What are the best trade entry models for day trading?

What are the best trade entry models for day trading?

The most defensible entry models pair a specific price location, called a point of interest, with confirmation from market structure across more than one timeframe and, where it is available, volume profile data. The video frames anything entered without that layered confirmation as impulsive, not a repeatable entry model.

In "THE BEST ENTRY MODELS + HOW JORDAN MADE $60K IN ONE DAY" (BWE Podcast Ep. 19), the RihariFX hosts say they all trade the same underlying strategy, described in the video as a foundation built on smart money concepts, but each has developed a personal set of entry criteria on top of it through repetition and session experience. The video repeatedly separates three recurring entry approaches: a pullback into a marked point of interest, confirmation through a change of character checked across the 1-minute, 5-minute and 15-minute charts, and confluence with volume profile levels such as the point of control and the value area high or low. A fourth, less structured approach, entering with New York session volume before a pullback occurs, is discussed but explicitly flagged by the hosts as harder to defend and not something they send out as a trade signal.

Nothing in the video should be read as a promise that any of these models produces profit or is safe to trade with real capital. The hosts describe their own results and habits; they do not describe a licensed product, a guaranteed system, or typical outcomes for a viewer.

How does the point of interest entry model work?

A point of interest, in the video's terms, is a price zone where the trader expects the market to react, ideally sitting in the discount half of a range for a buy or the premium half for a sell, using the 50% equilibrium level as the dividing line.

The hosts say the model works best when that zone also lines up with market structure and, for an A-grade version, with a higher-timeframe volume profile level. The hosts describe waiting for price to reach the point of interest, then looking for confirmation before entering rather than placing an order the moment price touches the zone. One host explains that if the point of interest sits at the extreme of a range, the whole range becomes available as potential reward, which the video presents as the reasoning behind favoring extremes over mid-range levels. The stop loss, per the video, is placed beyond the point of interest or beyond the most recent swing low or high, so the trade is invalidated if price simply pushes through rather than reacting.

The video also flags a session-based limitation of this model. One host recounts trading Asian session extremes successfully, then applying the same habit to New York session volume and getting run over, because New York volume, in the hosts' description, tends to push through levels that would have produced a reaction during quieter sessions. The lesson stated directly in the video is that a point of interest entry has to be adjusted for the session being traded, not applied identically around the clock.

Why do traders wait for a change of character across multiple timeframes?

Traders check a change of character against a higher timeframe before trusting it, since the hosts say the signal is unreliable alone on a low timeframe. Acting on just a 1-minute or 5-minute shift, they note, has led traders into entries against a higher-timeframe trend that was still intact.

The video walks through a specific example on gold: a change of character appeared on the 1-minute chart and closed through on the 5-minute chart, which one host initially read as confirmation to sell. The other host recounts checking the 15-minute chart as well, seeing it wick below the level and then close back above it, and only then treating the setup as genuinely bullish. Both hosts describe this as a recurring pattern, not a one-off, and say the discipline of confirming on a third, higher timeframe has kept them out of trades that the 1-minute and 5-minute charts alone would have triggered incorrectly.

The video is explicit that this is a filter, not a standalone entry trigger. A change of character that lines up across the 1-minute, 5-minute and 15-minute timeframes and sits at a point of interest is described as closer to an A-grade setup than a change of character on the entry timeframe by itself. Neither host claims this filter removes losing trades entirely, only that it reduces a specific, named failure mode they had both experienced.

How does volume profile improve entry timing?

Volume profile is described in the video as a chart tool, most reliable on regulated futures markets, that shows where the heaviest buying and selling has occurred at each price level over a chosen period, producing a point of control, a value area high, and a value area low.

The hosts use these levels as an institutional reference for fair value, discount, and premium, layered on top of their existing structure-based entries. The video's explanation treats the point of control as the level the market has agreed is fair, with the value area low framed as a discount an institution might buy at and the value area high as a premium an institution might sell at. One host says this reasoning only holds when combined with market structure and, ideally, with scheduled economic news, because the hosts have observed high-impact news events pushing price into a previous week's or previous month's value area level before a larger move develops. The video is careful to frame this as the hosts' interpretation of market behavior they say they have observed repeatedly, not as a documented fact about institutional order flow.

A specific caution is included directly in the video: a value area low or high should not be traded in isolation just because price is near it. One host says he needs the level to "make sense" against structure, giving the example that a value area low sitting in open space, reached by a fast, heavy move down, would not be a trade he takes without a further reason for price to reverse there.

What is the difference between an A-grade setup and an impulsive trade?

An A-grade setup, in the video's language, is one where the point of interest, market structure, and (where relevant) a volume profile level all line up before the trade is entered, with confirmation checked on more than one timeframe.

