We analyzed the strategies of Upscale traders who reached payouts — from $274 to $41,000 on funded accounts — to identify the most popular and effective approaches. The main takeaway: there is no single "best strategy," but there are patterns. The most common tool is Fibonacci, followed by Smart Money Concepts (liquidity and market structure), trading from levels, indicator systems, and volume analysis. Entry methods differ from trader to trader, but risk management is almost identical: 0.5–2% risk per trade, a mandatory stop-loss, a risk/reward ratio of at least 1:2, and leverage no higher than 5×. It's this combination — freedom in choosing a method plus strict discipline in managing risk — that sets apart the approaches that actually lead to a payout.

How we analyzed this

This breakdown is based on video interviews with Upscale traders who reached payouts, confirmed by on-chain certificates. For each one we recorded the decision-making method (what the entry is built on), the tools, the timeframe, and the risk parameters, then grouped the approaches and counted which appear most often.

A quick note on terminology. A strategy has two parts: an approach or tool that tells you where to look for an entry, and risk-management rules (stop-loss, position size, risk/reward) that decide how much to put on it. Below we break down the entry approaches — the most visible and variable part. The risk rules turned out to be nearly identical across the traders we studied, so they get their own section at the end. One more caveat: traders rarely use a single "pure" approach — more often it's a combination, for example Fibonacci layered on top of market structure.

Approach #1: Fibonacci — the most popular tool

How it works. After a strong directional price move, a trader draws a Fibonacci grid over it — a set of horizontal levels (38.2%, 50%, 61.8%, and beyond). The idea is that after an impulse, price usually pulls back to one of these levels before continuing. The trader waits for that pullback into the target zone, enters in the direction of the original impulse, places a stop beyond the level, and marks targets at further Fibonacci extensions. The tool itself gives no "buy" or "sell" signal — it only suggests where an entry is likely, so it's always paired with confirmation.

Fibonacci levels are the most common element across all the approaches we studied. Exerato took it furthest: fractals plus Fibonacci, a win rate of around 70% on a 500-trade backtest, a fixed risk/reward of 2.7–3.65, and 0.5–1% risk per trade. Saul built an asymmetric model on the same base with an 8:1 R:R — rare but large trades that earned him $27,053 in payouts. Alexander uses the specific 1.41 and 1.61 levels together with volume, while Nikita combines Fibonacci with volume and market structure.

One important limitation: Fibonacci levels on their own carry no statistical edge — it's a mapping tool, not a signal. It only works alongside discipline and fixed risk. The classic study by Barber and Odean (2000) supports this: a trader's results are driven not by the choice of tool but by trade frequency and cost control.

Approach #2: Smart Money Concepts

How it works. SMC starts from the idea that large players move price to collect liquidity — clusters of stop orders sitting beyond obvious highs and lows — and then reverse the market. A trader watches three things: liquidity sweeps (price spikes sharply through a visible extreme and returns), breaks of market structure (BOS — price breaks a prior significant level, confirming a change of direction), and a return to a "zone of interest" or order block — the area a strong move originated from. The entry comes on the pullback into that zone after a liquidity sweep. No indicators are used, only price structure.

Albert builds entries on order blocks, liquidity sweeps, and premium/discount zones with top-down analysis — from the daily dealing range down to the 15-minute chart. Pyotr trades pure structure and liquidity with no indicators at all: entry on the 15-minute timeframe after a liquidity sweep, R:R 1:2 — and all of it on forex and gold. Olaide places limit orders at zones of interest and deliberately switched from 100× leverage to 5×.

Elements of SMC show up in others too: Exerato catches fractal sweeps (liquidity sweeps in essence), while Irina and Wade use the Fair Value Gap (FVG) — a price gap the market tends to "fill" — as an entry point. That's why SMC nearly matches Fibonacci in reach: the concept is flexible and combines easily with other methods.

Approach #3: Trading from levels and price action

How it works. The most "manual" approach: a trader marks horizontal support and resistance levels on the chart — prices the market has already reversed from several times. The logic is simple: orders cluster at these levels, so price is likely either to bounce off a level or, having broken it, to keep going. The decision is made through price action — reading the candles themselves (a long wick at a level signals a bounce; a firm close beyond it signals a breakout), without indicators. Minimal tools, but it demands maximum experience in reading context.

Anton trades support and resistance with price action and volume across several timeframes — and does it entirely from his phone, without his own computer. Ernest, the oldest of the traders we studied, trades intraday from levels using the Gerchik system on the one-minute timeframe, trading ETH and the NASDAQ index only during the US session. Irina builds entries from support/resistance zones with confirmation via a structure break on the 5-minute chart.

Approach #4: Indicator systems

How it works. Here the signal comes not from the chart itself but from indicators — formulas calculated from price. Bollinger Bands build a volatility "channel" around price: a touch of the lower band hints at oversold conditions, the upper band at overbought. RSI measures the strength of a move on a 0–100 scale: below 30 is considered oversold, above 70 overbought. MACD catches momentum shifts through moving-average crossovers. The key principle of systems that work is minimalism: 1–3 indicators, not a dozen, or the signals start to contradict each other.

