A full-time income in the United States lands, very roughly, between $3,000 and $5,000 a month after tax, depending on where you live and what you do. That is the bar. "Making a living" is not a feeling, it is a number you can miss, and any honest conversation about automated trading as an income has to start by putting a real one on the table.
So here is the arithmetic: what the backtest produced, why an average is not a salary, and the three things that decide whether trading could ever pay your rent.
A monthly average is not a monthly paycheck. A system can average enough to live on and still hand you three losing months in a row. Income you can live on has to arrive when the bills do, and no backtest promises that it will.
The Algomyth engine is one of the two automated systems for NinjaTrader 8 sold here. It trades the micro Nasdaq once a day, at 9:30 AM ET, when the US cash market opens, with a stop and a target placed in the market at the instant of entry and the target set at three times the risk. It never holds a position overnight. Its published backtest runs day by day from January 2022 to September 2026 on a mid-size account at the Medium sizing level.
Over that period the simulation produced $87,359 net across 1,164 trades, an average of $18,814 a year. Net is the only version published: commissions of $1.90 per contract round turn and a tick of slippage come out inside the run, trade by trade. The deepest peak-to-trough fall along the way was $5,273.
Hypothetical performance. These figures come from a backtest of the system over historical data, not from a live account. Simulated results are prepared with hindsight, carry no financial risk, and cannot fully reflect real execution, slippage or liquidity. Past performance, real or simulated, does not guarantee future results.
Set $18,814 a year against a living wage and the honest picture is already visible: on one mid-size account at the Medium level, in simulation, this is a supplement, not a salary. It covers a car payment and the groceries, not a full-time income by itself. The complete breakdown of that figure, including every cost that comes off the top, is in how much a trading bot actually makes.
This is where most of the damage happens. The $18,814 is an average across four and three-quarter years, and no single year made exactly that, let alone any single month: some ran far above it, some made nothing, some lost money. A system whose target sits at three times its risk, and which therefore breaks even at a 25% hit rate, produces losing streaks as plain arithmetic, not a malfunction.
A salary is smooth. This is not. If you need a fixed sum in your account on the first of every month, a yearly average that arrives in lumps, sometimes as a loss, will not do that job on its own, however good the annual total looks. The gap between "averages enough" and "pays the bills on time" is the most underestimated fact in this subject, and a large part of why most traders lose even when the tool works exactly as designed.
An average tells you what a system did over years. A landlord asks what it did this month.
If one contract on one account is a supplement, the obvious move is to trade more. That is real, and also the fastest way to turn a working system into a loss. The sizing level is the lever, and the report publishes all three of them rather than one: Low, Medium and High.
Each step up moves everything at once. Going from Medium to High doubles the annual average from $18,814 to $37,629, and doubles the worst drawdown from $5,273 to $10,546. Profit and pain scale together, at the same speed, in the same direction.
| Sizing level (simulation, same edge) | Annual average, net | Worst drawdown of the period |
|---|---|---|
| Low | $9,407 | $2,637 |
| Medium | $18,814 | $5,273 |
| High | $37,629 | $10,546 |
Every row is the same edge at a different size, and each assumes you can sit through the drawdown in the right-hand column. Running several of your own funded accounts multiplies the result the same way, up or down, and the fees with it, as the guide to prop firm trading explains.
Change the account size, the sizing level and the commission rate, and see what the same backtest looks like against the figure you actually need.
There is one more number most income pitches leave out, and it is real cash. If you trade funded capital, you do not own the account, you rent the right to trade it by passing an evaluation, and evaluations cost money up front: roughly $100 for a 50k, $250 for a 100k, and $400 for a 250k.
You pay that whether the account goes on to make money or not. Funded accounts also have hard drawdown rules that close accounts, including ones a working system would have recovered, so you buy replacements, and the worst drawdown in the record, $5,273, is deeper than a typical 50k evaluation allows. In a flat six months you would pay those fees and receive nothing. It behaves like a salary running in the wrong direction, out of your pocket, on a schedule, earnings or no earnings.
Suppose the numbers work for you on paper. There is still the part no spreadsheet captures: whether you would actually leave the system running through a $5,273 drawdown, or through the larger one that comes with a bigger size. Most people who fail with a functioning system fail right there, switching it off in the middle of an ordinary losing stretch, which locks in the losses and forfeits the recovery the backtest depended on.
An automated system removes the temptation to meddle trade by trade, which is its real value. It does not remove the temptation to pull the plug at the worst possible moment, and that decision, which most often stands between a good backtest and a good outcome, is yours. The honest treatment of the downside is in risk, and the mechanics of the drawdown in what drawdown is.
Honestly: on one mid-size account at the Medium level, in simulation, an average of $18,814 a year is a supplement, not a living. To approach a full income you have to move up a size, add accounts or scale the system, which needs more capital, more evaluation fees up front, and the nerve to sit through a drawdown that grows as fast as the profit. It is possible in principle. It is never a salary, it is never smooth, and anyone selling it to you as either is not describing any real system.
The sober version is the useful one: start with a single account at the size the backtest used, prove you can live with the swings before you widen them, and read getting started before you fund anything. A system can make part of a living plausible; whether it makes a whole one is a question about your capital and your temperament, not the software.
Not on a single small account, and not as a smooth monthly income. The Algomyth engine backtest averages $18,814 a year net on one mid-size account at the Medium level, which is a supplement rather than a salary. Replacing a full income means a bigger size, more accounts or the second system alongside it, which requires more capital and a much larger drawdown tolerance, and even then the money arrives in lumps, not on a fixed payday. Treat it as variable business income, not a paycheck.
Less than people expect to begin, and more than they expect to do it comfortably. A single 50k evaluation costs roughly $100, plus platform and data costs and the system license, so the entry cost is modest; building toward a living means funding larger or multiple accounts and keeping enough cash in reserve to pay evaluation fees through flat stretches. There is a fuller breakdown in how much money you need.
No. It is a hypothetical average from a backtest over historical data on a mid-size account, and it includes losing months and flat months inside that average. Any individual year can land far above or far below it, and past performance, real or simulated, does not guarantee future results. Plan around the drawdown figure and the possibility of a barren quarter, not around the average.
Because the drawdown scales at the same rate as the profit. High doubles the annual average against Medium, from $18,814 to $37,629, and doubles the worst drawdown with it, from $5,273 to $10,546. A bigger size does not make the system safer, it enlarges both outcomes, so scale only after you have proven at a smaller one that you can sit through the swings.
They matter because they are cash you pay in advance regardless of results. In a strong stretch they are a rounding error against the profit, but in a flat or losing stretch you keep paying them and receive nothing, which is exactly when they hurt. Anyone modeling automated trading as an income has to subtract them on a schedule, the way a business subtracts rent, profitable month or not.
Everything we write comes back to one idea: verify, then decide. The live terminal exists for exactly that.
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