---
title: "Policy Portfolio Builder"
description: "Policy Portfolio Builder: enter target weights for equities, bonds, alternatives, and cash, then compute expected return, volatility, and Sharpe ratio."
canonical: https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/policy-portfolio-builder/
source: "Swoopr Investment: https://www.getswoopr.com"
---

Strategic & Tactical Asset Allocation



# Policy Portfolio Builder



Enter target weights for each asset class and adjust the capital market assumptions, then compute the portfolio's expected return, volatility, and Sharpe ratio. All calculations happen in your browser, no data is sent anywhere.





        



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## Direct Answer



> A policy portfolio builder computes a strategic asset allocation's expected return, volatility, and Sharpe ratio from the target weights and capital market assumptions you enter for each asset class. It lets you test how changing expected returns, volatilities, or weights shifts the policy portfolio's risk and return profile before committing to it. All calculations run in your browser and are for educational planning only.









 



## Target Weights





Global Equities




%






Investment-Grade Bonds




%






Alternatives / Real Assets




%






Cash & Short-term




%




Total: 100%





 



## Capital Market Assumptions





Expected Returns (%/yr)




Global Equities




%






IG Bonds




%






Alternatives




%






Cash




%








Annualised Volatilities (%)




Global Equities




%






IG Bonds




%






Alternatives




%






Cash




%








Correlations




Equity, Bond










Equity, Alt










Bond, Alt










Risk-free rate




%
















Compute Portfolio


Reset to defaults






 



## Portfolio Results







N/A


Expected Return






N/A


Portfolio Volatility






N/A


Sharpe Ratio











Risk contribution by asset class







### Asset class contributions





| Asset class | Weight | Exp. return | Return contrib. | Volatility | Marginal risk contrib. |
| --- | --- | --- | --- | --- | --- |








Expected return is the weighted average of CMA inputs. Portfolio volatility uses the 4-asset covariance matrix (cash assumed uncorrelated with all other assets). Sharpe ratio = (Expected return − Risk-free rate) / Volatility. Marginal risk contribution = (w × Σw) / σ_p per asset class. Results are illustrative, actual outcomes will differ.








## What this tool calculates



The **expected return** is the weighted average of each asset class's expected return: *E[R_p] = Σ w_i × E[R_i]*. The **portfolio volatility** is the square root of the portfolio variance, computed from the full covariance matrix. For four asset classes with covariance matrix Σ and weight vector w: *σ_p = √(wᵀ Σ w)*. Cash is assumed uncorrelated with all other asset classes. The **Sharpe ratio** measures risk-adjusted return: *S = (E[R_p] − R_f) / σ_p*. The **marginal risk contribution** of each asset class is its proportional contribution to total portfolio variance: *MRC_i = (w_i × (Σw)_i) / σ_p*, expressed as a percentage of total portfolio risk.



Use this tool to explore how different strategic asset mixes compare on a risk-adjusted basis before running full mean-variance optimization. The inputs are the same capital market assumptions (CMAs) your investment committee would use to set a formal policy portfolio. See [Strategic Policy Portfolio Design](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/strategic-policy-portfolio-design/) for the framework behind the inputs.








## Frequently Asked Questions




### What belongs in the capital market assumption fields?



Forward-looking estimates for each sleeve, not historical averages. Expected return is the long-horizon annual return assumed for the asset class over the policy horizon, volatility is its assumed annual standard deviation, and the correlations describe how the sleeves are assumed to move together. Published assumption sets from asset managers are a common starting point. Whatever source is used, all four sleeves need to come from one consistent framework, since mixing sources produces a covariance structure that does not hold together.




### Why does the tool treat cash as uncorrelated with the other asset classes?



It is a simplifying assumption that keeps the covariance matrix tractable while remaining close to reality for a short-dated cash sleeve, whose value barely moves with equity or credit markets. It is not exactly true: cash yields respond to the same policy rate that influences bond prices, so a small relationship exists. The effect on a portfolio result is minor at typical cash weights and grows as the cash allocation grows, which is worth remembering when testing a high-cash mix.




### Why is expected return a simple weighted average when volatility is not?



Expected return is a linear function of the weights, so combining assets averages their expected returns exactly, with no interaction term. Variance is quadratic: it depends on every pair of holdings through their covariances, so the combination can be lower than any weighted average of the individual volatilities. That asymmetry is diversification. It is also why the correlation inputs affect the volatility and Sharpe outputs while leaving the expected return figure untouched.




