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Risk Parity Portfolio ModelFree Financial Model Download

Build a risk parity portfolio with equal risk weights across asset classes and leverage adjustments, without manually recalculating volatility allocations. Covers equities, fixed income, and alternatives with rebalancing mechanics and drawdown analysis.

Free download. No sign-up required.

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About this model

This allocation framework weights assets by inverse volatility to achieve equal risk contribution across equities, bonds, and alternatives—the core principle behind Bridgewater's All Weather Fund and similar strategies. Input annual expected returns and volatilities per asset class; the model computes optimal inverse-volatility weights, applies leverage (1.5x-3.0x), and outputs portfolio returns net of financing costs, management fees, and transaction costs. It then verifies that each asset class contributes equally to total portfolio variance using the full covariance matrix (not simplified weighting).

The model projects 5+ years of portfolio value, Sharpe ratio, drawdown risk (99% VaR), and rebalancing triggers. Key mechanics: leverage ratio drives a financing cost line (SOFR + spread), transaction costs scale with turnover, and fee schedules separate management from performance-based costs. Circularity is eliminated by computing fees and returns on opening (not ending) NAV. Validation checks confirm equal risk contributions, weight sums to 100%, and leverage remains within bounds.

Target users are portfolio managers, CIOs, family offices, and institutional allocators managing $50M-$50B who want to optimise across correlated asset classes. Includes sensitivity on leverage ratio and expected return assumptions to show how portfolio targets change under different macro regimes.

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Income statement, brown brand palette
income_statement.xlsx
Income statement, green brand palette
income_statement.xlsx
Income statement, red brand palette

Recolor to your brand.
Formatted to IB standards.

Named theme colors repaint the whole workbook in one click, on top of an investment-banking structure with blue inputs, black formulas, and green cross-sheet links.

  • Brand-ready
  • Institutional grade
  • Fully auditable

What's included

  • Historical volatility calculation by asset class
  • Inverse volatility weighting and leverage sizing
  • Portfolio-level risk contribution analysis
  • Rebalancing mechanics and threshold triggers
  • Drawdown analysis and stress testing by risk factor

Equal risk contribution framework

Size positions so each asset class contributes the same amount of portfolio volatility rather than the same dollar amount, avoiding hidden equity concentration.

Leverage framework and funding cost

Model appropriate leverage ratios to boost returns while maintaining target portfolio volatility, with repo financing costs included in the return analysis.

Factor risk decomposition

Break down portfolio risk by equity beta, duration, credit spread, and inflation beta to identify where true concentration sits across the portfolio.

Frequently asked

What is a risk parity portfolio model?+

A model that allocates capital across asset classes based on inverse volatility so that each asset contributes equally to portfolio risk rather than being weighted by dollar amount.

Why weight by volatility instead of dollar amounts?+

Equal dollar weights lead to equity-heavy portfolios where stocks dominate risk. Risk parity equalises volatility contribution so every asset class matters equally to drawdowns.

What volatility measure should I use?+

Use historical rolling volatility, typically 252-day realised vol, or forward-looking implied volatility from options. Adjust for regime changes and tail risk periods.

Do I need leverage to run a risk parity strategy?+

Yes, to match target portfolio volatility while holding lower-vol assets like bonds. Typical risk parity portfolios lever 1.5x to 2.5x to achieve 10 to 12% annual volatility.

How often should a risk parity portfolio be rebalanced?+

Rebalance when volatility weights drift beyond defined threshold bands, typically monthly or quarterly, depending on transaction cost tolerance and tracking error targets.

Alex Tapio, founder of Finamodel and ex-Deloitte financial modelling expert

Alex Tapio

Founder of Finamodel • Professional Financial Modeller • Ex-Deloitte