Can I Trade for a Living? · Reality Check Simulator

This app does not ask “how rich could this get?” first.

It asks whether your capital, runway, time budget, research skill, operating discipline, and spending needs line up well enough for the pursuit to remain rational once drawdowns, taxes, friction, and bad market regimes show up.

The engine intentionally leans conservative. It models path dependency, strategy decay, operating drag, and the ugly fact that needing to pull cash out of a fragile trading program is usually the part that breaks it.

It also shows the calm counterfactual: put the same money into a low-cost ETF, add to it on schedule, and let compounding do its work without the stress of monitoring, slippage, and execution failures.

Use it as a survivability simulator. If the answer is “not yet,” the output should tell you what is missing first: more time, more capital, lower spending, stronger process, or less confidence.

Profile presets

Start from a realistic archetype

Presets set conservative values you can edit.

These are not outcome promises. They simply save time by loading a plausible starting profile for a careful builder, a stretched dreamer, or a genuinely disciplined operator.

Household pressure

Living costs and fallback income

If spending is rigid, trading needs more runway.

This block determines how hard the household pulls cash out of the trading effort. A strategy can be decent on paper and still fail once actual bills arrive every month.

Emergency fund outside trading capital currency

Decision horizon years

Capital and process

Money, time, and execution quality

The model rewards runway and punished fragility.

Retail traders usually underrate operating reality. Strategy quality, implementation quality, and available time are separate things. The app scores them separately and lets the weak link dominate.

Research and coding skill 1-10

Operational readiness 1-10

Discipline under stress 1-10

Strategy realism

Edge, costs, and pain tolerance

The defaults are intentionally unromantic.

Enter assumptions you can defend. The simulator already compresses edge, taxes positive months, and injects breakdown risk. If your base case is still heroic, the recommendation will tell you so.

18%

Run model

Simulate the next stretch

More paths smooth the estimate, not the life.

The engine runs monthly regime sampling, fat-tailed returns, behavior penalties, and cash-flow pressure. It then scores whether the profile is mainly suitable for side hustle, part-time, or full-time use.

Monte Carlo paths count

Current stance: a salary-supported side hustle with moderate skill, meaningful friction, and no free pass on drawdowns.

After each run, scan the five headline cards below first: viability, cost coverage, ruin risk, median ending wealth, and behavior-driven stop probability.

Mode comparison

How the same profile behaves under more pressure

These scores rerun the same profile with typical pressure levels for side hustle, part-time, and full-time cash extraction.

Side hustle

Run the model to compare.

Part-time

Run the model to compare.

Full-time

Run the model to compare.

Liquid wealth paths

10th, 25th, median, 75th, and 90th percentiles over time.

Median wealth path plus 25–75% and 10–90% bands over time.

median wealth

25%-75% band

10%-90% band

Ending wealth distribution

Histogram of total liquid wealth at the horizon.

A wide left tail is the whole point.

wealth bins

median marker

Recommendation

Run the model to generate a recommendation.

The recommendation panel turns the simulation into a practical reading: what looks viable, what does not, and what is most likely to break first.

Passive benchmark

Run the model to compare the trading path with a low-cost ETF plan.

The passive benchmark assumes monthly dollar-cost averaging into a broad index ETF such as SPY, with no slippage, no webhook delays, and no daily operational burden.

Starting investable cash

Monthly ETF contribution

Illustrative ending wealth

Trading median gap

Illustrative long-term tax rate

The point is not to optimize excitement. It is to compare the trading workflow against the calmest plausible alternative.

Dominant bottlenecks

These are the constraints the simulator believes are currently doing the most damage to survivability and rationality.

Run the model.
The bottleneck list will update.
That is where improvement should start.

Model assumptions

The engine stays deliberately simple, but it does not assume a smooth compounding fantasy. These assumptions are built into every run.

Monthly returns are fat-tailed and regime-dependent rather than neat normal draws.
Positive net trading income is taxed on an annual, aggregate basis; costs and tooling drag reduce the realized edge.
Drawdowns worsen behavior risk and can trigger strategy abandonment.
Higher time availability and better operations improve effective edge only gradually.
Full-time pressure is modeled mainly through recurring cash extraction from a finite reserve.