Prima Investment Intelligence Platform
A dynamic analytic system with our proprietary models that adjust as market conditions change.
A cross-asset research system that brings established financial models and Prima’s proprietary intelligence into one transparent, comparable decision framework.
For professional research and decision support. Not investment advice.
PRIMA / CROSS-ASSET ANALYSISMODEL STACK 01.6
AnalyseFund A + Listed Co. + Startup X3 assets
PRAR1.42Risk-adjusted return
PIQ78Investment quality / 100
PFR68%P(return > 0)
One analytical spine
Different assets. The same economic questions.
The system respects the mathematics of each asset class, then normalises the outputs that matter to an investment committee: return, loss, liquidity, time, uncertainty and portfolio contribution. A system updated by the hour. Feeding back real-time information to you.
Ingest
Market data, returns, models, filings, decks, cap tables and investment theses.
Calculate
100+ conventional metrics through the correct asset-specific engine.
Normalise
Cross-asset comparison without pretending fundamentally different investments are identical.
Challenge
Prima metrics, probabilistic scenarios and deliberate thesis-breaking analysis.
Transparent by design
Industry-standard mathematics below. Prima intelligence above.
Every conclusion remains traceable to the underlying inputs, formulae and assumptions. Analysts can move from a clear signal to the calculation beneath it.
DCF · NPV · IRR · MOIC · TVPI · DPI · RVPI · PME · Sharpe · Sortino · Alpha · Beta · CVaR · Drawdown · Correlation · Factor exposure · Scenario analysis
Valuation, performance, downside, liquidity and portfolio diagnostics are selected for the asset under review.
PRAR
(Expected return − risk-free rate) / weighted downside × persistenceExtends beyond volatility to drawdown, tail loss, liquidity, concentration and model uncertainty.
PIQ 0–100
A calibrated composite of return, downside, tail risk, quality, valuation, liquidity, correlation, persistence and uncertainty.
PFR distribution
Bear, base and bull outcomes with explicit probabilities—not a falsely precise single target price.
Asset-specific engines
The model changes when the investment changes.
A startup without price history should not be forced through a listed-equity model. Each engine uses the available evidence, then maps its result into the shared decision framework.
Public companies
Fundamental · relative valuation · factor models · macro · filings and calls
Startups and private companies
Unit economics · burn · retention · exit scenarios · probability-weighted MOIC
Hedge funds and managers
Performance · drawdowns · factors · liquidity · persistence · strategy drift
VC, PE and portfolios
Cash flows · concentration · vintage · scenarios · look-through diversification
Product demonstrations
Watch each engine work—then compare the results.
Five asset-specific walkthroughs show the inputs, unified output and calculation ledger. Two comparative demonstrations show how PIIP turns different investment structures into decision-relevant signals.
Comparative analysis
Cross-asset decision view
See return, downside, liquidity and PIQ across all five investment types.
Target comparison
Two opportunities, side by side
See why higher upside does not necessarily mean stronger risk-adjusted quality.
Public equity
Listed-company analysis
Valuation, quality, downside and forward scenarios.
Open detailed example →Hedge fund
Manager and strategy analysis
Returns, drawdowns, factors, persistence and liquidity.
Open detailed example →Startup
Venture opportunity analysis
Upside, unit economics, concentration and uncertainty.
Open detailed example →VC / private equity
Fund analysis
MOIC, cash flows, locked capital and portfolio risk.
Open detailed example →Portfolio
Whole-portfolio analysis
Contribution, diversification, concentration and tail risk.
Open detailed example →All demonstrations use fictional, modelled reference data for product illustration. They are not investment advice, recommendations or live assessments.
A model that must earn trust
Every forecast creates a measurable future benchmark.
Proprietary outputs are designed to be timestamped and assessed against realised outcomes. Calibration, Brier scores, forecast error, hit rate and model decay make performance measurable—and weak signals replaceable.
- At forecast
- Inputs, model version and probability distribution locked
- At horizon
- Outcome measured against the original distribution
- Over time
- Weights recalibrated with out-of-sample evidence
Investment decisions, made legible
Move from fragmented analysis to a system of record for investment conviction.
The platform is an investment-research and decision-support system. Proprietary metrics require ongoing validation and review against realised outcomes. Nothing on this website is investment, legal, tax or accounting advice, an offer of securities, or a recommendation to transact.