The clearest example is Alexey: a single indicator — Bollinger Bands — plus 5× leverage and under 1% risk per trade earned him $412 in 50 days. Maru Joshua uses a combination of MACD, RSI, Bollinger Bands, and Fibonacci for scalping on the 15-minute chart — but trades Bitcoin exclusively, deliberately narrowing down to a single instrument. Wade adds RSI below 30 as an oversold filter to his entries, stretching results with a risk/reward as high as 1:6.

Roman stands apart: he scalps breakouts with a 1:6 R:R and the counterintuitive rule of "do the opposite" — he blew four challenges in a row before taking $1,356 on the fifth. Scalping and breakouts are more of an execution style layered on any of the approaches above than a separate approach.

Approach #5: Volume analysis

How it works. Volume shows how many contracts or coins were actually traded on a given move. The logic: a move on high volume is "real" — actual buyers or sellers are behind it — while a move on low volume reverses easily. So volume is almost always used not as a standalone signal but as a filter: an entry from the main approach is taken only if volume confirms interest at a level or breakout.

That's exactly how it plays out in the stories we studied. Alexander confirms Fibonacci entries with volume, Nikita confirms structural entries, and Anton confirms bounces off levels. No standalone "volume strategy" in its pure form appeared among the cases we studied.

What all approaches have in common

This is where the main finding of the analysis lies. Entry methods vary from trader to trader — from pure Fibonacci to SMC to a single indicator — but their risk-management rules are almost identical:

• 0.5–2% risk per trade. Not one of the traders risks a large share of the account.
• A mandatory stop-loss. A study by Locke and Mann (2005) on Chicago Mercantile Exchange data found that traders who cut losses faster earn on average 65% more per year. According to PipFarm, 73% of failed prop accounts systematically violated their stop-losses.
• A risk/reward ratio of at least 1:2. For Wade and Roman it reaches 1:6, for Saul up to 8:1.
• Leverage no higher than 5×. Olaide and Alexey both name the switch to low leverage as a turning point.
• Selectivity. A PipFarm survey of 2,777 prop traders found that 45.1% of profitable traders make just 1–2 trades a day. Pyotr turned this into a "one trade a day" rule.
• A trading journal. Exerato and Ernest treat keeping a journal as the core of their system, not an add-on.

Key Takeaways

Analyzing the stories of traders who reached payouts leads to one answer to the question "which strategy is best": there is no best strategy. There are approaches of varying popularity — Fibonacci in front, followed by Smart Money, levels, indicators, and volume — but none of them delivers results on its own.

Strategy is 10% of success. What separates the 7% who reach a payout from the other 93% (according to FPFX Tech, based on 300,000 prop accounts) isn't the choice between Fibonacci and SMC — it's discipline of execution: fixed risk, a mandatory stop, sensible leverage, and selectivity. Alexey's single indicator and Albert's complex multi-timeframe system both work for the same reason: strict risk management sits behind each.

Choose a method that fits you, not the "most profitable" one. The best strategy is the one you understand deeply and can repeat mechanically. Anton trades from levels on his phone, Pyotr trades pure structure without a single indicator, Maru Joshua runs four indicators on a single Bitcoin. All of them succeeded because each turned their approach into a system.

Start small and scale on evidence. The through-line advice from almost every trader: take a small account, confirm the method works consistently, and only then increase capital.

Want to go deeper on the Fibonacci grid — the most popular tool in this breakdown? There's a full longread in the Upscale Library.

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Frequently Asked Questions

Which strategy is most popular among prop traders who get payouts?

Among the Upscale traders we studied, the most common tool is Fibonacci. Second comes Smart Money Concepts (liquidity, market structure, order blocks), then trading from levels, indicator systems, and volume analysis. Most traders combine several approaches rather than using one in its pure form.

Do you need indicators to get payouts?

No. Some traders use no indicators at all — Pyotr, for example, builds everything on liquidity and market structure. Others use a minimum: Alexey withdrew $412 with a single Bollinger Bands setup. The working principle isn't the number of indicators but the simplicity and repeatability of the system.

Which strategy is best for a beginner?

The one a beginner understands deeply and can repeat mechanically. Based on the traders we studied, the easiest starting points are trading from levels (support/resistance) or a single indicator with strict risk management. Complex multi-timeframe systems like SMC demand more experience in reading context.

How much do traders who get payouts risk per trade?

Between 0.5% and 2% of the account per trade — a rule every trader we studied follows without exception, even with aggressive profit targets.

What risk/reward ratio do profitable traders use?

At least 1:2, more often 1:3. For some it's higher: up to 1:6, and even 8:1. A high risk/reward keeps you profitable even with a win rate below 50% — one trader's win rate was just 29–47%.

What win rate do you need to get payouts in prop trading?

A high win rate isn't required — what matters is the pairing of win rate and risk/reward. One trader's win rate was just 29–47%, but a high R:R (up to 1:6) kept him profitable; another ran around 70% at an R:R of 2.7–3.65. A strategy can be profitable with a low win rate and high R:R, or the reverse, as long as the expectancy is positive.