i What this calculator does
Market timing fails for a specific reason: the best days cluster inside the worst periods, so anyone who sells into a panic is usually out of the market when the biggest rebounds happen. This calculator shows the cost. Enter a starting amount, a horizon, the return and volatility you expect, and how many of the best days you miss, and it compares the fully invested result with the result after those days are removed.
The simulation uses volatility regimes so that large moves cluster the way they do in real markets, is deterministic (the same inputs always give the same path), and sits next to the published S&P 500 figures for 2003 to 2022, so you can see that the pattern is not an artefact of the model. It pairs with the rand cost averaging calculator, which models the alternative of never trying to time anything.
This calculator is for educational purposes only. Results are estimates and may vary depending on market conditions, spreads, commissions, platform settings, and exchange rates. It should not be considered financial advice.
How the simulation works
The calculator draws a daily return for every trading day in your horizon from a log-normal distribution with the annual return and volatility you enter, switching between a calm and a stressed volatility regime so that large moves cluster, and using a fixed seed so that the same inputs always produce the same path. It then compounds every day for the fully invested result, removes the largest N daily gains and compounds again for the missed-days result. Because the days removed are the largest gains in the path, the gap between the two results is the cost of being out of the market on exactly the days that did the most work.
What the published figures show
The simulation is illustrative; the history is not. J.P. Morgan Asset Management's Guide to Retirement 2023 tracks $10,000 in the S&P 500 from January 2003 to December 2022: fully invested it grew at 9.8% a year; missing the 10 best days cut that to 5.6%; missing the 30 best days left 0.9%; missing 40 or more turned it negative. Seven of the ten best days in that twenty-year window fell within two weeks of one of the ten worst days. The same clustering appears in the simulation because large moves cluster in volatile periods whatever the market.
What it means for a trader
For a long-term investor the lesson is simple: the cost of being wrong about an exit is much larger than it looks, and a stop-loss on an index position is a bet against this pattern. For an active trader the lesson is different. Short-term strategies are out of the market most of the time by design, so they give up the best days and avoid the worst ones in roughly equal measure; what they live on is the edge in between, which the trading edge calculator measures. Mixing the two mindsets, trading an index position in and out on news, is where most of the damage happens.
Spotted an outdated figure? If a rate, limit or formula in this calculator no longer matches its source, email us the page and the source. A material correction is dated on the Updates Log.
Frequently asked questions
Why does the result change when I pick a different path?
Each path is a different random draw with the same return and volatility. The exact numbers move, but the cost of missing the best days is large in every path, which is the point: it is a property of volatile markets, not of one lucky history.
Is this the same as the J.P. Morgan study?
No. The published figures are historical S&P 500 total returns for 2003 to 2022 and are shown for reference. The simulation lets you change the return, the volatility and the horizon, which history cannot.
Why do the best days cluster around the worst ones?
Volatility clusters. In a panic, daily moves of 5% to 10% happen in both directions within days of each other. The biggest up-days of 2008 and March 2020 all fell inside the crash, so an investor who sold after the worst days was almost always out for the best ones.
Does missing the worst days help as much as missing the best days hurts?
Yes, by a similar amount, and that is the trap: to miss the worst days you would have to sell before them, and since the two kinds of day sit together you would miss the best ones too. Nobody has shown an ability to do one without the other.
Why is the default volatility 18%?
A broad equity index moves about 1% a day on average, which annualises to about 16% to 18%. The JSE All Share and the S&P 500 have both sat in that range over the last twenty years; single shares and crypto are far higher.
Does this argue against all active trading?
It argues against trading an investment. A deliberate short-term strategy accepts missing the best days as the cost of also missing the worst, and is judged on its edge per trade, not on time in the market.
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