From Guesswork to Data: Introducing Market Data-Driven Portfolio Projections

The Problem with Guessing

"What equity return should we assume for Monte Carlo?"

If you've run portfolio simulations, you've faced this question. Most tools force you to guess:

• 8% equity returns? 10%? 12%?
• 18% volatility? 15%? 22%?
• -20% equity-bond correlation? 0? Positive?

The problem: Everyone uses different assumptions. Results aren't comparable. Your auditors question your methodology. Your LPs ask "where did those numbers come from?"

And honestly? You don't have a great answer. "Industry average" or "seemed reasonable" doesn't inspire confidence in a $500M portfolio decision.

The Real Cost of Guessing

Let's be specific about what guessing costs you:

Scenario 1: Conservative Guess (6% equity returns)

• Your Monte Carlo shows P50 outcome: $280M NAV in 10 years
• IC decides to commit $15M to new fund
• Liquidity planning: conservative, holding more cash

Scenario 2: Aggressive Guess (12% equity returns)

• Your Monte Carlo shows P50 outcome: $420M NAV in 10 years
• IC commits $30M to new fund
• Liquidity planning: aggressive, lower cash reserves

Reality: Actual equity returns were 9%

• Scenario 1 was too conservative → missed opportunities
• Scenario 2 was too aggressive → liquidity crunch in year 3

The difference between 6% and 12%? You guessed wrong. And it cost you either opportunity or risk.

The Solution: Real Market Data

Today we're launching the Market Data Platform — pulling real market data to calibrate your projections.

No more guessing. Use actual market returns, calculated from real data, reproducible for audits.

What You Get

28 Instruments Across Asset Classes:

Equities:

• S&P 500 Total Return (SP500-TR)
• Russell 2000 Total Return (R2000-TR)
• MSCI EAFE (EAFE-TR)
• NASDAQ Composite (IXIC-TR)

Fixed Income:

• High-Yield Bonds (HY-TR)
• Investment-Grade Corporates (IG-TR)
• US 10-Year Treasury (US10Y)
• US 2-Year Treasury (US2Y)

FX Pairs:

• EUR/USD, GBP/USD, JPY/USD
• CHF/USD, CAD/USD, AUD/USD

Commodities:

• Gold (XAU-USD)
• Oil (WTI-USD)

Crypto:

• Bitcoin (BTC-USD)
• Ethereum (ETH-USD)

Data Coverage:

• 10,000+ observations
• Up to 10 years of history per instrument
• Daily data, aggregated to monthly returns
• Sourced from Alpha Vantage and FRED

Statistics Engine:

• Covariance matrices (sample, EWMA, Ledoit-Wolf shrinkage)
• Correlation analysis
• Expected returns (historical, CAPM)
• Sharpe ratios, drawdowns, volatility

Snapshot-Based Reproducibility:

• Every analysis pins to a specific snapshot (e.g., SNAP-2025-11-01)
• Time-travel back to any date
• Show auditors exactly which data you used
• No more "I can't reproduce last quarter's forecast"

Before vs After

Before: Guessing

Monte Carlo Configuration:

Market Assumptions:
  Equity Mean Return: 8%        ← You typed this
  Equity Volatility: 18%        ← You typed this
  Bond Mean Return: 4%          ← You typed this
  Bond Volatility: 6%           ← You typed this
  Equity-Bond Correlation: -20% ← You typed this

Source: "Industry average" (trust me bro)
Reproducible: No
Defensible to auditors: Not really

Your IC asks: "Why 8%?" You answer: "That's what we've always used." IC: "Is that still valid?" You: "¯\(ツ)/¯"

After: Data-Driven

Monte Carlo Configuration:

Market Assumptions:
  [Use Market Data] ← You click this button

System fetches:
  Data Source: S&P 500 Total Return Index
  Period: 2015-01-01 to 2025-01-01 (10 years)

  Equity Mean Return: 11.2%     ← From real data
  Equity Volatility: 16.8%      ← From real data
  Bond Mean Return: 4.8%        ← From HY-TR index
  Bond Volatility: 9.2%         ← From real data
  Equity-Bond Correlation: -31% ← Calculated from data

  Snapshot: SNAP-2025-11-01 (reproducible forever)

Source: S&P 500 Total Return (FRED)
Reproducible: Yes (snapshot SNAP-2025-11-01)
Defensible to auditors: Absolutely

Your IC asks: "Why 11.2%?" You answer: "S&P 500 Total Return Index, last 10 years, snapshot SNAP-2025-11-01." IC: "Can we reproduce this?" You: "Yes, it's pinned to that snapshot. I can show you the raw data."

