Most people will not read this page. They will download the strategy, get surprised by normal behavior, and quit at the worst moment. The data below is how you avoid being most people.

All five risk models are one strategy at five different risk levels. The trades are identical, governed by the same rules: a maximum of two trades a day, stopping after the first daily win. What changes is position size, and with it both the profit and the drawdown.

A risk model is the dollar amount you risk per trade. It is the one setting you choose:

The strategy divides your dollar amount by what the stop costs on one contract. A tighter stop means more contracts; a wider stop means fewer.

Built-in risk filters do the rest: the strategy will not take a trade that risks more than $400 per contract, on any model. The limit is locked in the code; it is not an adjustable setting. It is the maximum planned risk at entry, not a maximum possible loss: an actual loss can exceed it when a fill or a gap lands past the stop. What it protects, and what it costs, has its own section further down the page.

There is also a floor: when a setup is valid, the strategy always trades at least one contract. On the $200 and $300 models, a wide stop can make that single contract cost more than the risk per trade you set. The example below shows how, and the $400-per-contract limit is the ceiling.

The $200 model, worked through

stop costs $100
per contract2 contracts · $200 at risk

stop costs $300
per contract1 contract · $300 at risk

stop costs $400
per contract1 contract · $400 at risk

stop costs
more than $400
per contracttrade skipped

So far, every stop in the record has stayed under the $400 limit. That is why the $200 and $300 models share the same largest single loss, $381. From the $400 model up, losses track the setting: the $400 model's largest single loss was $410.

Even though the $200 and $300 models can lose more than their set risk per trade on a single trade, they still produce the lowest overall drawdown. That lower drawdown is essential for smaller accounts and for prop firm accounts still in the early trailing drawdown phase, where every dollar of buffer matters.

Higher risk models increase both return potential and drawdown. There is no optimal setting, only alignment with your account size, risk tolerance, and prop firm rules.

Why these five models. The models are position sizes, not tuned parameters. The strategy logic is identical on every one; the only thing that changes is how many contracts a given stop allows. The risk is set in dollars rather than a fixed number of contracts because dollars keep the risk consistent. With fixed contracts, the same position risks $100 on a tight stop one day and $400 on a wide stop the next; the exposure swings with the market. A fixed dollar amount sizes each trade to its stop, so every trade carries roughly the same risk, whatever the volatility. $200 is the smallest model because of the one-contract floor: below it, the floor keeps the risk and gives away the return. And $800 is the largest model we publish because the largest common prop accounts, 250K, carry a trailing drawdown around $6,500: the $800 model's worst historical drawdown of -$5,374 is the most we would run against that limit and still leave real room. You can size above it. We would not.

You are also free to test any value in between, free, in NinjaTrader. You will find settings that backtest slightly better than the published models, and neighbors that backtest slightly worse. That is contract rounding and sequence luck, not a better strategy.

This is backtested data, not a live track record.

The risk framework at the end of the dashboard sizes each model against account balances and prop firm drawdown limits, and the Trade Management System on the Strategy page explains the sizing in full.

Clara Core:
MNQ backtest ·
May 2019 – September 2026May 2019 – Sept 2026

Each tab is a risk-per-trade model.
Max 2 trades per day, and it stops after the first daily win.

Equity curve:
monthly cumulative P&L · 89 months

Month P&L

Cumulative

Year

P&L

Max DD

Trades

Win%

The account's running total, month by month, from $0 at the start of the record. Green marks a month that ended at a new equity high; a soft orange background marks a month that ended inside a drawdown, below a previous peak. This is the equity curve in numbers: every drawdown arriving, and every recovery. Month-end balances never show a drawdown's full depth: the deepest point happens intraday, between month ends. The boxed month can even finish green at a new high, as it does on the $300 model, where the May 1, 2020 low and the recovery that followed landed inside the same month.

Performance varies across months, sometimes significantly. Short-term variation is normal. The strategy is designed to perform over long periods, not individual months.

