Advanced Positioning, Flow, and Sentiment Analysis in Commodity Markets

Bridging Fundamental and Technical Analysis

Mark J. S. Keenan

• Publisher: Wiley
• Year: 2019
• Print ISBN: 9781119603825
• eBook ISBN: 9781119603818
• Edition: 2
• Topic: Business
• Subtopic: Trading
• Index: Business

The definitive book on Positioning Analysis — a powerful and sophisticated framework to help traders, investors and risk managers better understand commodity markets

Positioning Analysis is a powerful framework to better understand commodity price dynamics, risk, and sentiment. It indicates what each category of trader is doing—what they are trading, how much they are trading and how they might behave under a variety of different circumstances. It is essential in isolating specific types of flow patterns, defining behavioral responses, measuring shifts in sentiment, and developing tools for better risk management. Advanced Positioning, Flow and Sentiment Analysis in Commodity Markets explains the fundamentals of Positioning Analysis and presents new concepts in Commodity Positioning Analytics. This invaluable guide helps readers recognize how certain types of positioning patterns can be used to develop models, indicators, and analyses that can be used to enhance performance.

This updated second edition contains substantial new material, including analytics based on the analysis of flow, the decomposition of trading flows, trading activity in the Chinese commodity markets, and the inclusion of Newsflow into Positioning Analysis. Author: Mark J S Keenan, also covers the structure of positioning data, performance attribution of speculators, sentiment analysis and the identification of price risks and behavioral patterns that can be used to generate trading signals.. This must-have resource:

• Offers intuitive and accessible guidance to commodity market participants and risk managers at various levels and diverse areas of the market
• Provides a wide range of analytics that can be used directly or integrated into a variety of different commodity-related trading, investment, and risk management programs
• Features an online platform comprising a wide range of customizable, regularly-updated analytical tools
• Contains an abundance of exceptional graphics, charts, and illustrations
• Includes easy-to-follow instructions for building analytics.

Advanced Positioning, Flow and Sentiment Analysis in Commodity Markets: Bridging Fundamental and Technical Analysis, 2 nd Edition is an indispensable source of information for all types of commodity traders, investors, and speculators, as well as investors in other asset classes who look to the commodity markets for price information.

CHAPTER 1
Advanced Positioning, Flow, and Sentiment Analysis in Commodity Markets

Chapter objectives

• 1.1 Positioning Analysis – What Is It?
• 1.2 The History of Positioning Data, the COT Report, and the Agencies that Provide the Data
• 1.3 Misunderstandings and Issues in Positioning Analysis
• 1.4 Futures and Options Data

This book focuses on Positioning Analysis. It is based on new material, but also updates and builds significantly on some of the work in the previous book, Positioning Analysis in Commodity Markets – Bridging Fundamental and Technical Analysis, by Mark Keenan.

New material includes analytics based on the analysis of flow, the decomposition of trading flows, trading activity in the Chinese commodity markets, the inclusion of newsflow into Positioning Analysis, and how machine learning can provide insight into trading relationships.

This chapter introduces Positioning Analysis and positioning data and addresses some of the more common misunderstandings and issues in this area.

1.1 Positioning Analysis – What Is It?

Positioning Analysis is one area of research that provides a powerful framework to better understand price dynamics, risk, sentiment, and behaviour in commodity markets.

Based on standard positioning data and bridging aspects of fundamental and technical analysis, the approach builds on how certain types of positioning patterns – both within the data and in the context of changes in variables like price, curve structure, fundamentals such as inventory, seasonal factors, exchange rates, changes in the broader macroeconomic environment, and the levels of risk and uncertainty in the market – can be used to develop models, indicators, and analyses. These lead to the generation of robust trading signals that can be either used directly or integrated into a variety of different trading, investment, and risk management programmes to enhance performance.

Positioning data shows us who is trading what, and how much they are trading. Positioning Analysis helps us identify behavioural patterns in the data and to understand how changes in specific variables can affect positioning, impact sentiment, and drive price.

1.1.1 Positioning Data

Positioning data in commodity markets is generated by attributing exchange-traded futures and options positions between specific groups or categories of traders. It gives an idea of what each category of trader has been doing and the extent to which they have done it.¹

Positioning data is the breakdown of open interest on a weekly basis, between traders in each category according to their long, short, and, where reported, spreading positions. Futures open interest and combined futures and options open interest are typically reported separately, with the options positions reported on a delta-adjusted basis. Only reportable positions, defined as those positions that exceed specific reporting thresholds, are broken down, meaning that between 70% and 90% of open interest, on average, is categorised. The remaining positions are reported as a single group called non-reportables. Importantly, positioning data also includes the number of traders in each long, short, and spreading category.

