I recently came across a very interesting trading case. Italian trader Fabio Valentini accumulated millions of dollars through order flow scalping strategies. This guy has ranked in the top trader standings four times in the Robbins World Cup Trading Championship, with a total return exceeding 350%. His core logic is actually quite simple: combining order flow with volume and price analysis is the key to advancing in trading.

What impressed me most was that he completed over 2,000 trades during the competition. This high trading volume approach generates enough data samples, which is especially helpful for his positive expectancy scalping strategy. It allows him to significantly increase profit expectations while maintaining relatively low overall drawdowns. Fabio Valentini’s main focus is short-term scalping on NASDAQ index futures.

His advice to traders is very practical: first, find your area of expertise. Is it stocks, futures, forex, or cryptocurrencies? Long-term, short-term, or arbitrage? Find the field where you truly understand volatility, can obtain effective information, and can apply suitable strategies. Deeply understand the characteristics, volatility, and the underlying logic behind price movements of an asset. This helps develop market intuition and a feel for trading. He openly admits that trading multiple assets simultaneously didn’t make him money until he focused on one or two, after which his trading skills improved dramatically.

At the operational level, he uses three indicators to execute his strategy. The first step is identifying key levels using the CVD (Cumulative Volume Delta) indicator to determine trend direction. Key levels are mainly supply and demand zones, but can also be price ranges or other structural patterns. CVD is essentially a market pressure detector; it continuously tracks which side—buyers or sellers—is initiating more volume within a price range, then calculates the cumulative volume. If the CVD is declining while the price is rising, it indicates the market is accumulating significant selling pressure, creating a short-term divergence between volume and price. Conversely, if the CVD is rising while the price drops, it suggests accumulation of buying pressure. Since volume often leads price, CVD can provide early signals of potential market reversals.

The second indicator is a large-volume indicator used to verify the true intentions of big funds. Although Fabio Valentini hasn’t disclosed the specific source of this indicator, you can substitute it with TradingView’s volume distribution charts or AICoin’s large order tracking or big trade indicators, which have similar effects. The key is capturing signals of large fund activity to confirm whether the decline in CVD originates from institutional investors.

The third point is whether the price action aligns with volume signals. Only when the price breaks through a key support level and then bounces near large sell orders does he establish a short position. He doesn’t place limit orders in advance at preset prices; instead, he waits until the price reaches the target level and confirms that there are no abnormal large buy orders near large sell orders before entering.

After entering, he sets a stop-loss. His stop-loss is mainly based on order flow and key market structures, such as critical levels, swing highs and lows, or large orders nearby. If the price movement doesn’t meet expectations, he quickly moves the stop-loss to break-even to ensure the trade doesn’t lose money, and can even lock in some profits.

Once in the trade, he continuously monitors market phase changes. When large orders no longer effectively push the price down—say, several large sell orders appear but the price doesn’t decline as expected—the market enters another phase, and the trend may pause or consolidate. At this point, he will decisively close the position. The risk-reward ratio of this trade exceeds 3:1, or even higher, making it a very successful trade.

Dynamic risk management is a core part of Fabio Valentini’s trading strategy. He doesn’t risk a fixed amount on every trade but categorizes trades into three levels: A, B, and C. Level C has the lowest risk, with potential losses only around 1,000 to 1,500 euros; B is medium risk, with a maximum loss of 2,000 euros; A is his top-tier setup, where he believes the statistical advantage is greatest and all signals align perfectly, with risk around 2,500 to 3,000 euros. Each trading day, he starts with low-risk positions and gradually increases risk capital as profits accumulate. This approach ensures that even if losses occur later, they are just profit losses, greatly reducing emotional stress.

He also stipulates that if he loses three times in a day, he immediately stops trading. This indicates that market conditions on that day are not suitable for his strategy. This rule is based on extensive data samples and practical experience optimization.

To learn this method, there are three stages. First, backtesting—using TradingView’s replay feature and historical data to identify tools and timeframes with statistical advantages. Second, paper trading or small-scale trading to test how the strategy performs under real market conditions, checking for stability and drawdown management. Finally, real trading. Any strategy optimization should be cautious; even minor adjustments like adding or removing indicators, changing products, or timeframes should only be made after confirming improvements in the first two stages. This process is essential for building and validating a trading strategy.

He has a saying worth pondering: past data cannot guarantee future results, but having no data guarantees future failure.