### What does marginal risk contribution mean in the results table?



It measures how much of total portfolio volatility comes from that sleeve: the sleeve's weight times how much portfolio volatility changes for a small increase in that weight. It is not the same as the sleeve's own volatility. A holding that moves against the rest of the portfolio can carry high standalone volatility and a low, even negative, marginal contribution. Because each value in the table already includes the sleeve's weight, the values sum to total portfolio volatility, and the percentage shares sum to 100 percent, which is what makes them comparable across sleeves.




### Does a higher Sharpe ratio here mean a better policy portfolio?



It means a higher expected excess return per unit of assumed volatility, given the inputs entered. Whether that describes a better policy depends on things the calculation does not see: whether the mix meets a required spending rate in absolute terms, whether its drawdown behavior is tolerable, whether the sleeves can actually be held and rebalanced, and whether the assumptions themselves are reasonable. A ratio computed from optimistic inputs is a statement about the inputs.




### Why must the target weights sum to 100%?



The math assumes a fully allocated portfolio, so the weights are shares of one whole. A set summing to less than 100% implicitly leaves capital unmodeled, and the expected return and volatility figures would then describe only the part that was entered while being read as though they described everything. Holding a deliberate cash position is modeled by putting that share into the cash sleeve rather than by leaving the total short.




### Can a portfolio with more than four asset classes be modeled here?



The tool works in four aggregate sleeves, so a finer allocation is represented by mapping each holding into the closest sleeve and blending its assumptions by weight. That approximation is reasonable when the components inside a sleeve behave similarly and misleading when they do not, since blending averages away the differences that made them separate allocations. A mix where private assets and listed real assets sit in the same sleeve is the common case where the approximation costs the most.




### How sensitive are the outputs to the correlation inputs?



Portfolio volatility responds directly to them, and the response grows with the weights of the two sleeves involved. Changing the equity to bond correlation across the range it has historically occupied can move portfolio volatility noticeably for a balanced mix, while leaving expected return unchanged. Running the same weights across a range of correlation values, rather than one point estimate, is the practical way to see how much of a result depends on that single assumption.




### Do the results account for fees, taxes or trading costs?



No. The figures describe a gross portfolio built from the assumptions entered. Fund expenses, advisory fees, taxes on distributions and the cost of rebalancing all reduce what an investor actually receives, and they do so in ways that depend on the vehicles, account types and turnover involved rather than on the allocation alone. Comparing two mixes here compares them before those effects, which can differ materially between the two.












## References



- Markowitz, H. (1952). "Portfolio Selection." *The Journal of Finance*, 7(1), 77-91, the mean-variance framework this tool's expected-return, volatility, and Sharpe-ratio calculations are built on.
- [CFA Institute Research and Policy Center](https://rpc.cfainstitute.org/)
- [SEC Investor.gov: Asset Allocation and Diversification](https://www.investor.gov/introduction-investing/getting-started/asset-allocation)






## Related Reading

- [Strategic & Tactical Asset Allocation](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/) the section this guide belongs to
- [Capital Market Assumptions and Expected Returns](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/capital-market-assumptions-and-expected-returns/) a companion guide in this cluster
- [Cross-Asset Momentum and Trend-Following Overlays](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/cross-asset-momentum-and-trend-following-overlays/) a companion guide in this cluster
- [Deviation Bands and Rebalancing Triggers](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/deviation-bands-and-rebalancing-triggers/) a companion guide in this cluster
- [Factor Tilts in Strategic Allocation](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/factor-tilts-in-strategic-allocation/) a companion guide in this cluster
- [Governance of the Allocation Process](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/governance-of-the-allocation-process/) a companion guide in this cluster
- [Strategic Policy Portfolio Design](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/strategic-policy-portfolio-design/) a companion guide in this cluster
- [Tactical Asset Allocation Signals and Frameworks](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/tactical-asset-allocation-signals-and-frameworks/) a companion guide in this cluster
- [Tactical Tilt Impact Calculator](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/tactical-tilt-impact-calculator/) a companion guide in this cluster
- [Tail Risk Overlays and Hedging Policy](https://www.getswoopr.com/portfolio-management/strategic-tactical-allocation/tail-risk-overlays-and-hedging-policy/) a companion guide in this cluster