Robo-Advisor Rebalancing Lab

Robo-Advisor Policy

Risk tolerance (target equity) 60%

Rebalancing mode

Drift band (± threshold) 5%

Rebalance every 12 mo

Market volatility × 1.0×

Simulation speed 6 mo/s

Portfolio state

Elapsed

0 mo

Rebalances

Robo-advisor value

$100,000

Buy & hold value

$100,000

Transaction costs

Tracking error (RMS)

0.0%

Stocks / Bonds / Cash

–

Target weights

–

How it works

Every simulated month, each asset class earns a random return drawn from its own risk/return profile (stocks: high mean, high volatility; bonds: moderate; cash: low, low volatility). As prices move, the winners grow to a larger share of the portfolio than intended — the account "drifts" away from its target mix. A robo-advisor watches that drift and decides when to trade back to target.

weight_i = value_i / Σvalue
IF policy = threshold:  trigger when |weight_i − target_i| > band
IF policy = calendar:   trigger every N months regardless of drift
on trigger: sell overweight, buy underweight → value_i = total·target_i
            cost = 0.05% × Σ|trade_i|

Risk tolerance — sets the target equity/bond/cash split a robo-advisor would assign; higher equity means higher expected growth but wider swings.
Threshold mode — rebalances only once an asset drifts outside its band, minimizing trading but letting weights wander further between corrections.
Calendar mode — rebalances on a fixed schedule regardless of how far weights have drifted, which can mean unnecessary trades in calm markets or too-slow reactions in volatile ones.
Drift band / frequency — the core dial real robo-advisors tune: tighter bands or shorter calendars track the target more closely but rack up more transaction costs over time.

Real-world relevance: this threshold-vs-calendar tradeoff is exactly the algorithm robo-advisors like automated brokerage accounts run continuously behind the scenes — the "buy & hold" comparison line shows what an investor gives up (or gains) by never rebalancing at all.

Stocks Bonds Cash Target band

Rebalanced

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