VICTORIA, Seychelles, Feb. 17, 2026 /PRNewswire/ — Retail online trading on financial markets has moved away from indicator-first chart reading toward data, contextVICTORIA, Seychelles, Feb. 17, 2026 /PRNewswire/ — Retail online trading on financial markets has moved away from indicator-first chart reading toward data, context

Gulf Brokers: Trend Change, Traders Move from Indicators to Complex Approach

2026/02/17 17:45
3 min read

VICTORIA, Seychelles, Feb. 17, 2026 /PRNewswire/ — Retail online trading on financial markets has moved away from indicator-first chart reading toward data, context, and a repeatable process. Instead of searching for a perfect signal, majority of traders focus on understanding why prices move and building rules that work across different market conditions. According to the analysis of Gulf Brokers‘ clients behavioral patterns, trading is evolving simultaneously in three directions: More market data and context. Automation and AI as execution and analysis tools.

Fewer Indicators More Market Data

Traders rely less on universal indicators such as the RSI or MACD as the primary decision driver and focus more on market-specific information. Price action is used to read market structure, breaks, reactions at key zones, and overall context (trend vs. range). Liquidity is equally important. Markets often move toward areas where orders cluster, around obvious highs/lows and typical stop-loss placements, so price can sweep a level before moving in the expected direction.

Order flow and volume tools add details within the candle. Aggressive buyers/sellers, volume profiles, and imbalances can confirm whether a move has real participation or is weak. The takeaway is simple. It’s not about adding more tools, but about understanding the mechanics behind price movement.

Automation and Algo Trading

Algorithmic trading is a natural extension of rules. If you can define entries, exits, stop-loss logic, and position sizing, you can automate them. Automation enhances repeatability and discipline by enforcing execution rules and reducing limiting decisions, especially in the area of risk controls.

AI in real trading is typically used to filter and evaluate data, not to predict markets. Reinforcement learning and advanced models may seem impressive, but their success depends on the quality of the data, realistic testing, and risk constraints such as fees, slippage, and changing market regimes. The more sophisticated the system, the more important performance measurement and clear limits become.

Psychology, Risk Management, and Process

The biggest long-term differentiator is a professional approach to risk: fixed risk per trade, daily/weekly loss limits, and rules for managing drawdowns. The focus shifts from hunting signals to managing exposure, protecting capital, and staying consistent when conditions are not ideal.

Process tools make this practical. A trading journal tracks the entry reason, context, execution quality, emotions, and outcome, so you can identify what truly works and what repeatedly fails. A routine also includes rules for when not to trade and a review loop that turns mistakes into system improvements.

To stay competitive, simplify your approach, focus on meaningful data, test realistically, and adhere to strict risk management rules, the report by Gulf Brokers concludes: The modern edge is rarely one secret strategy. It is how they collect information, how they execute consistently, and how they control risk when the market changes.

Cision View original content:https://www.prnewswire.com/news-releases/gulf-brokers-trend-change-traders-move-from-indicators-to-complex-approach-302689338.html

SOURCE Gulf Brokers

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