit and at rest. Access to account-level analysis is restricted to the account holder, and no portfolio data is shared with third parties for marketing purposes.
Underlying datasets are updated continuously as new market data becomes available, and the model is recalibrated on a monthly cycle to reflect recent conditions without overreacting to short-term noise.
Trustorment is designed to connect with commonly used brokerage and market data feeds. Where a direct connection is not yet supported, analysis can be reviewed independently and applied manually through your existing platform.
Every backtested strategy is presented with its historical drawdown and benchmark comparison, so you can assess the reasoning at your own pace, with no obligation to proceed.