Interview noteThis page restates a public interview in new words. Dollar results, win rates, and payouts are claims made by the speaker or the host. They are not this desk's record, and they are not a result to expect.
Imre Garth, whom the caption also calls Emre and Emery, is the portfolio manager the host introduces as an eight-figure institutional trader, a former hedge fund director, and the right-hand of the trader the caption names Andy Krieger. He does not arrive with a setup to copy. He arrives with a definition. An edge is a mechanical cause and effect in the market, repeatable enough to be taken advantage of and to pay over time. Asked what share of retail traders are actually exploiting one, he says nearly zero percent. In thirteen or fourteen years of asking the question, he has not once received an answer he considers legitimate. Following smart money, being disciplined, and knowing a chart pattern are the answers he gets. None of those is an edge. Nothing in the hour is advice. The useful half is how he separates a durable constraint from a fragile one, and then the candlestick filter he uses so a day trader is not applying the right setup to the wrong regime.
A durable edge is a constraint, and it will not pay like a secret
He wants retail to look for a durable edge. Durable means it has been there and is not leaving soon. Fragile is his favorite contrast, and the example is Barron Trump. He is explicit that he is assuming, not reporting, that a person in that position sees information before other people do. Trading that access is an informational edge, and it is fragile because the access can disappear. Fragile edges are less crowded. High-frequency firms are the other example, and he does not call that one fragile so much as unavailable. They exploit very small inefficiencies, extremely fast, many times a day. The cost is the infrastructure. Firms compete for real estate next to the exchange to cut latency, and then they pay for the research and the upkeep of the algorithms. Retail cannot express that edge. A durable edge is the realistic shot at consistency, and the downside is that it is less explosive. You will not pull as much from it.
His favorite durable version is a large participant who is constrained. Not because they want to transact, and not because they do not. Structural reasons force the trade. The one he says he actively uses is the continuous institutional demand for downside protection in options. Puts carry a premium because they hedge a crash. A manager concentrated in the large American companies, the blue chips and the AI names, wants that hedge, and other institutions have written into their own mandates how much downside protection they must hold and at what levels. You cannot Google the playbook. It lives in an operating manual. If the demand is always there, an edge can be expressed in it.
The moment he wants is the spike. A real selloff, the headlines turning dark, a market that looked fine a day earlier and now might be the top. Demand for the puts jumps. The old line is to buy when there is blood in the streets. He sells. What he sells is the downside protection, to the institutions who suddenly need it. The image is a house on fire and an offer of insurance that more than covers the damage. He can charge a great deal, up to the value of the house. If the house actually burns, he owes the policy. That is the risk, and he has to hedge his own exposure. It is his favorite way to trade. He will not give the minimum reproducible version in full. Selling puts is not new, and the specific expression is an edge he wants to keep. Asked how important a real understanding of options is for an average retail trader, he says ten. Without it, the trader is oblivious to the forces moving the market.
Even if every retail account traded the same way at the same time, which they do not, the flow would not shift a very liquid market by much. He is talking about US equity index futures, not a thin stock. GameStop was a different story. He does not like the phrase dumb money, and he uses it anyway, as ignorance of the forces rather than as an insult. Retail wants the market up because they are long, or down because they are short. It is a narrow view. A large hedge fund or a pension, on many days, is happy if the market stays in a range. The incentives are different. Trading against the desk without knowing it is, over time, unlikely to end well.
Define it, then do not treat a hand-drawn backtest as proof
Gain and an edge are correlated and they are not the same thing. He has seen professional traders who understand the edge and still under-express how explosive it is. On the retail side, money over a short sample can be random. If you cannot define the edge and you are profitable, you might be exploiting something without knowing it. You are more likely, in his view, to be lucky. Proof is whether you can quantify it, articulate it, and back it with research. Some edges are narrow in time and have to be hit hard. That ability, identifying a narrow explosive edge and taking everything it will give, is what he has seen in the best traders he has worked beside. The second step is whether live performance matches the quantitative expectation. This is where people say they backtest.
A fully manual discretionary backtest, as a statistical foundation, has zero validity for him. Not one percent. Looking at old charts can still be useful. Believing you have built an expected distribution, while you are the person making the decisions, is a false belief. Pressed, he says the manual review is more valuable than an automated backtest for a trader who also executes by hand. The automated test assumes perfect conditions. He has rarely seen one that properly includes slippage, fees, and commission. He is obsessed with efficiency because those costs are a large part of the result. Even a tight futures spread is ticks paid away, which is how a market maker lives, and it adds up over a year. The automated test also assumes the trader pulls the trigger the same way every time. He does not care how disciplined the person is. Perfect consistency is impossible. A quantitative fund, and he has a friend who runs one, does the research properly and then executes the strategy with an algorithm. In that case the backtest has value, and it still has to be checked against real performance. The question is not only whether live results missed the test. It is what changed in the market. Tomorrow will differ from yesterday, and the further back the sample, the larger that gap is likely to be.
