Down 50% Needs a 100% Gain to Break Even. The Asymmetric Math of Losses
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4 min read
Say your portfolio drops 30% in a bad month. Thirty percent down, so a 30% gain gets you back to even, right? It does not. You would need a 43% gain just to get back to where you started, not 30%. The bigger the loss, the wider that gap gets, and by the time a loss reaches 50%, it takes a full 100% gain, a double, just to break even.
The reason is simple once you see it: a loss shrinks the amount of money that has to do the recovering. If Rp10,000,000 falls 30%, you are left with Rp7,000,000. To get back to Rp10,000,000, that smaller Rp7,000,000 has to grow by Rp3,000,000, and Rp3,000,000 is 42.9% of Rp7,000,000, not 30%.
Gain needed to break even = Loss ÷ (1 − Loss)
Here is that formula run across a range of real loss sizes.
| Loss | Gain needed to break even |
|---|---|
| 10% | 11.1% |
| 20% | 25.0% |
| 25% | 33.3% |
| 30% | 42.9% |
| 40% | 66.7% |
| 50% | 100% |
| 70% | 233.3% |
| 90% | 900% |
Notice how the gap barely matters at small losses and then explodes. A 10% loss only needs an 11.1% gain, close enough to ignore. A 70% loss needs a 233.3% gain, nearly impossible within a normal investing time frame. This is why avoiding a large drawdown protects a portfolio more than chasing a large gain does: the math of getting back to even gets harder, not proportionally, but exponentially, as the loss grows.
GoTo Gojek Tokopedia (GOTO) started 2026 trading around Rp69 a share. By early May 2026, after the government capped online motorcycle-taxi commissions at 8%, the stock fell to Rp50, the exchange's minimum trading price (known locally as "gocap"), a 27.54% decline, and it was still sitting at that Rp50 floor as of early August 2026, a stretch retail investors have nicknamed the "kutukan gocap" (the gocap curse), according to Klik Anggaran and Kompas.id. A 27.5% loss is not extreme by market standards, but recovering it from Rp50 still requires a 38% gain, back to that same Rp69, which the stock has not managed in over three months.
IHSG, Indonesia's benchmark stock index, closed 2025 at 8,646.94 (30 December 2025, Tempo/Infobanknews), then fell to a 2026 low of 5,342 by 8 June 2026 amid a rupiah crisis and Bank Indonesia rate hikes, a 38.2% decline. Getting fully back to 8,646.94 from that low needs a 61.9% gain, not 38.2%. As of 11 August 2026 the index has climbed back to around 6,383 (CNBC Indonesia), which sounds like real progress and is, but it is only about 19.5% of the way up from the low. Reaching the old high still needs roughly another 35% gain from here, months or years away at typical market growth rates, even though the original drop took only about five months.
Both examples land in the same place: the loss and the recovery are never the same number, and the larger the loss, the further apart they get. That is the real argument for spreading risk across assets rather than concentrating in one stock, and for paying attention to how large your portfolio's worst drawdowns have actually been, not just its best-year returns. A portfolio that avoids a 50% loss and instead only ever loses 20% at its worst needs a 25% recovery gain, not a 100% one, to get back to even. That difference compounds into a much smaller amount of time spent underwater.
You can see your own worst drawdowns, not just your current balance, on your Portfolio Health view on your NetWort dashboard. A single position that has fallen 40% or 50% needs a much bigger recovery gain than the headline percentage suggests, and knowing that number changes whether holding on and waiting for "even" is actually a reasonable plan. NetWort's Market page tracks IHSG and IDX sentiment alongside the kind of index-level swings covered in the example above, useful context before judging whether a single stock's drawdown is normal for the market or unusual to that stock.
This same asymmetry is part of why an investment's average annual return and its actual compounded result can tell two different stories, covered in why arithmetic and geometric returns diverge under volatility: both come down to the same fact, that losses and volatility cost more than a simple average suggests.