An impulsive trade is anything entered without that alignment, including entries taken purely because a level is nearby or because session volume is already moving. The table below summarizes how the hosts describe their main entry approaches, based on statements made directly in the video. It is a record of what the RihariFX hosts say they do, not an independently verified trading system, and none of these approaches is described as risk-free.

| Entry model | What triggers it | Confirmation the video says is required | Session it is best suited to | Risk noted in the video | |---|---|---|---|---| | Point of interest pullback | Price returns to a marked discount or premium zone | Internal change of character reacting from the zone | Any session, but the reaction differs by session volume | A higher-timeframe candle can push straight through the zone, especially in New York | | Multi-timeframe change of character | 1-minute and 5-minute structure shift | Must also close through on the 15-minute chart | Any session, used as a filter on other entries | Skipping the 15-minute check led to a losing trade the hosts describe by name | | Volume profile confluence | Price reaches a point of control, value area high, or value area low | Level must align with market structure, ideally with scheduled news | Futures markets, higher-timeframe levels | Only reliable, per the video, when the level "makes sense" against structure, not traded on its own | | New York volume continuation | A level breaks and price pulls back before continuing | Pattern recognition built from repeated exposure to New York volume, not a fixed rule | New York session, high-volume pairs such as US30 and gold | Described by the hosts as aggressive, without a clean invalidation point, and not something they send as a signal |

The hosts are candid that the fourth row is the hardest one to defend. One host describes debating internally whether entering with volume before a pullback is informed pattern recognition or simply an impulsive trade that happened to work, and concludes it is not something he would recommend to someone without that session experience already built up.

How should day traders manage risk and position size after entry?

The video describes a repeatable sequence for managing a trade after entry rather than a single fixed rule, built around trailing stops and reducing position size once an initial profit target is reached. None of the steps below are presented as guaranteed to protect capital.

1. Learn the underlying strategy foundation before defining any entry criteria; the hosts say building an entry model without that foundation leads to losses.
2. Mark the point of interest and any relevant volume profile levels on the chart before price arrives there, rather than reacting in the moment.
3. Wait for a change of character confirmed on at least the next higher timeframe before entering, not just the entry timeframe alone.
4. Check whether the level lines up with market structure and, where relevant, a scheduled news event, rather than trading the level in isolation.
5. Place the stop loss beyond the point of interest or the relevant swing point so the trade is invalidated cleanly if price pushes through.
6. Size the first trade to reach an initial target, then reduce size, described in the video as "de-risking," for any additional trades taken afterward.
7. Apply a trailing stop once in profit, which one host says is necessary on prop-firm evaluation accounts to manage rules based on unrealized profit drawdown rather than realized loss alone.
8. Record which entry type was used and whether it won or lost, so a personal win rate can be built up over time rather than assumed.

The video includes a specific caution about step 7. One host describes losing an evaluation account despite being up around $12,000 at the time, because the account's rule measured drawdown from the highest unrealized profit reached, not from the starting balance, a rule he says he learned the hard way. This is presented as a lesson about reading the specific rules of a funded account, not as advice that applies to every broker or account type.

Can a day trader copy someone else's entry model?

The hosts say directly that a viewer cannot simply copy their A-grade setup and expect the same results, because the setup only works alongside the personal data and experience used to build it.

Repetition, described in the video as time in the market, is presented as the only way a trader develops enough confidence in a specific entry to size it appropriately. One host gives a concrete illustration: during a period when the group sent trade signals, a week with a 38% win rate would still have been profitable overall if every signal was taken, but subscribers who had just lost two signals in a row would often skip the third one, missing the win that followed. The video uses this to argue that a viewer copying trades without the underlying data or reasoning behind them is likely to behave differently, and often worse, than the person who built the setup. This is an anecdote the hosts use to make a point about trader psychology, not an audited or independently verified performance statistic.

The video also mentions that RihariFX has partnered with Blueberry Markets to offer free trade signals, and describes an advanced course focused on helping traders build their own entry criteria and psychology after learning the shared foundation. These are statements made in the video about products and partnerships the hosts say exist; they are not evidence of licensing, regulatory approval, or typical results for anyone who uses them, and nothing in the video should be read as an income or performance promise.

The $60,000 figure referenced in the video's title is also worth separating clearly from a business claim. In the video, one host describes passing three $300,000 Apex evaluation accounts in a single day, combining to roughly $60,000 in evaluation profit, using two trades he classifies as A-grade setups and a third taken more on session volume. This is a single trader's account of one day's outcome on prop-firm evaluation accounts, not a licensed track record, not a typical result, and not a claim that any other trader following the same entry models would achieve a similar outcome.

What do independent statistics say about retail trading risk?

Two independently published facts are relevant to how much confidence a trader should place in any entry model, day trading strategy, or signal service. Neither statistic is drawn from the video, and neither should be read as a comment on RihariFX specifically.

ASIC Report 828: Risky business records that 68% of Australian retail CFD investors lost money in the 2024 financial year. This figure covers CFD trading broadly across the Australian retail market, not the specific instruments, brokers, or entry models discussed in the video, and it should be read as context for the base rate of loss in this category of trading rather than a statement about any individual trader's likely outcome.

The BIS 2025 Triennial Survey reported average daily OTC foreign-exchange turnover of US$9.6 trillion in April 2025, underlining how large and liquid the broader market is that instruments like gold and major currency pairs trade within. Scale and liquidity at the market level say nothing about whether a specific entry model, or a specific trader's application of it, will be profitable; the two facts are presented here as independent background, not as validation of any claim made in the video.

Read together, these two figures frame the practical stakes of the entry models described above. A large, liquid market does not protect an individual trader from the loss rates ASIC has documented, which is why the video's own emphasis on confirmation, invalidation levels, and building personal data before risking capital is a reasonable operating discipline, separate from any claim about how well it performs.