Quieter months are a useful time to get infrastructure in place: setting up prop firm accounts, understanding evaluation and funded-account rules, and getting NinjaTrader and the strategy installed, so that when a stronger month arrives you are ready rather than still working through setup.

Each cell is the deepest drawdown measured inside that calendar month. The full-period max drawdown is deeper than any single month because drawdown windows cross month boundaries: on the $300 model, the -$1,811 ran from an August 7 peak to a September 30 low in 2026.

Trade loss distribution ·
456 losing trades

Avg loss

Largest loss

Trade win distribution ·
1,112 winning trades

Avg win

Largest win

Avg P&L/trade

Trade distributions: these count individual trades. Avg P&L per trade is every trade averaged together, winners and losers. It is the number that decides whether the strategy makes money over time, and it is where a high win rate carrying larger losses either survives or does not.

Daily loss distribution ·
374 losing days

Avg losing day

Worst day

Daily win distribution ·
952 winning days

Avg winning day

Best day

Daily distributions: these count days, not trades. A worst day can include two losses: on the $300 model it was -$309 and -$310 on the same day.

Losing streak distribution ·
374 losing days

Avg streak

Longest

Winning streak distribution ·
952 winning days

Avg streak

Longest

Streaks are counted on traded days: consecutive trading days finishing positive or negative. Days without a trade neither break nor extend a streak: a 14-day winning streak is 14 traded days in a row, not 14 calendar days.

Trade behavior

Daily trade limits

Max trades per day2

Avg trade duration1H 58M

Trade frequency

% of 1-trade days81.7%

% of 2-trade days18.3%

When 2 trades occur

Lose 1st → Win 2nd79.8%

Lose both20.2%

When the first trade is a loss, the second trade won 79.8% of the time.

Monte Carlo drawdown simulation

Actual backtest → what happened. Monte Carlo → what can happen.
What happened The deepest drawdown in the actual backtest.
50th percentile Half the shuffled runs drew down less, half drew down more.
5th percentile 5% of runs drew down deeper.

Based on 10,000 shuffled simulations

ActualWhat happened

Median50th percentile

Downside5th percentile

Total Full Period Profit

Methodology

Monte Carlo analysis performed using 10,000 randomized simulations of the strategy's 1,568 historical trades (May 2019 – September 2026).

Each simulation randomly reorders the same trades and calculates the resulting maximum drawdown. This illustrates how trade sequence affects drawdown risk when trade outcomes remain constant.

Same trades. Same total profit.
Different order. Different drawdown.

Results represent statistical analysis of historical data and do not predict future performance.

Why it matters

It helps answer: if the order of my trades were different, or if I hit a concentrated streak of losses, would I still be profitable, and would the account survive it?

Important context

The strategy executes with consistent rules: same instrument, same session, same entry model, same risk per trade. It trades near the open rather than at a different hour each day, so conditions are broadly comparable across the record. Even so, consistent systems still vary depending on how wins and losses are distributed over time, changing market conditions, and macroeconomic events.

This analysis does not change the strategy: it uses the same trades in a different order.

This is a tool for risk awareness,
not prediction.

There is no single correct approach. The appropriate model depends on how you prioritize capital preservation versus growth, and how your account is structured.

All configurations and guidelines on this site are based on this historical backtested data.

Markets evolve. Performance will vary over time due to changing conditions, volatility, and broader market environments. There are no guarantees. All results shown are backtested and provided for transparency, not prediction.

You are responsible for your own trading decisions, risk management, and how you choose to apply the strategy.

Why the median drawdown

The framework sizes accounts to the median simulated drawdown rather than the actual backtest. The actual drawdown is a single run of history. The median sits above it, and sizing to the higher number leaves a buffer for a future that will not replay the past exactly: trade order can differ, and so can what stops cost. The 5th percentile, the simulated downside, is the same idea, more conservative: a planning figure, not the worst that can happen. The true worst case is unknowable. The three approaches below show where each number fits.

ONE WAY TO STRUCTURE CAPITAL

Different risk profiles can be applied depending on the role of each account within a portfolio. This is shared as an example of structured implementation, not a recommendation.