Real-World Use Cases

1. Monte Carlo Calibration

The Old Way:

1. Open Excel, Google "average stock market returns"
2. Find article saying "10% historically"
3. Type "10%" into Monte Carlo config
4. Run simulation
5. IC asks "why 10%?" → you have no great answer

The New Way:

1. Open Nagare Monte Carlo
2. Click "Use Market Data"
3. Select "S&P 500 Total Return, last 10 years"
4. System auto-populates: 11.2% mean, 16.8% vol
5. Run simulation
6. IC asks "why 11.2%?" → "S&P 500, 2015-2025, here's the snapshot"

Time saved: 30 minutes of research Confidence gained: Infinite

2. Benchmark Comparisons

Question: "How did our PE fund perform vs public markets?"

Without Market Data:

• You have PE returns: 18.2% IRR
• You Google "S&P 500 returns 2015-2020"
• Find conflicting numbers (14%? 16%? Depends on source)
• Make rough comparison
• Not confident in conclusion

With Market Data:

Your PE Fund:
  IRR: 18.2%
  TVPI: 2.1x
  Period: 2015-2020

Public Market Equivalent (PME):
  S&P 500 Total Return: 14.8% CAGR
  TVPI Equivalent: 1.9x

Outperformance: +3.4% IRR
Alpha (net of fees): +3.4%
Snapshot: SNAP-2025-11-01

Conclusion: Your PE fund beat public markets by 3.4% annually. Defensible. Reproducible.

3. Correlation Analysis

Question: "Are my private funds correlated with public markets?"

Why it matters: If your PE funds tank when SPY tanks, you're not as diversified as you thought.

With Market Data:

1. Navigate to Market Data → Statistics
2. Add instruments: SP500-TR, HY-TR, your fund proxy
3. Click "Compute Correlation Matrix"
4. Results in 5 seconds

Insight: Your PE exposure is NOT independent of public markets. Adjust allocation accordingly.

4. Reproducibility for Audits

Scenario: It's Q4 2025. Your auditor asks: "Show me the assumptions you used in Q1 2025 forecasts."

Without Market Data:

• You dig through old Excel files
• Find version "Final_v3_FINAL_revised.xlsx"
• Cell B7 says "8%" but no source
• You can't prove where it came from
• Auditor is skeptical

With Market Data:

• You click on Q1 2025 forecast
• It references snapshot: SNAP-2025-01-01
• You navigate to Market Data → Snapshots → SNAP-2025-01-01
• Exact data shown: SP500-TR (2015-2025), mean 11.2%, vol 16.8%
• Export raw data as CSV
• Hand to auditor: "Here's the exact data we used."

Auditor: "Perfect. This is compliant."

Getting Started

Step 1: Sync Data (One-Time Setup)

1. Log in to Nagare
2. Navigate to Market Data tab
3. Click "Sync Data"
4. Select provider: Alpha Vantage (default)
5. Choose instruments: All recommended (or custom selection)
6. Click "Start Sync"

Time: 60-90 seconds Frequency: One-time setup, then weekly/monthly refreshes

Step 2: Use in Monte Carlo

1. Go to Fund Detail → Monte Carlo
2. In "Market Assumptions" section, click "Use Market Data"
3. Dialog appears with equity/bond indices
4. Click "Apply"
5. System auto-fills parameters with real data
6. Run simulation

Time: 10 seconds Confidence: Maximum

Step 3: Explore Statistics

1. Navigate to Market Data → Statistics
2. Click "Add Instruments"
3. Select 2-10 instruments
4. Choose analysis: Covariance Matrix, Correlation Heatmap, Expected Returns
5. Click "Compute"

What's Next

December 2025

• Custom universes (create your own index baskets)
• Factor models (Fama-French, momentum, value)
• Real-time data feeds (15-min delayed quotes)

Q1 2026

• Bloomberg integration (for enterprise clients)
• Options and derivatives pricing
• Scenario analysis (what if equity vol spikes 50%?)
• Regime detection (bull vs bear market auto-switching)

Q2 2026

• Machine learning models (predict returns, vol, correlations)
• ESG data integration
• Alternative data (sentiment, satellite imagery)

Pricing

Market Data Platform is included in all paid plans:

• Free (up to 10 funds): 3 instruments, last 3 years
• Boutique ($3,500/mo): 28 instruments, up to 10 years
• Institutional ($8,500/mo): All instruments, unlimited history, daily snapshots
• Sovereign (Custom): Bloomberg/Refinitiv, real-time feeds

Try It Today

Ready to stop guessing and start using real data?

1. Log in: app.nagarehq.com
2. Navigate to Market Data
3. Click "Sync Data"
4. Use in your next Monte Carlo simulation

Free trial: 14 days, no credit card required.

Questions? Email hello@nagarehq.com

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Related:

• Monte Carlo vs Deterministic Modeling
• Calibrating Monte Carlo with Market Data
• Building Market-Linked Monte Carlo Engine