Mean reversion bonus is optional
Rebalancing only adds return when assets mean-revert; in a one-way bull market, buy-and-hold can win (with higher risk).
Context matters
Rebalancing Impact Calculator
Inputs
Assets & Target Weights
Add 2–5 assets. Weights auto-normalize to 100%.
| Name | Target weight (%) |
|---|
Option A: Paste historical returns (preferred)
Paste CSV with columns: Date, Asset1, Asset2, ... where returns are percentages per period (e.g., monthly). Example:
2020-01, -1.5, 0.8 2020-02, -8.2, 0.5 2020-03, -12.4, 2.1 ...
Option B: Monte Carlo (quick synthetic series)
Enter annualized mean (%) and stdev (%) for each asset; we assume zero correlations for simplicity (quick mode).
Strategies
Results
Summary:
Metrics (annualized unless noted)
| Strategy | CAGR | Volatility | Sharpe* | Max Drawdown | Turnover (avg/yr) | Trading Cost (total) | End Value |
|---|
*Sharpe uses optional risk-free input; if blank, RF=0.
Equity Curves
Portfolio value over time (same starting £).
What Rebalancing Changes (and What It Doesn’t)
Rebalancing nudges a drifting portfolio back to its target weights. When one asset rallies and another lags, the mix often drifts away from the plan (for example, a 60/40 ending up at 68/32). Rebalancing sells some of the winner and buys the laggard to restore the target. The potential benefits are intuitive: consistent risk exposure, prevention of overconcentration, and—if markets mean-revert—an opportunity to “buy low/sell high”. The trade-offs are also clear: transaction costs, taxes (not modeled here), and the possibility of trimming winners too early during strong momentum phases.
This calculator lets you compare three approaches. Buy & Hold never rebalances; weights drift freely. It can produce higher returns in a strong one-asset bull market, but with higher concentration risk. Periodic rebalancing (e.g., yearly) is schedule-based and simple to implement. Threshold rebalancing reacts to deviations (e.g., ±5% bands) and can be more responsive in volatile markets where weights move around quickly.
We estimate annualized return (CAGR), volatility, max drawdown, and Sharpe ratio (if you provide a risk-free rate). We also compute turnover—the fraction of the portfolio traded—plus the cumulative drag from your per-trade cost in basis points. Turnover tends to be highest for tight bands and frequent schedules. In practice, investors often coordinate rebalancing with cash flows (new contributions or withdrawals) to reduce trading, or use wider bands to balance cost versus tracking.
Inputs are flexible. Paste your own asset return series (monthly, quarterly, or annual) for a history-based comparison, or generate a quick synthetic series by specifying annualized means and volatilities. Because the tool runs entirely in your browser, your data stays private. The output is not a prediction—just a transparent, testable way to see how different policies would have affected your portfolio given the return paths you supply.
Educational only—not investment advice. Consider fees, taxes, trading frictions, and your personal constraints.
5 Fun Facts about Rebalancing
Tracking error tax
Rarely rebalancing can let a 60/40 morph into 80/20. That higher equity weight explains most “outperformance,” not magic.
Hidden drift
Cash flows are stealth rebalances
Plowing new contributions into the laggard asset often captures most of the benefit with less trading cost than selling winners.
Low-friction
Bands beat calendars in choppy markets
Threshold (e.g., ±5%) rules can react faster in volatile periods, but may spike turnover if bands are too tight.
When to act
Vol drag explains “why bother”
Even with identical averages, lower volatility from rebalancing can raise geometric (compound) returns via reduced volatility drag.
Compounding edge