Cash & Retirement Accounts
(Downside-Case Drawdown)

Starting Capital: $5,000 and up ·
Risk per Trade: $300
Simulated downside drawdown, the 5th percentile, around -$3,860. Holding account capital above that figure with a buffer on top sizes the model for slow growth behind a buffer rather than short-term performance.

Cash & Prop Accounts
(Median Drawdown)

Starting Capital: $2,500–$5,000 ·
Risk per Trade: $200 / $300 / $400
Most accounts are structured around the median drawdown. Objective: consistent performance with controlled risk.

Higher-Risk Allocation,
Prop Only (Actual Drawdown)

10%–20% of total portfolio ·
Risk per Trade: $600
Starting Capital: $2,000–$2,500 on 50K accounts & $4,000 on 150K accounts. Objective: improve capital efficiency while keeping total portfolio risk controlled.

In some cases, a single account within the portfolio runs at $600 risk on a 50K account, fully aware of the higher probability of drawdown limits being reached. This is a deliberate allocation decision, not a recommendation.

CHOOSING THE ACCOUNT:
PROP FIRM OR CASH

A prop firm account risks the evaluation fee, $85 to $200, for $2,000 to $2,500 of drawdown room. A cash account risks every dollar in it. That difference is why the profiles above lean on prop firm accounts for the higher-risk models and reserve cash and retirement accounts for the conservative sizing.

If you go with a prop firm account, check how its trailing drawdown is measured before you buy it. An end-of-day rule moves the limit once per day, on the closing balance. An intraday rule moves the limit on the highest point an open trade touches. We suggest end of day over intraday; regardless of the strategy you run, it is the better option. How prop firms measure drawdown is covered in detail on the Structure page.

RISK SCALING APPROACH

As accounts grow and build a buffer, risk per trade can be increased gradually.

Capital protection stays first; added exposure comes second.

Risk is not increased to chase returns; it rises only as the account's buffer supports it.

The strategy remains the same. Only the risk allocation changes.

OUR ROLE

Clear data · A structure for execution · A framework for your decisions, sized to your own risk tolerance.

Transparency is the foundation. Understanding the strategy matters more than selling it.
Your financial well-being
always comes first.

The dashboard above is the record. Everything below is the deep dive: what the risk limit costs, how drawdown is measured, and the questions the numbers raise, answered one by one.

Quarter	Trades	Net	Worst drawdown	What we changed
Q1 2026	55	+$2,400	-$845	Nothing
Q2 2026	56	+$1,624	-$852	Nothing
Q3 2026	55	-$971	-$1,811	Nothing

Through	Net profit	Max drawdown	Win rate	Profit factor	Trades
2019	+$821	-$943	64.71%	1.45	34
2019–2020	+$4,193	-$1,406	66.01%	1.25	253
2019–2021	+$12,393	-$1,406	69.81%	1.46	467
2019–2022	+$19,714	-$1,406	69.66%	1.46	712
2019–2023	+$27,774	-$1,406	69.96%	1.51	942
2019–2024	+$37,062	-$1,406	70.73%	1.56	1,165
2019–2025	+$47,677	-$1,406	71.33%	1.61	1,402
2019–2026	+$50,730	-$1,811	70.92%	1.56	1,568

How it is measured	Worst drawdown	Who this is for
End-of-day balance only	-$1,651.90	An account whose limit trails on the daily close
Closed trades, trade by trade	-$1,651.90	What NinjaTrader's own summary reports
Including the dip while a trade is open	-$1,810.50	What we publish in the dashboard and every headline figure

Year ($300 model)	Deepest drawdown from peak	Longest peak-to-recovery
2019 (May–Dec)	-$943	36 days
2020	-$1,406	188 days
2021	-$1,162	46 days
2022	-$1,072	64 days
2023	-$1,158	35 days
2024	-$1,152	63 days
2025	-$957	42 days
2026 (Jan–Sep)	-$1,811	54 days, still open

The Give-Back

Clara Core has no fixed take profit. Trades can close on a trailing stop, a breakeven move in slight profit, or the daily session close, so no trade is ever closed at its best point. The gap between a trade's highest point and where it finally closed is the give-back. NinjaTrader records the give-back value as End Trade Drawdown, the ETD column in the exported CSV file.

