Predictive modelling for private capital

Institutional-grade data analysis for personal capital

Draymint Group applies predictive modelling and automated optimisation to your portfolio inputs, producing tailored recommendations without requiring you to write code, build spreadsheets, or interpret raw market feeds yourself.

Live Performance Logs
Decisions logged (30d)1,042
Models currently active06
Average log review time< 2 min
Public ledger statusOpen

Historical analysis accuracy, published as a public ledger

Rather than ask you to take our word for it, every model decision is time-stamped and written to a log that community members can review. The excerpt below illustrates the format; it is not a projection of future results.

Log Reference Date Decision Type Rationale Summary Status
DG-10482 04 Mar Rebalance Volatility threshold exceeded on sector weighting Closed
DG-10483 05 Mar Hold No deviation from projected confidence band Closed
DG-10484 06 Mar Defensive Shift Correlation spike detected across two linked assets Monitoring
DG-10485 07 Mar Reallocation Low-volatility yield opportunity identified Closed

Real-time decision logs

Each model action is recorded with a timestamp, the data trigger that caused it, and the resulting adjustment, so the reasoning is traceable after the fact.

Community-verified review

Subscribers can cross-check logged decisions against the published rationale, flagging discrepancies for the research team to address.

Public ledger access

Historical logs remain accessible after the fact rather than being summarised or edited retrospectively.

From raw data to a recommendation you can act on

The process is split into three stages. You are only required to monitor the outcome at the end; the ingestion and analysis stages run without manual input.

1

Massive Data Ingestion

The system scans market feeds, pricing histories, and macroeconomic indicators continuously, consolidating inputs that would otherwise require several separate tools to track.

2

Predictive Analysis

Models filter the ingested data against your stated risk tolerance and time horizon, identifying patterns and discarding signals that fall outside your defined parameters.

3

Tailored Execution

The engine optimises the resulting recommendation into a plain-language action, logged for review, while you monitor progress from a single dashboard.

Draymint Group research team reviewing risk model output on screen

Predictive risk reduction, built into every recommendation

Capital preservation is treated as a constraint on the model, not an afterthought. Before any reallocation is suggested, the system checks it against defensive thresholds set at account level.

The chart format used internally tracks projected drawdown against a rolling volatility band, flagging any recommendation that would push exposure beyond your pre-set limit before it reaches you.

  • Automated defensive rebalancingPositions are shifted toward lower-volatility holdings when correlation risk rises across linked assets.
  • Confidence-band monitoringRecommendations outside the model's stated confidence range are withheld rather than surfaced.
  • Capital-preservation limitsAccount-level thresholds cap how much reallocation can occur within a single cycle.

Applications for different approaches to capital

The underlying models are the same; the parameters applied differ depending on what you are trying to achieve.

For the passive earner

Our models are tuned to identify low-volatility yield opportunities that would otherwise require tracking multiple income-bearing instruments manually.

  • Parameters favour stability over short-term upside.
  • Defensive rebalancing triggers earlier than in growth-oriented profiles.
  • Recommendations are reviewed on a weekly cycle by default.

For portfolio diversification

The model analyses correlation across your existing holdings and surfaces allocations that reduce concentration risk without requiring you to research each new asset class.

  • Correlation mapping runs across all tracked asset categories.
  • Recommendations include a stated rationale for each proposed shift.
  • Suited to users consolidating holdings from more than one source.

For long-term growth

Time horizon is extended in the model's parameters, allowing it to tolerate short-term volatility in exchange for compounding exposure over a longer period.

  • Rebalancing cadence is slower, reducing unnecessary turnover.
  • Growth-weighted recommendations are logged alongside their reasoning.
  • Suited to capital not required for withdrawal in the near term.

Access the Engine

No technical setup is required. Most new accounts deploy their first model in under ten minutes, using the parameters set during onboarding.

Questions before you start? Read the FAQ or see why users choose Draymint Group.