Title: An Overview of Dr. Glen Brown’s Market Expected Moves Hypothesis (MEMH)

Abstract:

This paper aims to provide a comprehensive understanding of Dr. Glen Brown’s Market Expected Moves Hypothesis (MEMH). The hypothesis presents a predictive model for anticipating the probable extent of price movements of financial assets. By integrating the concept of Dynamic Adaptive ATR Trailing Stops (DAATS) and theoretical ratios of expected moves, it offers an innovative way of predicting market fluctuations.

Introduction:

The global financial market is an intricate web of variables and constants, with each asset having its unique factors that contribute to its price movements. To predict these movements, various statistical and mathematical models have been developed over the years. Among these models, Dr. Glen Brown’s Market Expected Moves Hypothesis (MEMH) stands out for its unique approach to predict market movements using dynamic Adaptive ATR Trailing Stops (DAATS).

The Market Expected Moves Hypothesis:

Dr. Glen Brown’s MEMH is built upon the concept of expected moves derived from the DAATS. It incorporates an algorithmic approach that calculates the probable extent of price movements in the financial market. MEMH proposes a specific formula:

Market Daily Average Expected Moves (MDAEM) = 0.6375 * Average Dynamic Adaptive ATR Trailing Stops (DAATS) on M1440.

In the context of the Forex market, the MEMH offers another formula for determining the average expected moves:

Average Market Expected Moves = (Sum of DAATS on M1440 for the 28 Major Forex pairs) / 224 * 0.6375.

These formulas represent theoretical percentages of how frequently and to what extent these expected moves should manifest, and they form the core of the MEMH.

Dynamic Adaptive ATR Trailing Stops (DAATS):

The DAATS is a stop-loss method that adapts according to market volatility. DAATS utilizes the Average True Range (ATR), a measure of market volatility, and dynamically adjusts as the market evolves. It provides an objective method to place and trail stop-losses, which is an essential factor in risk management in trading.

Empirical Application:

An application of the MEMH can be demonstrated using an example where the DAATS values for 28 major forex pairs are given. Using these values, one can calculate the Market Daily Average Expected Moves (MDAEM) using the MEMH formula. This empirical application provides valuable insights into the potential usefulness and practicality of the hypothesis.

Conclusion:

The MEMH, by Dr. Glen Brown, provides a promising framework for predicting price movements in the financial market. By harnessing the power of DAATS and the principle of expected moves, the hypothesis offers a comprehensive and nuanced perspective on market fluctuations. This framework could potentially contribute significantly to financial modeling and predictive analysis, thereby enhancing trading strategies and decision-making processes in the financial market.

Title: An Application of Dr. Glen Brown’s Market Expected Moves Hypothesis (MEMH)

Abstract: The following paper explores a practical application of Dr. Glen Brown’s Market Expected Moves Hypothesis (MEMH), demonstrating its utility in predicting financial market movements. The analysis focuses on a set of Dynamic Adaptive ATR Trailing Stops (DAATS) values for 28 major forex pairs, utilizing the MEMH formula to compute the Market Daily Average Expected Moves (MDAEM).

Introduction: Predicting the financial market’s behavior is a challenging endeavor that calls for sophisticated tools and methodologies. Dr. Glen Brown’s Market Expected Moves Hypothesis (MEMH) offers an innovative approach to forecasting potential price movements of financial assets. This paper illustrates a practical application of MEMH by calculating the Market Daily Average Expected Moves (MDAEM) based on a given set of DAATS values for 28 major forex pairs.

Application of MEMH: The MEMH incorporates Dynamic Adaptive ATR Trailing Stops (DAATS), custom-tailored for different trading timeframes, into its calculations to predict price movements. For the application in focus, we consider the following DAATS values for 28 major forex pairs: [7878, 11050, 12919, 7277, 8610, 7004, 6658, 12549, 8172, 5253, 5211, 13106, 14946, 11633, 5256, 8768, 15690, 13358, 11503, 4702, 9450, 6258, 8992, 5642, 12283, 8335, 6533, 4982].

Utilizing the MEMH formula for the Forex market:

Average Market Expected Moves = (Sum of DAATS on M1440 for the 28 Major Forex pairs) / 224 * 0.6375.

we proceed with the following steps:

  1. Summation of DAATS values: We begin by adding up all the provided DAATS values, resulting in a sum of 270859.
  2. Divide by 224: Next, we divide this sum by 224, the factor representing the total number of hours in two weeks (5 trading days a week times 24 hours times 2 weeks), which results in an average of approximately 1209.545.
  3. Multiplication by 0.6375: Lastly, we multiply this average by 0.6375 as per the MEMH formula, yielding a MDAEM of approximately 770.8319463526785.

This MDAEM figure represents the average extent to which we can expect the market to move daily according to the MEMH and the provided DAATS values.

Conclusion: The application of Dr. Glen Brown’s MEMH with real-world data helps illustrate the theory’s practicality and potential usefulness in financial market analysis. By integrating the concept of DAATS with expected market move ratios, the MEMH presents an exciting and novel perspective on predicting market fluctuations, thereby advancing our understanding and strategy building within the financial markets.

Keywords: MEMH, Dr. Glen Brown, DAATS, MDAEM, Forex market, financial market, expected moves, predictive model.