A strategy with a fixed target does not have a big give-back. If the target is $100, you can expect $100 minus fees, and the give-back is close to zero. We made the opposite choice deliberately. Letting trades run is where the large winners come from, and the same choice helps produce the lower drawdown and the higher win rate the backtest shows. The cost is that every trade hands something back on the way out.

The give-back matters most on an intraday-trailing prop account: when a trade makes a new high, the limit moves up with it, so every dollar handed back is room consumed. An end-of-day account never sees it. We suggest end of day over intraday. How prop firms measure drawdown is covered in detail on the Structure page.

The table below takes the single worst give-back in each year: the highest point the trade reached, where it finally closed, and the difference between the two. That difference is the give-back. Across all 1,568 trades the average give-back was about $136 and the median about $99.

2019 covers May onward and 2026 covers January through September. 2019 is the only year whose worst case still closed green: it reached +$465 and kept +$111.30. The other seven went briefly green, between +$48 and +$201, gave all of it back, and closed red on a stop. All eight exited on a stop, none on the daily close.

A trade that touches +$160 and closes red is not a malfunction. Exits adapt to conditions: some trades trail tight and keep nearly everything, others are given room and hand most of it back. No single trade is meant to look perfect. Across 1,568 trades, that mix is what produces the low drawdown and the win rate that carries the edge.

$300 model · worst give-back in each year

Year	Reached	Closed at	Given back	Year average
2019	+$465.00	+$111.30	$353.70	$169.30
2020	+$48.00	-$325.90	$373.90	$142.32
2021	+$134.00	-$290.80	$424.80	$124.55
2022	+$124.50	-$381.40	$505.90	$130.14
2023	+$125.00	-$302.80	$427.80	$138.77
2024	+$142.00	-$283.80	$425.80	$143.93
2025	+$116.50	-$346.90	$463.40	$131.60
2026	+$200.50	-$217.90	$418.40	$140.05

One thing to know about these figures. NinjaTrader's End Trade Drawdown compares a gross high against a net close, so the trade's commission sits inside the give-back. On the 2019 trade, $5.70 of the $353.70 is commission and the price give-back alone was $348.00. We publish the exported figure unmodified rather than adjusting it, so that what you see here matches what you get when you open the file yourself.

How the exits work →

Risk Awareness &
Drawdown Impact On Account Size

The tables below show how to look at risk and its impact on an account, each from a different angle. The goal is awareness of what risk looked like over time.

Risk At Account Size

The same drawdown feels completely different depending on the type of account and the account balance. A 50K prop firm account costs $85 to $200, and its true size is its available drawdown, $2,000 to $2,500 depending on the firm. In simple terms: on that account the real risk is the $85 to $200 it cost to open. Fund a cash account with $2,000 and the real risk is the full $2,000. Lowering risk on a cash account means having a bigger account balance. The table below runs account balances from $2,000 to $100,000 against three max drawdown figures: the actual backtest at -$1,811, the Monte Carlo median at -$2,597, and the Monte Carlo 5th percentile, the simulated downside, at -$3,860. Each line shows what each drawdown would be as a percentage of that account balance. This is not meant to scare you off; it is to bring awareness to how you need to think about risk when choosing the account size you run.

Your account	Historical -$1,811	MC median -$2,597	MC downside case -$3,860
$2,000	90.5%	over the account	over the account
$2,500	72.4%	over the account	over the account
$5,000	36.2%	51.9%	77.2%
$7,500	24.1%	34.6%	51.5%
$10,000	18.1%	26.0%	38.6%
$12,500	14.5%	20.8%	30.9%
$15,000	12.1%	17.3%	25.7%
$17,500	10.3%	14.8%	22.1%
$20,000	9.1%	13.0%	19.3%
$25,000	7.2%	10.4%	15.4%
$30,000	6.0%	8.7%	12.9%
$35,000	5.2%	7.4%	11.0%
$40,000	4.5%	6.5%	9.7%
$45,000	4.0%	5.8%	8.6%
$50,000	3.6%	5.2%	7.7%
$60,000	3.0%	4.3%	6.4%
$70,000	2.6%	3.7%	5.5%
$80,000	2.3%	3.2%	4.8%
$90,000	2.0%	2.9%	4.3%
$100,000	1.8%	2.6%	3.9%

