Our Solutions
Comprehensive Risk Reporting
We not only calculate risk at the company, fund, and portfolio level but also project Net Asset Values and cashflows — enabling you to assess the probability of achieving a positive Internal Rate of Return by the end of the investment's life.
Projected Internal Rate of Return Distributions Across Funds (5-95% Percentiles)
IRR Statistics by Fund
| Fund | Median IRR (%) | Std Dev (%) | 5th Pctl (%) | 95th Pctl (%) | Prob Positive (%) |
|---|---|---|---|---|---|
| Fund 1 | 10.9 | 58.3 | -53.9 | 131.3 | 58.9 |
| Fund 2 | 11.9 | 18.8 | -15.2 | 46.1 | 74.3 |
| Fund 3 | 11.2 | 20.5 | -18.5 | 48.3 | 71.1 |
| Fund 4 | 12.2 | 17.5 | -12.8 | 44.0 | 76.6 |
| Fund 5 | 11.0 | 20.8 | -18.2 | 49.6 | 71.9 |
| Fund 6 | 11.8 | 19.3 | -16.4 | 47.0 | 73.9 |
| Portfolio | 11.6 | 19.7 | -16.8 | 47.7 | 72.2 |
Risk Measures by Investment Type
Risk Analysis of Investments in Private Equity Funds
| Fund Name | Vintage Year | Commited Amount | Risk due to Cash Flow Timing | Risk due to Market Fluctuations | Risk due to Market Fluctuations and Secondary Market Liquidity |
|---|---|---|---|---|---|
| Fund 1 | 2012 | 322.8 | 3.2 | 0.7 | 1.2 |
| Fund 2 | 2019 | 150.0 | 18.5 | 29.9 | 52.2 |
| Fund 3 | 2017 | 400.0 | 14.3 | 19.4 | 34.2 |
| Fund 4 | 2021 | 25.0 | 0.3 | 0.5 | 0.9 |
| Fund 5 | 2017 | 149.0 | 24.5 | 33.5 | 58.4 |
| Fund 6 | 2018 | 145.6 | 29.7 | 44.7 | 78.5 |
| Portfolio | 108.4 | 199.6 |
For private equity funds and portfolios, we analyze risks related to cash flow timing, liquidity, and market fluctuations to support scenario-driven decisions. Please note cashflow timing risk is not aggregated due to path-dependency of individual risks.
Risk Analysis of Direct Investments in Private Companies
| Company Name | Net Asset Value | Risk due to Market Fluctuations | Total Risk |
|---|---|---|---|
| TechInnovate Solutions | 7.5 | 2.2 | 4.0 |
| HealthCare Dynamics | 18.0 | 4.0 | 6.5 |
| GreenEnergy Systems | 55.0 | 10.9 | 14.0 |
| Portfolio Total | 80.5 | 13.6 | 18.2 |
Total risk represents the combination of market risk and idiosyncratic risk. The idiosyncratic component captures company-specific factors not explained by market movements. All dollar amounts are presented in millions. Risk figures were based on a 3-month horizon with a 95% confidence level.
Stress Test & Tail Risk Insights
Our stress testing proactively identifies portfolio vulnerabilities and extreme events by anticipating a diverse range of extreme yet realistic scenarios, offering deeper insights beyond standard risk metrics.
Stress Test of a Portfolio of Single Companies
| Scenario | Description | NAV (% of Base) | Default Rate | Exit Correlation |
|---|---|---|---|---|
| Base Case | Normal market conditions | 100.0% | 15.3% | -97.6% |
| Market Crash | Market down 30%, lower distributions, higher defaults | 74.0% | 35.5% | -32.1% |
| Liquidity Crisis | Funding constraints and secondary market distress | 86.7% | 26.4% | 29.1% |
| Slow Exit | Extended holding periods, delayed exits | 97.0% | 19.7% | -95.0% |
Stress Test of a Portfolio of PE Funds
| Scenario | Description | NAV (% of Base Case) | Median Forecast IRR |
|---|---|---|---|
| No Stress | Normal market conditions | 115.7% | 11.5% |
| Market Crash | Market down 30%, lower distributions, and higher secondary market discounts | 86.1% | 3.5% |
| Liquidity Crisis | Funding constraints, lower distributions, and secondary market distress | 95.9% | 6.6% |
| Slow Exits | Extended holding periods, and delayed distributions | 104.9% | 8.8% |
| Rate Cuts | 50bps fall in interest rates over the next 6 months | 116.4% | 11.5% |
| Spread Widening | 200bps widening of credit spreads | 112.4% | 10.7% |
Note: Stress test was performed on a representative sample of 100 funds typically held by institutional investors.
Stress scenarios assume 6-month shock conditions.
IRR is calculated using full simulation of future cashflows including initial NAV.
Tail Risk Analysis
By identifying and analyzing the economic and financial factors that drive worst-case scenarios—often referred to as tail events—we gain deeper insights into potential vulnerabilities within our portfolios.
This proactive approach allows us to anticipate extreme but plausible risks, facilitating the timely implementation of targeted hedging and risk mitigation strategies.
| Scenario | Maximum Drawdown | Annualized Volatility | Contributing Factor | Market Indices Associated |
|---|---|---|---|---|
| Scenario 1 (Path 125) | 95.41% | 60.29% | Severe Liquidity Crisis | TED Spread / LIBOR-OIS Spread |
| Scenario 2 (Path 46) | 95.44% | 66.88% | Prolonged Economic Recession | ISM Manufacturing PMI / Conference Board Leading Index |
| Scenario 3 (Path 107) | 97.59% | 76.27% | Market Valuation Collapse | S&P 500 Shiller CAPE Ratio |
| Scenario 4 (Path 71) | 88.23% | 63.42% | Sector-Specific Disruption | MSCI Sector-Specific Indices (Tech/Healthcare/Energy) |
Factor Paths Driving Worst-Case Scenarios
