💼 Portfolio — Backtest Tab

Rebalancing Simulation · CAGR Comparison · India Tax Breakdown · Limitations

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Published: April 19, 2026  |  7 min read  |  Platform Guide  |  Portfolio

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See what rebalancing would have cost — and what it would have earned — on your actual portfolio

What You Will Master

The Backtest tab runs a historical rebalancing simulation on your actual portfolio holdings. It compares three strategies — buy-and-hold, threshold-triggered rebalancing, and quarterly rebalancing — and shows CAGR for each alongside a full India tax breakdown (LTCG/STCG per financial year). This lets you answer: would periodic rebalancing have improved my returns, and what would the tax cost have been?

What This Guide Covers:

  1. What the simulation actually models — the three strategy lines and what each represents
  2. All 5 input parameters — start date, threshold %, lot method, limited history, target weights
  3. Reading the NAV chart — the four output lines and the tax drag gap
  4. Summary and Tax Year Breakdown — CAGR comparison, LTCG/STCG, ₹1.25L exemption
  5. Rebalancing Events log — when each rebalance fired and why
  6. Key limitations — perfect execution, no costs, survivorship bias, simplified tax

Who This Is For:

  • Rebalancing researchers — investors deciding whether to rebalance and how often
  • Tax-aware investors — understanding the LTCG/STCG cost of rebalancing before committing to a strategy
  • FIFO vs HIFO evaluators — comparing lot selection methods on your specific trade history
What three strategies does the Backtest simulate?
1. Buy-and-Hold — no rebalancing, just track NAV as stocks drift from target weights. 2. Threshold Rebalancing — a rebalance fires at the next quarter-end when any stock deviates beyond the threshold %. Shown as both Gross-of-Tax and Net-of-Tax lines. 3. Quarterly Rebalancing — forced rebalance every quarter regardless of drift. Shown Net-of-Tax only.
What does the Threshold % parameter control?
It sets the drift tolerance before a rebalance triggers. At the default 5%, if any stock's actual weight deviates more than 5 percentage points from its target weight, a rebalance fires at the next quarter-end. Lower threshold = more frequent rebalancing. Higher threshold = fewer rebalances and less tax, but more drift allowed.
What is the difference between FIFO and HIFO lot methods?
FIFO (First In, First Out) sells your oldest lots first. Older lots are more likely to have been held over 12 months — qualifying for LTCG (13%) instead of STCG (20.8%). HIFO (Highest In, First Out) sells the lots where you paid the most, minimising the capital gain (and therefore tax) on each individual sale. Neither is universally better — compare both in the simulation on your actual trades.
What does the tax drag gap in the NAV chart show?
The Threshold Gross-of-Tax line shows what the rebalanced portfolio would be worth if taxes did not exist. The Threshold Net-of-Tax line shows actual NAV after each year's LTCG/STCG tax is paid. The gap between the two lines is the tax drag — how much of the rebalancing benefit was consumed by taxes over the simulation period.
What are the LTCG and STCG rates used in the simulation?
India post-July 2024 budget rates: STCG (Short-Term Capital Gains, held <12 months) = 20.8% (20% + 4% cess). LTCG (Long-Term Capital Gains, held ≥12 months) = 13% (12.5% + 4% cess). LTCG annual exemption = ₹1.25 lakh per India financial year. These are simplified estimates — consult a tax professional for actual tax planning.
What does "Limited History — Exclude" vs "Use Available" mean?
"Exclude" removes any stock that lacks Yahoo Finance price history going back to the start date. The remaining weights are renormalized to sum to 100%. "Use Available" includes those stocks from the earliest date their data exists — they enter the simulation later than others. "Exclude" gives a cleaner comparison; "Use Available" is more accurate if you hold many mid/small-cap stocks with limited history.
Why does the simulation freeze your lot history at the start date?
The simulation models how a rebalancing strategy would have performed given the stocks you held at that point. Trades made after the start date are not included — the simulation asks: "if I had started rebalancing on this date with these holdings, what would have happened?" Adding future trades would conflate the rebalancing strategy with new capital deployment decisions.
What is survivorship bias in this context?
Survivorship bias here means the simulation only includes stocks you currently hold — implicitly, stocks that survived (you didn't sell them after major losses). Stocks you sold and removed from your portfolio are not in the backtest. This can make the buy-and-hold line look better than it would have been in real time, since it only includes your "survivors."