For a manual trader, old shapes are there to train the eye on the trigger. They are not there to support a belief that the pattern will make a million dollars because it seems to play out. The purpose is narrow. It will not make the trader better except at recognizing the moment to put risk on. Most of those patterns, he agrees, are statistical noise, unless the trigger has already been separated from an edge that was quantified. Asked what the vast majority of discretionary traders should do instead, he says they should probably not trade. There are more entertaining ways to lose money. If someone is committed anyway, automation is better only when there is an identifiable edge and the skill to see it decay. Most people do not have that skill. Even a quantified edge still needs a moment where risk goes on. If that moment is a mouse click on a visual pattern, the trader has to know what the pattern looks like.
He proved his own edge mathematically. Options help, because they depend less on a price chart. For the swing trading and the technical analysis most people want, he spent years on charts and on the tape, as a professional and before that. The value he keeps from that work is framing the opportunity and, more importantly, framing the reward against the risk. Risk, if the stop is honored, is relatively defined. Slippage is real, and he sets it aside for the point. Reward is uncertain. Most retail trading is what he calls delta one. In, out, a bet on direction. Persistence in returns is extremely small and usually arbitraged away quickly. He still thinks trend following and breakouts, held longer, can be part of an edge. There is empirical evidence. US stock markets, up to this point, go up and to the right. New highs are breakouts by definition. Most people who trade breakouts fail anyway, not because the thesis is wrong, but because the way they put money behind it does not realize the return.
A random walk, the drunk man stumbling uphill, does not, for him, kill the breakout. The only way a market rises consistently is by breaking out. Whether that beats beta is a question of the risk framework, the second step of his recipe. If the structure survives ordinary variance and the nominal return is greater than what the market provides per year, it beats the market. A more durable edge is more crowded and offers less. A narrower, more fragile edge offers more and will not last, because other people arrive, the edge gets crowded, and the opportunity is arbitraged out. He would rather start from the worst case than from a percentage target. Some leveraged funds will say that if the market is up 10 percent they will be up 40, 50, or 60, and if the market is down 12 percent they might be down 25, which can pull the investors out. Tolerance is the manager's, the fund's, or the person at home. The risk parameters have to be tied to the edge. Selling a 30-delta put makes much more premium than a 1-delta put, and a 30-delta put should theoretically win about 70 percent of the time. He will claim very little in the interview, and he will claim that consistently selling 30-delta puts blows up at that win rate. A 20-delta put, still a high delta in his view, also blows up. There is no edge. A trader can win ten or eleven months and lose the year in the twelfth. That is what he says happens to people who treat a 20-delta short put as safe. The risk framework has to be built around the limitation of the edge being expressed.
The process can be taught. The subconscious click cannot.
Discretion transfers to a point, the way a coach can teach a jump shot and still cannot put a player in the league by instruction alone. He thinks most people, in the right environment, could become halfway good and make returns with some consistency. Not millions. Something that shows up on a tax return. In theory, yes. In practice, no. Sitting next to professionals is what turned his own trading. He did not learn their discretion. He will never trade the way the host trades, and the reverse is true. He can teach a global-macro process, where he thinks money is moving between countries, markets, and sectors, and the student will change it. He learned tape reading, technically and mechanically, from a couple of people. That is a pattern, not an edge. He learned how to assess a market from a global-macro perspective from one of the greatest traders of all time. The knowledge is not fully transferable. The process he adapted is his.
The thing the best discretionary traders cannot explain, in his account, is information processed subconsciously and very fast. A lot of it is observed behavior that was once deliberate. The last seller cleared off the offer, and the market goes, and it does not work every time, but paired with other variables it beats a coin flip, and that is when they size up. They are not walking the steps. The brain is good at patterns, including the illusory ones. The reason they cannot name the thing is that the processing is subconscious. He believes that if a discretionary trader were put in front of him, he could mechanically explain why the results happen, including cases where the results happen for a reason the theory says they should not, and risk management can be that reason. A host's hypothetical, a long-only logic that tests as garbage and a short of the same rules that tests as excellent, he treats as a question of data rather than of the original story. Good trading, as he puts it there, is an exercise in collecting high-quality data.
