Clara Core is a fully rule-based intraday strategy designed to trade the Nasdaq-100 using Micro E-mini Nasdaq-100 Futures (MNQ). It trades on a 2-minute chart, chosen to reduce the noise and false signals of the 1-minute, while entering moves earlier than the 5-minute would allow.
Price Action First
The strategy is built entirely on price action. All entries and exits are executed automatically based on predefined rules.
You can manually close trades or disable the strategy at any time.
This page explains exactly how the strategy behaves so you can understand it, trust it, and let it run.
Clara Core was built to be the kind of strategy most of this industry sells, a high win rate carried by a negative risk-to-reward, with one difference: every weakness would be published. We prioritised low drawdown first, then win rate and profit factor. A low drawdown does not mean a tight stop; it means the strategy stays out of the conditions where it loses most.
Every filter had to earn its place the same way. It was tested against the full seven-year backtest, and the question was never only whether the numbers improved but how many trades it touched. A filter that improves drawdown by acting on a handful of trades out of 1,500 is noise, and it was not used; a filter has to change the result across a meaningful share of the sample. Improving one number usually costs another: a higher win rate tends to shrink the payoff, a lower drawdown tends to cost profit. When that trade-off came up, we chose the lower drawdown every time.
There are no random skip days. Every day the strategy sits out has a reason: FOMC days, where volatility spikes and liquidity is taken on both sides; market half-days and the session after, where participation is thin and moves reverse instead of trending; and rollover week, when the contract changes hands. Each showed a lower drawdown and a better win rate across a meaningful sample. The specifics of every filter are proprietary; the results of all of them are in every number on this site.
One thing this method cannot do: the filters were chosen against the same seven years the backtest reports, so the published result is not a test on unseen data. That is why the Monte Carlo exists, why we plan around its worst case with a buffer, and why we say plainly that neither a backtest nor a Monte Carlo tells you what the strategy will do next.
Clara Core trades MNQ exclusively.
This allows for consistency, specialization, and controlled execution within one of the most actively traded markets in the world.
Why MNQ:
Tracks the Nasdaq-100 index, driven by global technology and growth sectors
High liquidity and strong participation
Supported across prop firms and platforms
Accessible capital requirements
Clara Core uses an OnBarClose execution model.
All actions (entries, stop adjustments, profit protection, and trailing) occur only after a candle fully closes.
Nothing updates intrabar or on-tick data.
Why this matters:
No repainting
No intrabar noise or false movement
Stable and consistent execution
Backtest behavior aligns closely with live conditions, apart from slippage and fills
When a trade enters, a stop loss is applied immediately, and it is the one exception to bar close: the stop rests at the broker, so if price touches it, the position exits.
There is no fixed take profit, exits are managed dynamically based on price behavior and bar closes. Stop adjustments only update on bar close.
We have run Clara Core on live and simulated accounts to confirm it enters and exits exactly as designed, and because every action happens on bar close with nothing updating intrabar, live execution tracks the backtest closely.
NinjaTrader vs TradingView →Position size is calculated based on the distance between entry and stop loss. The strategy adjusts contract size to stay within a defined risk per trade.
The strategy takes a trade when conditions are met and the risk is within the limit. Because at least one contract must be executed, a trade can use slightly more than your selected risk per trade when the stop distance is wide, but never beyond the $400-per-contract limit, the hard ceiling on how much any single trade can risk.
This behavior is expected and is reflected in the performance data.
On the $200 and $300 models, the one-contract minimum means a single loss can exceed the set risk. They still produce the lowest overall drawdowns of any model. The performance page’s How To Read The Data explains the floor and the ceiling in full.
Clara Core does not operate on a fixed risk-to-reward ratio. It uses several different exit mechanisms, and not all trades behave the same; this is by design, allowing the strategy to adapt to different market conditions. Depending on which exit activates, a trade may:
Close quickly with a small gain
Run for an extended move when conditions allow
Have the stop move to a secured profit level after reaching a threshold, then exit if the market reverses before the full target is reached
That secured level is not break-even. Once price moves a defined percentage toward the target relative to the stop, the stop adjusts into profit, locking in part of the move. How much depends on which of the 5 exit models is active. Not all exits use this mechanism, and every adjustment happens on bar close.
Because of this, some trades close early and protect capital, some run and capture extended moves, and some give back unrealized profit before exiting. That variation is expected and intentional, and it is why performance should not be evaluated on any single trade outcome or a fixed risk-to-reward ratio. The relevant metrics are win rate, profit factor, and drawdown; that is what the strategy is built around.
Any trade still open is closed automatically on the first bar close after 3:30pm ET. No positions are ever carried overnight. This is built into the strategy and has shown improved results over time. It also ensures compliance with prop firm rules that require all positions to be closed before market close.
Full profit factor and win rate breakdown by year and risk model is available on the performance dashboard.