The Journey, Level By Level

This table replays the backtest on a $2,000 account running the $300 model, from May 2019 to September 2026. It shows when the account reached each balance, and what the worst drawdown from that point felt like as a percentage of the account.

The safer way to run this is using prop firm accounts, where the $2,000 to $2,500 of drawdown room costs $85 to $200 to replace, or a cash account funded at $5,000 and up, depending on your risk tolerance. On prop firm accounts, pick one whose drawdown is measured on the end-of-day balance rather than intraday. Scaling is the same idea, over time stepping up the risk model as equity grows. The published models, $200 through $800, are that staircase. None of this is a recommendation; it is what the numbers say about account size and the impact of its max drawdown over the seven years.

Balance reached	When	Worst drawdown	Felt as
$2,000+	May 2019	-$249	12.4%
$2,500+	May 2019	-$1,406	56.2%
$5,000+	Jun 2020	-$1,373	27.5%
$7,500+	Jan 2021	-$1,162	15.5%
$10,000+	Jul 2021	-$646	6.5%
$12,500+	Aug 2021	-$560	4.5%
$15,000+	Jan 2022	-$1,072	7.1%
$17,500+	Jun 2022	-$754	4.3%
$20,000+	Oct 2022	-$1,119	5.6%
$25,000+	Jun 2023	-$1,158	4.6%
$30,000+	Jan 2024	-$847	2.8%
$35,000+	Jul 2024	-$1,152	3.3%
$40,000+	Jan 2025	-$957	2.4%
$45,000+	Jun 2025	-$895	2.0%
$50,000+	Jan 2026	-$1,811	3.6%

The Start-Date Study

What if you had started at the worst possible time? We took every month from June 2019 through April 2026, 83 start dates, and asked what happened to an account that began the $300 model on the 1st of that month. Some caught drawdowns immediately, some caught the best runs. All 76 start dates with a full year of data finished their first 12 months positive.

