Market Control and Quarterly Shifts Insights

Oct 13, 2024

ICT Mentorship - January 2017 Lesson 1.1

Introduction

  • Focus: Implementing macro analysis using quarterly shifts and EPTA data ranges.
  • Objective: Understand if markets are truly random or controlled through algorithms.
  • Belief: Markets are engineered with price delivery algorithms, particularly in Forex.

Market Randomness vs. Control

  • If markets were random, predicting them reliably would be impossible.
  • ICT belief: Markets are 100% engineered, controlled to the pip.
  • Ability to predict specific price levels suggests non-randomness.

Understanding Quarterly Market Shifts

  • Occur in all asset classes, not just Forex.
  • Every 3-4 months, market structure shifts to generate new trader interest.
  • Important to analyze markets on a macro level (monthly, weekly, daily).

EPTA Data Ranges

  • Algorithmic price delivery is controlled within data ranges.
  • Central banks set prices and allow movements within predefined daily ranges.

Quarterly Shifts and Market Structure

  • Market shifts approximately every three months, influencing directional bias.
  • Use macro-level analysis to anticipate intermediate price swings.
  • Understand these shifts to better manage long-term trades.

Identifying Market Structure Shifts

  • Look back 60, 40, and 20 trading days to identify institutional order flow.
  • Identify significant highs and lows as liquidity reference points.
  • Use these to predict future market movements and structure shifts.

Smart Money Concepts

  • Buy Programs: Successive days of buying, seen across multiple time frames.
  • Sell Programs: Successive days of selling, using opposite criteria.
  • Manipulation seen in the relationship between underlying asset and benchmark.

Practical Application: Forex

  • Analyze underlying currency vs. benchmark for signs of manipulation.
  • Use examples like Dollar Index vs. Euro/USD for practical insights.
  • Apply this understanding across commodities, stocks, and interest rates.

Practical Steps

  1. Look Back: Analyze past data ranges (60, 40, 20 days) for market direction.
  2. Identify Liquidity: Find institutional reference points (highs/lows).
  3. Cast Forward: Predict next market shift within 20-60 trading days.

Example Analysis

  • Dollar Index and Euro/USD analysis for 2015-2016.
  • Use of vertical lines to delineate market shifts and project trading ranges.
  • Expectation of market behavior based on historical data and smart money accumulation.

Conclusion

  • Markets have predictable patterns through engineered price algorithms.
  • Quarterly shifts offer a framework for anticipating market changes.
  • Combine macro analysis with smart money strategies for effective trading.

Note: Further examples and insights will be provided throughout January's content.