What the Backtest Actually Models

The Backtest tab is a rebalancing simulation — not a free-form historical return lookup. It takes your actual holdings and trade history, freezes them at a chosen start date, then replays history to compare three portfolio management strategies side by side.

Strategy How It Works Lines in Chart
Buy-and-Hold No rebalancing. Portfolio drifts freely from target weights as prices move. 1 line (net = gross, no tax events)
Threshold Rebalancing A rebalance fires at the next quarter-end when any stock deviates beyond the threshold % from its target weight. 2 lines — Gross-of-Tax and Net-of-Tax
Quarterly Rebalancing Fixed rebalance every quarter-end (March, June, September, December) regardless of drift. 1 line (net of tax only)

All four lines start from a base NAV of ₹1,000 — so the chart shows relative performance of each strategy, not absolute rupee returns. Price data comes from Yahoo Finance monthly closing prices.

The simulation uses your real trade history. Target weights you enter are the "ideal" allocation you want to maintain. The simulation sells overweight stocks and buys underweight ones at each rebalance event — using the lot method you choose (FIFO or HIFO) to determine which specific lots are sold and what tax they trigger.

Input Parameters Explained

Start Date

Presets: Inception (your first ever trade), Last 1Y / 2Y / 3Y, or a Custom month and year. Your lot history is frozen at this date — only trades recorded before the start date enter the simulation. Trades made after the start date are ignored.

Start from Inception for the most complete picture. For a shorter simulation, use Last 3Y — enough history to see multiple market cycles while staying within well-covered Yahoo Finance data.

Threshold %

Default 5%, range 1–20%, step 0.5%. This is the drift tolerance for the Threshold Rebalancing strategy. A stock with a 20% target weight triggers a rebalance when its actual weight rises above 25% or falls below 15% — and the rebalance fires at the next quarter-end (March, June, September, or December).

ThresholdEffectBest For
2–3%Very frequent rebalancing — high tax, tight drift controlConcentrated portfolios where position sizing is critical
5% (default)Moderate frequency — quarterly at most during trending marketsMost diversified portfolios
8–10%Infrequent — only rebalances after large movesLong-horizon investors wanting to minimize tax events

Lot Method

Controls which lots are sold first during each rebalancing event:

Limited History

When a stock in your portfolio lacks Yahoo Finance price data going back to the start date:

Target Weights

Enter your ideal allocation % for each stock in the table. Total must equal 100%. Set a stock to 0% to exclude it completely from the simulation. Click ↺ Reset to current to prefill from your actual portfolio's current allocation percentages as a starting point.

Target weights are the simulation's ideal state, not a recommendation. The simulation rebalances toward whatever weights you enter. If you enter equal weights (e.g. 5% each for 20 stocks), the simulation tests an equal-weight strategy — not necessarily what you should do with your portfolio.

Reading the Output

NAV Chart (Base ₹1,000)

The chart plots four lines over the simulation period, all starting from ₹1,000:

Line What It Shows CAGR Label
Buy-and-Hold Portfolio NAV with no rebalancing. Stocks drift freely. Hold CAGR
Threshold (Gross) Threshold rebalancing NAV before tax payments Threshold Gross CAGR
Threshold (Net) Threshold rebalancing NAV after India LTCG/STCG tax Threshold Net CAGR
Quarterly (Net) Forced quarterly rebalancing NAV after tax Quarterly Net CAGR

The gap between Threshold Gross and Threshold Net is the tax drag — the percentage of the rebalancing benefit consumed by LTCG and STCG payments. A wide gap suggests that rebalancing this particular portfolio has significant tax costs; a narrow gap means the rebalancing mostly triggered LTCG (lower rate) or stayed within the ₹1.25L annual exemption.