Started	First 12 months	Total to Sep 2026	Worst drawdown
Jun 2019	+$1,088	+$50,150	-$1,811
Jul 2019	+$1,996	+$49,661	-$1,811
Aug 2019	+$2,492	+$49,736	-$1,811
Sep 2019	+$1,854	+$49,721	-$1,811
Oct 2019	+$2,878	+$50,076	-$1,811
Nov 2019	+$2,712	+$49,873	-$1,811
Dec 2019	+$2,541	+$49,873	-$1,811
Jan 2020	+$3,373	+$49,909	-$1,811
Feb 2020	+$4,673	+$49,841	-$1,811
Mar 2020	+$3,854	+$49,541	-$1,811
Apr 2020	+$3,466	+$49,076	-$1,811
May 2020	+$5,458	+$49,945	-$1,811
Jun 2020	+$5,045	+$49,063	-$1,811
Jul 2020	+$4,451	+$47,666	-$1,811
Aug 2020	+$6,617	+$47,244	-$1,811
Sep 2020	+$7,902	+$47,866	-$1,811
Oct 2020	+$7,675	+$47,198	-$1,811
Nov 2020	+$8,410	+$47,162	-$1,811
Dec 2020	+$8,890	+$47,333	-$1,811
Jan 2021	+$8,199	+$46,537	-$1,811
Feb 2021	+$7,743	+$45,168	-$1,811
Mar 2021	+$8,236	+$45,687	-$1,811
Apr 2021	+$8,748	+$45,610	-$1,811
May 2021	+$8,270	+$44,487	-$1,811
Jun 2021	+$8,690	+$44,017	-$1,811
Jul 2021	+$8,512	+$43,215	-$1,811
Aug 2021	+$6,718	+$40,627	-$1,811
Sep 2021	+$6,423	+$39,965	-$1,811
Oct 2021	+$6,669	+$39,523	-$1,811
Nov 2021	+$7,012	+$38,752	-$1,811
Dec 2021	+$7,427	+$38,443	-$1,811
Jan 2022	+$7,321	+$38,337	-$1,811
Feb 2022	+$6,617	+$37,425	-$1,811
Mar 2022	+$7,050	+$37,451	-$1,811
Apr 2022	+$7,211	+$36,862	-$1,811
May 2022	+$7,413	+$36,217	-$1,811
Jun 2022	+$6,884	+$35,327	-$1,811
Jul 2022	+$7,070	+$34,703	-$1,811
Aug 2022	+$6,692	+$33,910	-$1,811
Sep 2022	+$6,804	+$33,542	-$1,811
Oct 2022	+$6,378	+$32,854	-$1,811
Nov 2022	+$7,172	+$31,740	-$1,811
Dec 2022	+$7,364	+$31,016	-$1,811
Jan 2023	+$8,060	+$31,016	-$1,811
Feb 2023	+$9,648	+$30,808	-$1,811
Mar 2023	+$9,183	+$30,401	-$1,811
Apr 2023	+$8,460	+$29,651	-$1,811
May 2023	+$8,824	+$28,804	-$1,811
Jun 2023	+$8,845	+$28,443	-$1,811
Jul 2023	+$8,142	+$27,633	-$1,811
Aug 2023	+$9,727	+$27,218	-$1,811
Sep 2023	+$11,851	+$26,738	-$1,811
Oct 2023	+$12,583	+$26,477	-$1,811
Nov 2023	+$10,221	+$24,568	-$1,811
Dec 2023	+$9,989	+$23,652	-$1,811
Jan 2024	+$9,288	+$22,955	-$1,811
Feb 2024	+$8,696	+$21,160	-$1,811
Mar 2024	+$10,257	+$21,219	-$1,811
Apr 2024	+$11,651	+$21,191	-$1,811
May 2024	+$11,089	+$19,980	-$1,811
Jun 2024	+$11,478	+$19,598	-$1,811
Jul 2024	+$11,546	+$19,490	-$1,811
Aug 2024	+$10,060	+$17,491	-$1,811
Sep 2024	+$7,327	+$14,887	-$1,811
Oct 2024	+$8,082	+$13,894	-$1,811
Nov 2024	+$10,375	+$14,347	-$1,811
Dec 2024	+$10,162	+$13,663	-$1,811
Jan 2025	+$10,615	+$13,668	-$1,811
Feb 2025	+$10,391	+$12,464	-$1,811
Mar 2025	+$9,624	+$10,962	-$1,811
Apr 2025	+$8,887	+$9,539	-$1,811
May 2025	+$8,453	+$8,891	-$1,811
Jun 2025	+$8,257	+$8,121	-$1,811
Jul 2025	+$8,916	+$7,944	-$1,811
Aug 2025	+$8,991	+$7,431	-$1,811
Sep 2025	+$7,854	+$7,560	-$1,811
Oct 2025	partial year	+$5,812	-$1,811
Nov 2025	partial year	+$3,972	-$1,811
Dec 2025	partial year	+$3,501	-$1,811
Jan 2026	partial year	+$3,053	-$1,811
Feb 2026	partial year	+$2,073	-$1,811
Mar 2026	partial year	+$1,338	-$1,811
Apr 2026	partial year	+$653	-$1,811

Then we made the bad timing deliberate. We restarted the clock at the equity peak right before every major drawdown in the record, the nine worst possible days to begin, where the first thing a new account lives through is the full drawdown. Every one that has run a full year since finished it positive. The ninth is the deepest in the record and it is still running: it began on August 7, 2026 and the account has not yet made a new high, so there is no recovery time and no first year to report. It is in the table because leaving it out would make the other eight look like the whole story.

$300 model ·
starting at the peak
before each major drawdown

Start date	Drawdown lived first	1st month	Days until back above zero	Next 12 months
Aug 7, 2019	-$1,101	-$463	188	+$2,130
Mar 30, 2020	-$1,406	-$1,132	71	+$3,018
Jul 23, 2020	-$1,373	-$696	139	+$5,301
Mar 22, 2021	-$1,162	+$204	29	+$7,708
Jan 4, 2022	-$1,072	-$432	64	+$5,815
Dec 29, 2022	-$1,119	+$196	22	+$7,895
Jun 30, 2023	-$1,158	+$440	18	+$8,142
Oct 4, 2024	-$1,152	-$796	60	+$7,643
Aug 7, 2026	-$1,811	–	not yet	–

When We Would Stop

The way to tell variance from a broken edge is to fix a drawdown tripwire in advance. Ours is the Monte Carlo 5th percentile, the potential worst case: about -$3,860 on the $300 model, the figure in the dashboard above.

Crossing it is a trigger to stop adding risk and investigate, not proof the edge is dead. Two things can put a strategy past that line: variance, a losing run that a working edge still produces from time to time, or edge decay, the market changing in a way that makes the edge itself weaker. Telling them apart means measuring recent behavior against this published record: the win rate, the size of the losses, and how long recovery is taking.

If the recent numbers still look like the record, it is variance, and variance is what a working edge does. If they stop looking like it, we stop running it and say so, here and on our channels.

Reasons Not To Use Clara Core

Clara Core is not for everyone, and we would rather tell you that now than let you find out the hard way.

Don't use it if:

You need a strategy with a positive risk-to-reward ratio. Clara Core's average loss is larger than its average win; it profits only from a high win rate, and that is a fragile edge.

You can't sit through a losing stretch without intervening. Some historical drawdowns lasted one to two months before recovering. If you would turn it off mid-drawdown, this is probably not the right strategy for you.

You're trading money you can't afford to lose, or funding an account with borrowed money. This is high-variance futures trading.

You want fast, guaranteed, or linear returns. The data shows the opposite: uneven, sequential, and dependent on staying in the strategy.

You expect live support or a community chat. Clara Core is self-directed: the setup guide walks every step, but there is nobody on the other end of a chat.

You won't take the time to read the performance data and understand what you're running. If you skip that, you'll be surprised by normal behavior, and surprise is what makes people quit at the worst moment.

If several of those describe you, the honest answer is that Clara Core, as it is today, isn't the right tool for you. That's not a sales tactic; it's the same transparency we apply to everything else here.

That said, even if Clara Core is not the strategy you end up running, there is real value here that costs nothing. Run it on a simulation account and you are practicing the part of trading almost nobody trains: consistent execution. Turning the strategy on every day, letting it trade, watching it win and lose without stepping in builds the habits any strategy demands, automated or manual. Losing is part of trading; every strategy carries losses and drawdowns that can last days, weeks, or months, and watching it happen at zero financial risk is how you learn how you handle them.

You also learn the tools. How to use NinjaTrader, how to enable a strategy, how to read a backtest, and how to verify a published number before you trust it, from anyone. You learn about prop firms and risk management, and how to apply both to a strategy built on published data. Every future strategy uses the same tools, and none of it has to come from us; you never have to buy anything here. But when the time comes to buy something, you will know exactly what to look for, and you will not spend money or months on a strategy sold without the data to back it. Test-drive all of it here, free, for as long as you like, then decide if any of it is for you.

Before you decide anything, read Trading & The Mind. It is the conversation we wish someone had had with us before our first trade: why trading is not easy, why money is personal, why losing is part of the business, and what automation actually solves. Whether you end up running Clara Core, something we release later, or nothing at all, that page is how you find out if trading is for you. Automated trading is the easier way to find out: there is no decision to make on every candle, only one, once. You turn it on and you leave it alone. Clara Core is a free place to start, at no cost and no financial risk.

