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Portfolio Analysis Tool

Free Tactical Allocation Backtester

Compare fixed-weight ETF portfolios using historical adjusted closes. Rebalance periodically to the same targets; this tool does not change allocations in response to market signals.

Real Historical Data
Multiple Rebalancing Options
100% Free

Portfolio Allocation

%
%
Total Allocation100%

Current Allocation

Configure Your Portfolio

Select your asset allocation, choose a backtest period, and click "Run Backtest" to see how your portfolio would have performed historically.

What Is Tactical Asset Allocation?

Tactical asset allocation is an active investment strategy that adjusts portfolio weights based on market conditions, economic outlook, or valuation metrics. Unlike strategic allocation (which maintains fixed weights), tactical allocation allows investors to overweight or underweight asset classes to capitalize on short-term opportunities or reduce risk during market stress.

This implementation tests fixed weights, not tactical signal rules. It requests a rolling 1, 3, 5 or 10 years ending today; only overlapping provider history is used and the actual dates are displayed. It cannot test a crisis outside that window. Presets are illustrative allocations, not verified fund models.

How to Use This Backtester

  1. 1

    Choose Your Assets

    Select from 14 major ETFs spanning stocks, bonds, commodities, and real estate. ETF exposures and available histories differ; overlapping holdings are not independent asset classes.

  2. 2

    Set Allocation Weights

    Assign percentage weights to each asset. Weights must sum to 100%. Presets are editable examples, not recommended allocations.

  3. 3

    Configure Rebalancing

    Choose how often to rebalance back to target weights: monthly, quarterly, annually, or never. Resets use the first available close after the interval from the previous rebalance month; costs and execution constraints are excluded.

  4. 4

    Run the Backtest

    Click "Run Backtest" to simulate your portfolio using real dividend-adjusted price data. View performance charts, risk metrics, and comparison to the SPY ETF benchmark over exactly the same dates.

Understanding Backtest Metrics

Total Return

The cumulative percentage gain or loss from start to end of the backtest period. Uses provider dividend-adjusted close ratios, a total-return proxy without a separate cash-dividend ledger.

CAGR

Compound Annual Growth Rate — the smoothed annual return that would produce the same total return if compounded each year. Better for comparing different time periods.

Max Drawdown

The largest peak-to-trough decline during the backtest. Measures observed adjusted-close declines in this sample; it excludes intraday losses and does not bound future losses.

Frequently Asked Questions

Does this test tactical allocation signals?

No. This implementation holds fixed target ETF weights and optionally rebalances back to them. It does not implement momentum, valuation or economic-signal rules that change target allocations. You can compare separately chosen fixed-weight portfolios.

What data and dates are used?

The tool requests FMP dividend-adjusted daily closes for selected positive-weight ETFs and SPY. Results use their overlapping dates, displayed above the chart. Missing SPY observations or gaps against its calendar within that interval reject the calculation. Zero-weight rows are excluded. Coverage may be shorter than the requested 1, 3, 5 or 10 years.

How does rebalancing work?

Monthly, quarterly and annual settings reset holdings at the first available close after 1, 3 or 12 calendar months from the previous rebalance month. Targets remain fixed. Fractional adjusted-price units are allowed; commissions, slippage, taxes and market-impact costs are excluded.

How are the metrics calculated?

CAGR uses elapsed calendar days divided by 365.25. Volatility is sample standard deviation of daily returns times sqrt(252). Sharpe uses mean daily excess return over a fixed assumed 2% annual risk-free rate, divided by daily sample deviation, times sqrt(252). The assumed rate is not a historical Treasury series. Zero-deviation Sharpe is unavailable.

Is drawdown a worst-case loss forecast?

No. Maximum drawdown is the largest observed decline from an earlier portfolio peak within this sample, measured at adjusted closes. It misses intraday losses and does not bound future losses.

Do the results include dividends?

The provider adjClose series accounts for dividends and splits. The simulation uses its ratios as an adjusted-price return proxy; it does not model separate cash dividend payment dates or tax treatment. Do not add dividends again to these returns. Data corrections and ETF history limits can affect the result.

Ready to Build Your Trading Strategy?

Describe your indicator or strategy rules to Pineify, review the generated Pine Script and test its assumptions in TradingView. This allocation simulation does not transfer holdings or execute portfolio rebalances.

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