All logic is predefined within the strategy. Entry logic, exits, filters, and internal behavior are not visible or user-adjustable.
You control two inputs: risk per trade and a time zone offset. Everything else runs automatically. One built-in limit is public: no trade can risk more than $400 per contract. It is locked in the code; it is not an adjustable setting. No other part of the logic is adjustable, by design.
The published record runs this exact configuration. That includes the skip-day filters in the next section. The one choice you make is risk per trade. If you run a value other than the published models, treat it as your own experiment: backtest it first, free in NinjaTrader, and compare it against the defaults. The defaults are the strategy we publish.
Strategy parameters are fixed, tested against seven years of data. This removes the temptation to interfere, second-guess, or over-optimize based on short-term results.
This structure is a key reason the strategy maintains:
Controlled drawdown
Stable performance over time
A historical win rate of 71.45%
That win rate is the entire edge: the average loss is larger than the average win, so Clara Core profits only because it wins far more often than it loses. The performance page shows the full picture.
Clara Core is designed to operate without the need for constant monitoring or manual decision-making. Predefined execution filters automatically avoid specific market conditions that have historically shown lower consistency and higher risk.
Built-in filters, reflected in all backtest results:
FOMC decision days
Futures rollover week (one week each in March, June, September, and December)
Market half-days
The session after a half-day, covered by the same notice
These filters are built into the strategy as a capital protection measure.
Why these filters exist
Historical testing shows these periods tend to produce less stable conditions, including increased drawdown and inconsistent behavior. Rather than maximizing trade frequency, the strategy prioritizes stability and capital preservation. This removes the need to monitor economic calendars or manually avoid unfavorable conditions.
Day after half-day
The strategy also avoids trading the day following a market half-day. The specific weekday varies from year to year with the holiday calendar. While the impact on total trades is small, testing shows this period can slightly increase drawdown. For this reason, it is treated as a protective filter.
Built In
These filters are part of the strategy itself. There is nothing to configure and no calendar to monitor; the chart label tells you when one is active.
The goal is not to trade more. It is to trade better.
The strategy trades Monday through Friday. All other economic events (CPI, payroll, PMI, earnings, and other high-impact news days) are traded normally. No calendar monitoring required. Only structurally abnormal sessions are excluded.
You do not need to track the news, watch earnings releases, or manage exposure around the Nasdaq's largest components. The strategy handles entries and exits based on price behavior, not on what is happening in the news. Turn the strategy on and step away.
Experienced traders often feel the pull to intervene, closing a trade early because the move looks extended, skipping a day because the market feels uncertain. But no indicator, reading, or intuition is consistently right enough to override a systematic edge. The reason you are using automation is to remove that burden. Let it run.
There is a risk here that rarely gets discussed: if the platform disconnects or restarts while a trade is open, a strategy can lose track of the position, and depending on your platform settings the protective order can be cancelled along with it, leaving the position running unprotected. A naked position.
Two things prevent it, and the Setup Guide covers both. Your protective order rests at the broker, so a stop never depends on your machine staying up, and one NinjaTrader setting keeps that order alive if the strategy stops. After a short drop, the platform reconnects and the strategy continues on its own. After a restart the strategy is no longer running, and after a longer outage it may be disabled. Your stop stays exactly where it is, resting at the broker, for as long as the trade is open, and you can confirm it from your broker's phone app with NinjaTrader fully closed. The Setup Guide walks through what to do when you are back at the machine, along with how to set an extra layer of protection: a maximum daily loss limit on the broker side, on a prop firm or cash account.
The strategy operates based on U.S. market hours (9:30am ET, Eastern Time). A time zone offset setting is available for users running NinjaTrader outside of ET.
Most people never touch this. It only matters if NinjaTrader itself is set to a time zone other than Eastern, usually because another strategy on the same platform needs it there. Example: your platform runs on European time for a different strategy; leave it there, set Clara Core’s offset to the difference, and it still trades the New York session. If NinjaTrader is on Eastern Time, leave the offset at zero.
No strategy performs well in all conditions.
Clara Core may struggle during:
Choppy, range-bound markets
Low participation or low volume
Repeated false breakout conditions
The execution filters reduce exposure to some of these conditions, but no filter can fully anticipate every market environment. Losses and drawdowns are part of trading regardless of the strategy. Managing risk correctly is what keeps emotions in check when difficult conditions arrive.
Your selected risk per trade plays a major role in how these periods affect your account.
Detailed statistics, drawdown profiles, and risk models are provided so you can choose an approach that fits your account size and risk tolerance.
For a detailed view of how to structure risk across account types, see the full Performance page.
Risk At Account Size →This page replaces onboarding and support: everything the strategy does is laid out here, in plain language. All results are based on historical backtesting. The objective is structured risk management, not risk elimination.