This gallery of examples highlights typical use cases of the different tools provided by Portfolio Visualizer.
Compare historical performance and risk vs. return profile of different asset class allocations:
Analyze the performance, exposures and dividend income of a portfolio consisting of equities, ETFs and mutual funds:
Use the Monte Carlo simulation tool to model the probability of different outcomes based on the given portfolio asset allocation and cashflows.
Simulate portfolio performance with forward looking return and volatility assumptions rather than relying on historical estimates for asset returns.
| Asset Class | Expected Return |
|---|---|
| US Equities | 5.5% |
| International Equities | 5.7% |
| US Bonds | 1.8% |
| REITs | 5.0% |
| Sample assumptions for expected annual returns | |
Use Monte Carlo simulation to test portfolio growth and survival against specified financial goals both during career and retirement.
Visualize the efficient frontier for any asset classes or funds.
What asset mix has provided the best risk adjusted return historically?
How has the efficient frontier changed from decade to decade?
Use resampling to mitigate the impact of input estimate errors in the mean variance optimization and to improve diversification in the efficient frontier portfolios
Use the portfolio optimization tool to optimize portfolios based on risk adjusted performance or other target criteria.
Use optimization to find the risk parity portfolio that equalizes the risk contributions of portfolio assets.
| Asset | Risk Contribution Target |
|---|---|
| Vanguard Total Stock Market ETF (VTI) | 25% |
| Vanguard Total International Stock ETF (VXUS) | 25% |
| Vanguard Real Estate ETF (VNQ) | 25% |
| Vanguard Total Bond Market ETF (BND) | 25% |
Use allocation weight constraints at both asset and asset group level to enforce specific minimum and maximum allocation weights.
| Asset | Group | Min Weight | Max Weight |
|---|---|---|---|
| SPDR S&P 500 ETF | Equity | 5% | 40% |
| iShares S&P Small-Cap 600 Value ETF | Equity | 5% | 20% |
| iShares MSCI EAFE ETF | Equity | 5% | 30% |
| iShares MSCI Emerging Markets ETF | Equity | 5% | 15% |
| iShares 20+ Year Treasury Bond ETF | Fixed Income | 5% | 30% |
| iShares 7-10 Year Treasury Bond ETF | Fixed Income | 5% | 30% |
| iShares iBoxx $ Invmt Grade Corp Bd ETF | Fixed Income | 5% | 20% |
| Asset Class | Expected Return |
|---|---|
| US Equities | 5.5% |
| International Equities | 5.7% |
| US Bonds | 1.8% |
| REITs | 5.0% |
| Sample assumptions for expected annual returns | |
| Risk Factor | Existing Exposure | Target Exposure |
|---|---|---|
| Market (Rm-Rf) | 0.61 | 0.61 |
| Size (SMB) | 0.10 | 0.10 |
| Value (HML) | 0.15 | 0.20 |
| Term Risk (TRM) | 0.20 | 0.10 |
| Credit Risk (CDT) | 0.09 | 0.15 |
View asset correlations for selected assets. How has the correlation changed over time?
| Ticker | VTI | VNQ | GLD | BND |
|---|---|---|---|---|
| VTI | - | 0.76 | -0.02 | -0.32 |
| VNQ | 0.76 | - | 0.06 | -0.02 |
| GLD | -0.02 | 0.06 | - | 0.27 |
| BND | -0.32 | -0.02 | 0.27 | - |
| Daily correlations from 01/01/2011 to 12/31/2016 | ||||
Run factor regression (Mkt, HmL, SmB, Mom) to see the factor loadings for the specified assets:
| Ticker | Rm-Rf | SMB | HML | MOM | Annual Alpha | R^2 |
|---|---|---|---|---|---|---|
| IJS | 0.98 | 0.77 | 0.32 | -0.04 | 1.84% | 97.2% |
| IWN | 0.97 | 0.81 | 0.43 | 0.04 | -0.38% | 98.1% |
| RZV | 1.08 | 1.03 | 0.35 | -0.40 | 1.09% | 93.2% |
| VBR | 1.04 | 0.51 | 0.26 | 0.02 | 0.12% | 97.9% |
| Monthly returns regression from 01/01/2011 to 12/31/2016 | ||||||
Backtest moving average based models for a single asset or for a portfolio of assets. For example, test a tactical asset allocation model based on the S&P 500 index using VFINX with a 10-month simple moving average (SMA) from 1990 onwards.
How well did momentum based asset class rotation work in the past? Backtest asset class ETF momentum strategy rotating across asset classes based on the past 5-month performance:
Compare the results against buy-and-hold portfolios. How would the results change based on different time periods?
Explore dual momentum model combining relative momentum with an absolute momentum based trend-following filter:
Adaptive asset allocation model combining relative strength momentum model with inverse volatility or minimum variance based asset weights.
Hold top two best performing assets with risk parity weighting:
Use target volatility model to keep portfolio within preferred risk tolerance. Compare drawdowns and risk adjusted performance against annually rebalanced buy-and-hold portfolio.
Portfolio assets for 8% annualized volatility target: