The Portfolio Performance chart is probably the easiest part of the dashboard to misuse. A rising line invites a simple conclusion: the model worked.
Slow down. The chart is a current-methodology model simulation, not a brokerage statement, audited live performance, or proof of future outperformance. The history before January 2, 2025 is a retrospective reconstruction, not a record of signals published live. Later rows occupy the archived-record period, but they were recalculated under the same methodology so the series never mixes versions.
What the simulation does
The performance engine begins with the reference maximum-risk portfolio and follows the current-methodology daily signal history from the first available trading session of 2020. A lower total-risk target must persist for two consecutive closes; adding total risk or rotating between risk assets at the same total-risk level requires five closes. The simulation trades a confirmed target on the next market session.
Investable ETFs use adjusted total returns so distributions do not appear as losses. Gold uses GLD before GLDM and chains the two funds on their first common trading session. Trades include 5 basis points of transaction cost and 5 basis points of slippage. Residual cash earns the FRED three-month Treasury constant-maturity yield, accrued over calendar days.
Those choices make the result more realistic than a same-day, cost-free price chart. They do not make it live performance.
Why next-session execution matters
A signal calculated at today’s close cannot be filled at that same closing price unless the order was known before the calculation finished. Using the next session avoids that look-ahead error.
The difference can be material around gaps and fast reversals. A model that always buys yesterday’s close after seeing today’s data has quietly borrowed information from the future.
The simulation also stores the signal history used by the calculation. The chart marks the boundary between retrospective reconstruction and the archived-record period. Revised macro GRID data remains context-only because the dashboard does not yet store true point-in-time vintages.
Read the benchmark carefully
The main comparison is an annually rebalanced 60% stocks, 30% gold, and 10% bitcoin portfolio. It starts with the same sleeves and the same sample period, which makes it more useful than comparing the model with the S&P 500 alone.
The chart also includes a conventional 60% stocks / 40% bonds comparison using adjusted-total-return VT and AGG, rebalanced on the first trading day of each year. It uses the same start and end dates as the KISS simulation, but it is not a matching-allocation benchmark because it replaces gold and bitcoin with bonds.
Benchmark choice still affects the story. A static portfolio, annual rebalance, monthly rebalance, and stock-only index answer different questions. Vanguard’s rebalancing guide explains why the rebalancing rule itself is part of portfolio behavior.
Base allocation also affects the story. The KISS 40/30/30 Performance page runs the same current-methodology signal process with 40% stocks, 30% gold, and 30% bitcoin, alongside an annually rebalanced benchmark with matching starting weights and the same start date. Its additional 60/40 line is a common reference portfolio, not a like-for-like benchmark. These are useful comparisons, not evidence that one base allocation is universally better.
Sortino is not a verdict
The dashboard reports return, CAGR, volatility, maximum drawdown, and Sortino ratio. Sortino focuses on downside volatility, which can be useful for a risk-control strategy. It remains one statistic from one sample.
A high Sortino ratio over a short period may reflect favorable timing, limited stress, or a small number of losses. AQR’s long-run trend research spans far more markets and history than the dashboard’s common three-sleeve sample. That gap in evidence should remain visible.
What the simulation excludes
The result excludes taxes, account restrictions, bid-ask variation beyond declared slippage, market impact, investor cash flows, and personal implementation delays. A taxable investor may experience a very different result from an IRA following the same target.
The CFA Institute’s GIPS standards address the ways performance presentations can mislead when definitions, composites, and calculation rules are vague. The dashboard does not claim GIPS compliance. The narrower lesson still applies: name the assumptions and do not blur simulated results with actual client performance.
The SEC’s asset-allocation guidance is also relevant. A model result cannot replace a personal plan, tax analysis, or risk assessment.
A better way to judge the chart
Use Portfolio Performance to inspect the process, not to crown a winner.
Check the reconstruction boundary, execution timing, total-return treatment, costs, cash return, and benchmark. Then ask whether the sample and proxy choices support the claim you want to make. The chart does not support grand claims, and the page should never pretend otherwise.