One-time framing is the filter, and it is stricter than a higher low
Most traders, he thinks, already know what a good setup looks like. They trade it without the larger regime. Whether the day-trading session is won or lost is decided before the first trade. The missing piece of the pre-market work is what he calls the macro technical regime. The tool is a plain candlestick. Two regimes. Balance is the range. Imbalance is the trend. If the market is a bell curve, balance is the fat middle, and it happens about 70 percent of the time, give or take. Directional markets are the other 30 percent. Day traders need that directional volatility. Chop is where accounts get blown up, and a basic regime check avoids a lot of it.
Inside imbalance he uses one-time framing, up or down, as the sign of who controls the auction. His definition is stricter than the older one. The older version was higher lows, or lower highs, so long as the market was not making a lower low. He wants a candle that makes a higher high, a higher low, and a higher close above the previous candle's high. On the monthly ES chart, the May 2025 candle does that against April. Buyers are in control. June does it against May. July's high sits very near August's close. He treats them as the same for the example, and August is no longer one-time framing up. August can make a higher high and a higher close relative to July and still fail the test, because the close is not above July's high. That is balance. November starts another balance. December makes a higher high, a higher low, and a higher close, and does not close above November's high. November becomes the reference for whether the up cycle breaks. The low of the candle that started the balance remains the reference for whether one-time framing down has begun. A later candle can print a lower low, a lower close, and a lower high and still not be one-time framing down, if it does not close below that reference low. He uses January's low for one of those candles. March one-time frames down against February and is still inside the larger balance, because it has not closed below the November 2025 low, the candle that opened the balance.
Balance, in auction terms, is a temporary agreement on fair value. Buyers will take inventory at the low. Sellers will sell it at the high. Price rotates. Institutions can accumulate and distribute while that business gets done. When it is finished, the next phase is imbalance, up or down, and that is the directional movement a day trader wants. Momentum setups inside balance are far less likely to work. Fading highs for a mean reversion, while the market is clearly one-time framing up, is trading against the larger flow.
He runs the same test on the monthly, the weekly, and the daily chart. On the monthly chart in front of them, April 2026 resumed one-time framing up, May continued, and June and July were a two-month balance. August is not finished. The interview is a Friday before the cash open. If the month ended where it sat, it would be one-time framing up again, back with the larger bullish imbalance. The weekly chart shows the same balance, and the week of August 3, 2026, resumed one-time framing up. The current week, if it closed where it was, would still be up. On the daily chart, Thursday, August 13, resumed one-time framing up after a small multi-day balance. Friday is still ahead. He will lay a market profile on the same balance. The value area, between the value-area high and the value-area low, is where 70 percent of the trade in that profile occurred. That is fair value. Higher highs and higher lows are a simple definition of an uptrend. The more professional one, for him, is whether value itself migrates. Price moving is one thing. Time spent higher, a new balance, is the market accepting fair value up here instead of down there. He uses the filter for swing trades, for systematic options, and for day trading. It cuts the decisions and puts him on the side of the larger participants.
When the monthly, the weekly, and the daily are all one-time framing up, he wants momentum to the long side and continuation on pullbacks. One-time framing down is the same idea in reverse. A range with no one-time framing is where he fades the extremes. About 70 percent of the time is spent inside value, so a rotation from one extreme to the other is the high-probability path. In a balance he is an intraday trader from move to move. A long at the value-area low is exited at the value-area high. The thickest node in the middle is the point of control, and it is a systematic place for a partial. He does not take the partial. He wants the full rotation. He assigns an 80 percent probability to completing that rotation once the value-area low is reclaimed, and the same in the other direction. The study, he says, goes back to Jim Dalton. He has validated it himself across timeframes and profiles. The 80 percent moves slightly with the market. The market he concentrates on is the ES.
In an imbalance, breakouts are statistically more likely to work. Every breakout trader still has to define the initial break and the pullback. He does both. The choice depends on the tape and on a short look back at how similar breaks behaved in recent sessions. Sometimes price returns to value. Sometimes it does not look back. A pullback into value is one version of the pullback trade. He cannot know, at the entry, that it will drift on instead of rotating inside the old fair value. The actual level, for him, comes from the options data he reads intraday, the concentration of dealer inventory, which moves. That is a thesis about where dealers will hedge. The timeframe rule is personal and he wants it systematic. He will not short when the daily chart is one-time framing up. He will wait for a buy. He will not go long when the daily chart is one-time framing down. A hyper-scalper might trade against that. He will not. He needs a shift in the auction on at least the daily chart. When the monthly is one-time framing up, the weekly is in balance, and the daily is one-time framing down, those are the sessions to sit on his hands until the timeframes he cares about agree.