Trading & The Mind →

Verification

This report is generated directly from NinjaTrader strategy data, including all entries, exits, and execution fees. Every trade carries a $1.90 round-turn commission per contract, $0.95 per side. That is NinjaTrader's free-account rate, all-in, and it is the highest commission anyone running this strategy is likely to pay. We publish at the highest rate on purpose, so that almost everyone's real commission comes in lower than the figures you see here.

A full raw trade export is available for download. You can upload this data into any analysis tool to review the strategy behavior yourself.

Download Full Trade Log →

The Cross-Check: NinjaTrader vs TradingView

To check the record against a completely separate platform, we ran the identical strategy in TradingView and put the two side by side. Since TradingView's 2-minute chart reaches back only about five to six years, this comparison runs on the window both platforms cover, January 2021 through September 2026, on the $300 model. The start is anchored at January 1, 2021 deliberately: TradingView's 2-minute history is a sliding window that moves forward every day, and a clean January start is one you can still reproduce yourself for months to come. Both runs carry the same $1.90 round-turn fee, so the only differences are the platforms themselves.

One structural difference is worth pointing out: TradingView uses the MNQ continuous contract (MNQ1!), a synthetic stitched feed, while NinjaTrader uses the actual front-month contract with real rollover dates. Different data sources, different candle closes, occasionally a different tick.

NinjaTrader took 1,315 trades and TradingView took 1,316, and the two lists pair up on 1,314 of them: a 99.8% match between two independent data sources with different rollover handling. The two platforms disagreed on only three days in nearly six years, and the final results ended $33 apart.

$300 model · Jan 2021 – Sep 2026Jan/21 – Sep/26 · fee $1.90 RT	NinjaTrader	TradingView
Total trades	1,315	1,316
Win rate	71.86%	71.73%
Profit factor	1.63	1.63
Net P&L	$46,537	$46,503
Max drawdown	-$1,811	-$1,816

Three days of difference across the whole overlap, win rate within 0.13 points, profit factor identical, net within $33, and the worst drawdowns within $6 of each other. NinjaTrader's drawdown here is measured on open equity, the way it is everywhere on this page; TradingView reports it the same way. The strategy behaves the same on two unrelated data feeds.

Download both exports →

The Outlier Trade

The largest single win in this record is $1,461.30, taken on January 4, 2022 (with three contracts). A tight stop of about $90 sized three contracts on the $300 model; the strategy went short at 10:02 AM New York time into a session that sold off almost without pause, and the trailing exit followed the move down for $489 per contract, closing at 11:36. It was also the best single day in the record. The average winning trade is $126.75, so that one trade is over eleven times a normal win.

Trades like it are rare. Only four trades in the whole record cleared $1,000, about one in every four hundred.

We point at it because a single outsized trade can carry a backtest and make everything around it look better than it is. This one does not. Take it out completely and the seven-year net goes from $50,730 to $49,269. It accounts for under 3% of the total. The edge is in all the other trades, and it would still be there if this one had never happened.

The same holds for every outlier in the record. Only those four trades won more than $1,000. Cap all four at the average win of $126.75 and here is the whole difference: net profit goes from $50,730 to $46,347, and the worst drawdown does not move at all. It stays at -$1,811, because the deepest stretch in the record has nothing to do with those four trades. Outliers are not the average trade, but they are not accidents either; letting winners run is how the strategy trades, and these are what that looks like when conditions line up.

Slippage

The published figures include commission but do not model slippage, and we would rather say that plainly than pretend otherwise. A few things work in your favor here. MNQ is one of the most liquid instruments in the world, so in normal conditions slippage is minimal; it is during high-volatility sessions that entry and exit prices can differ from the bar-close price the backtest filled at. Slippage is heaviest at the market open and around high-impact news. The strategy never enters during the first 20 minutes after the open. Most high-impact news lands around 8:30 AM, an hour before the market opens, so the entry window sits clear of it. FOMC days are skipped entirely, a skip the backtest supports.

Performance comes from
disciplined execution repeated over time,
not from any single trade.

Clara Core: MNQ backtest · May 2019 – September 2026May 2019 – Sept 2026

Clara Core:
MNQ backtest ·
May 2019 – September 2026May 2019 – Sept 2026