Summary Card

Below the chart, the Summary shows CAGR for all four lines, total tax paid under Threshold and Quarterly scenarios, and the tax drag %. It also shows how many rebalancing events fired in each scenario and how many stocks were excluded due to limited history.

Tax Year Breakdown (Threshold scenario)

A table showing each India financial year (Apr–Mar) with:

Use the tax breakdown to time your rebalancing. If a year shows large STCG (held <12 months), consider waiting until those lots cross the 12-month mark before rebalancing — the same gain is taxed at 13% instead of 20.8%. The simulation shows the historical cost; use it to inform your real-world rebalancing timing.

Rebalancing Events Log

A timeline of every rebalance that fired in the simulation — the date, which stocks were overweight/underweight, and the direction of each trade. This log shows how frequently the threshold triggered and whether rebalancing was concentrated in specific market periods.

Key Limitations — Read Before Acting on Results

Simulated performance is not actual performance. The Backtest shows what would have happened under simplified assumptions. Real returns will differ due to costs, execution constraints, and taxes not fully captured by the model.

Perfect Execution at Month-End Prices

The simulation assumes every rebalancing trade executes at the month-end closing price with zero slippage. In reality, large rebalancing trades in mid- and small-cap stocks move the price against you — the actual execution price will be worse than the month-end close used in the simulation.

No Brokerage, STT, or Transaction Costs

Zero brokerage, Securities Transaction Tax (STT), exchange fees, or capital gains tax impact on trade timing are modelled. Frequent rebalancing at a 2–3% threshold in a real portfolio would incur material transaction costs that would reduce the net-of-tax CAGR shown in the simulation.

Survivorship Bias

The simulation only includes stocks currently in your portfolio — stocks you sold after losses are not present. This means the buy-and-hold line only shows the performance of your "survivors" — not the full history including stocks you exited. The buy-and-hold line may look better than it would have in real time.

Simplified India Tax Model

The tax model uses post-July 2024 rates (LTCG 13%, STCG 20.8%, ₹1.25L annual exemption). It does not model:

Use the Backtest for directional insight, not tax planning. The simulation answers "would rebalancing have helped?" — it is not a substitute for advice from a qualified CA or SEBI-registered investment adviser for actual tax and portfolio decisions.

Yahoo Finance Data Quality

Price history comes from Yahoo Finance monthly closing prices. Data gaps, corporate action adjustments, or symbol changes can affect results for specific stocks — particularly older mid-cap holdings. Stocks with insufficient history are excluded or truncated based on your Limited History setting.

3 Practical Use Cases

Use Case 1 — Should I rebalance at all?

Run the simulation with your actual target weights from Inception. Compare the Buy-and-Hold CAGR against Threshold Net CAGR. If buy-and-hold wins, your winners are your best performers — rebalancing would have trimmed them and bought weaker stocks. If threshold rebalancing wins, periodic trimming would have added value. Let the data from your specific holdings answer the question, not generic theory.

Use Case 2 — FIFO vs HIFO on your specific trades

Run the simulation twice — once with FIFO and once with HIFO, same start date and weights. Compare Total Tax Paid in the Summary. For portfolios where most trades are old (many LTCG-eligible lots), FIFO often produces less STCG. For portfolios with many recent purchases at different prices, HIFO can reduce total gains more efficiently. The answer depends on your specific lot history.

Use Case 3 — Choosing a threshold frequency

Run three times: Threshold 3%, 5%, and 10%. Compare Threshold Net CAGR and Total Tax Paid across runs. A tighter threshold produces more rebalances — if the incremental CAGR improvement does not compensate for the higher tax bill, a looser threshold is better for your specific portfolio.

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