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This section features a curated set of educational posts created to help you better understand key trading concepts and market behavior.Β
Whether you're exploring concepts like Elliott Wave, Heikin-Ashi, or regression channels, these resources are designed to support your growth as a trader β with clarity, simplicity, and practical insights.
Elliott Wave Theory, developed by Ralph Nelson Elliott, suggests that the seemingly chaotic movements of financial markets actually follow predictable, repetitive cycles β known as waves. These wave patterns are driven by collective investor psychology and can often be measured and forecast using Fibonacci ratios.Β
Fibonacci-based tools help traders identify potential reversal points, trend targets, and key price zones by applying ratios from the Fibonacci sequence. Common tools include retracements, extensions, channels, fans, and time projections β all widely used to define structure and anticipate market movement.
β’ How to and Where to Apply Fibonacci Extensions & Retracements
β’ How to Apply Fibonacci Fans
β’ How to Apply Fibonacci Channels
β’ Fibonacci Extensions & Retracements β with Pivot Logic
β’ Auto Fib Speed Resistance Fans
β’ Auto Fib Channels
β’ Auto Fib Time Zones + Trend-Based Fib Time
Market cycles are shaped not just by fundamentals or technicals, but by human psychology. From optimism to euphoria, denial to panic, each stage of the cycle reflects shifts in collective trader sentiment. Recognizing these emotional phases helps traders better anticipate turning points, avoid herd mentality, and align with the true structure of the market.
Related Resources:
β’ π§ Fear & Greed Index Script β Visualize shifting market sentiment in real time
β’ π Market Cycles β Educational Post β Understand the emotional phases behind market movements
Volume reflects the strength behind a price move. High volume confirms conviction β signaling that many participants support the direction of a move β while low volume can indicate weakness or hesitation. By analyzing volume in context, traders can better understand trend sustainability, spot potential reversals, and avoid false breakouts.
Related Resources:
β’ π§ Neglected Volume β Script
β’ π Why Volume is the Key Behind Big Price Movements β Educational Article: A closer look at volumeβs role
In day trading, timing isnβt just important β itβs everything. Market activity and volatility vary significantly throughout the trading day, often clustering around session openings, closings, and major news events. Understanding when liquidity peaks and momentum shifts can help traders enter with precision and avoid unnecessary risk.
Related Resources:
β’ π§ Day Trading Booster β Script: Designed to highlight high-probability entry windows during the trading day
β’ π Timing When Day Trading β Educational Guide: Explore the role of session timing, volatility windows, and momentum shifts
The Pitchfork is a classic technical analysis tool used to identify potential support and resistance zones based on three anchor points. By projecting a set of parallel trendlines β including a central median line β it helps traders visualize trend channels and future price trajectories. Itβs especially useful in spotting balanced price movement and structure across timeframes.
Related Resources:
β’ π§ Auto Pitchfork Script β Automatically draws Pitchforks using key swing anchors
β’ π§ Auto Pitchfan Script β An extension of Pitchfork logic with wider angle projections
β’ π How to Apply Pitchfork β Educational Guide β Learn the method, anchoring, and practical use cases
Regression channels use statistical models to map price movement within a trend.
β’ The Linear Regression Channel centers around a best-fit line, with upper and lower bands marking standard deviation zones.
β’ The Raff Regression Channel draws boundaries around the regression line based on the furthest price deviations β resulting in tighter, more adaptive zones.
These tools help traders identify trend direction, strength, and potential reversal points β all through a mathematically grounded approach.
Related Resources:
β’ π§ Linear Regression Channel / Curve / Slope β Script
β’ π What is a Linear Regression Channel? β Educational Post
β’ π§ Raff Regression Channel β Script
β’ π What is a Raff Regression Channel? β Educational Post
Heikin Ashi is a type of candlestick chart that filters out market noise by averaging price data. Unlike standard candles, it smooths trends and makes it easier to identify momentum, direction, and potential reversals. Itβs especially useful for staying in trades longer and avoiding false signals during choppy price action.
Related Resources:
β’ π§ HTF Candles β Script: Overlay higher-timeframe Heikin Ashi candles for better trend clarity
β’ π Heikin Ashi Candlesticks Overview β Educational Guide: Learn how Heikin Ashi works and when to use it
Algorithmic trading uses rule-based logic to execute trades automatically, eliminating emotion and improving consistency. Strategies can range from simple moving average crossovers to complex, multi-condition systems β often deployed via platforms like TradingView or through custom scripts.
By automating entries, exits, and risk parameters, traders can focus more on system design and less on manual execution.
π Intro to Algorithmic Trading β Educational Guide: Understand the core concepts, benefits, and practical applications of automated trading strategies
Stop loss hunting refers to sudden price movements that appear to "grab" clusters of stop orders before reversing. While it's often seen as manipulation, these moves usually reflect natural liquidity dynamics β where large players seek out areas with concentrated orders to efficiently enter or exit positions.
By recognizing common liquidity grab zones, traders can avoid getting trapped and even align themselves with the momentum that follows.
π Understanding Stop Loss Hunting and Liquidity Grabs β Educational Article: Learn how these moves unfold, where they occur, and how to trade them smartly
The MACD (Moving Average Convergence Divergence) began as a simple momentum oscillator based on moving average crossovers. Over time, traders have adapted it into more dynamic tools β incorporating histogram analysis, signal-line shifts, divergence spotting, and even hybrid models that integrate RSI or volume filters.
This post explores how MACD has evolved from a basic indicator into a versatile framework for modern market analysis.
Related Resources:
β’ π§ MACD-X β More Than MACD (Script)
β’ π§ MACD-X Overlay β More Than MACD (Chart Overlay Tool): Visualizes MACD logic directly on price action for clearer decision-making
β’ π The New Ways Traders Use MACD β Educational Article: A look at modern adaptations and use cases beyond the classic crossover