1.1.2 Positioning Analysis – Bridging Fundamental and Technical Analysis

The analysis of changes in positioning data – Positioning Analysis – makes it possible to define behavioural responses, quantify shifts in sentiment, isolate specific types of flow patterns, and develop tools and signals for better trading, investment and risk management.

In this respect, it is like technical analysis but with more emphasis on behavioural patterns. In many cases, behavioural patterns take a long time to change, so understanding how traders have behaved in the past with the help of Positioning Analysis allows useful decisions to be made in the future.

Positioning Analysis bridges fundamental and technical analysis in two ways; firstly, it is agnostic to whether a position was established because of a fundamental or technical reason; and, secondly, insights from Positioning Analysis can be used to enhance both fundamentally and technically driven trading strategies.

1.1.3 Positioning Signals, Indicators, Models, and Analyses

Positioning Analysis makes up a substantial proportion of this book and COT data is therefore used extensively.

Most of the trading signals, indicators, and models in this book use speculative positioning data. This has been done both in the interest of space and also because the motivation behind the data is intuitive, meaning that we understand speculators are seeking to profit from their trading, as opposed to it being a function of hedging activity. Unless otherwise specified, all the signals, indicators, models, and analyses in this book can be applied to the positioning data in other trader groups to help formulate a complete picture of the overall positioning landscape in a commodity. In doing so, however, an understanding of the trade motivation behind all the different trader categories is essential in helping to gauge how price, curve structure, and sentiment may evolve.

The ideas, insights, and concepts behind the signals, indicators, models, and analyses, collectively the ‘analytics’, in this book have been developed over the last 20 years by the author. In many cases, their construction is unique, but in all cases, the approach is robust, intuitive, and accessible to commodity market participants and risk managers on a variety of levels.

A sizeable proportion of the analysis in this book is open to interpretation, and there are often a variety of different conclusions that can be drawn from the data with different ways to respond. Commodity price action driven by positioning dynamics is often linked to sentiment and behavioural patterns, which can change and evolve over time. This can lead to the formation and establishment of new patterns and relationships as different types of market participants enter and leave the market, and as new price drivers emerge.

This book provides a wide range of different analytics to help understand positioning dynamics and to track how relationships evolve. It is important to note that the analytics, how results and data are interpreted, and what conclusions are drawn throughout this book are by no means exhaustive or final.

Significant literature and several excellent books already exist that cover many of the areas of how positioning data is defined and generated.² The aim of this book is not to re-do this work in any capacity, but is instead to establish and develop Positioning Analysis as a trading, investment, and risk management tool.

In Chapter 2, however, a complete overview of how positioning is broken down on every level for a commodity is given. Section 2.1 is vital as it shows how different positioning categories are related to each other. Appendix 2, taken directly from many of the official sources including the CFTC, the ICE, and the LME, also provides valuable information.

1.2 The History of Positioning Data, the COT Report, and the Agencies that Provide the Data

The Commodity Futures Trading Commission (CFTC) website explains that positioning data in commodities has been around since 1924 when the Grain Futures Administration of the US Department of Agriculture (USDA) published its first comprehensive annual report of hedging and speculation in regulated futures markets.^3,4

In 1962, positioning or commitment of traders (COT) data, as it became referred to, was published each month. In 1990, the CFTC started publishing data mid-month and month-end, in 1992 every two weeks, and then in 2000 on a weekly basis. Current and historical COT data is now available on the CFTC website, going back to 1986 for futures-only reports, to 1995 for futures and options combined reports, and to 2006 for the supplemental and disaggregated reports. A more detailed history of the CFTC COT data is also given in Appendix 1.

In addition to the COT data published by the CFTC, almost identical COT data is published by the Intercontinental Exchange (ICE) for the commodity markets traded on the ICE. The ICE includes markets like Brent and gasoil.

The London Metal Exchange (LME) also publishes a COT report for industrial metals which, as shown in Section 2.2, has some significant differences to the CFTC and ICE COT reports. The Shanghai Futures Exchange (SHFE) publishes a form of positioning data called Daily Ranking data, where the volume and open interest (long and short) rankings, including changes from the previous day, are reported for the top 20 members in each commodity.⁵ This data is, however, entirely different from the CFTC, ICE, and LME COT reports and is covered briefly in Section 2.3.2.

1.3 Misunderstandings and Issues in Positioning Analysis

Positioning data can provoke strong opinions about its validity and usefulness – and is therefore not unlike...

Table of contents

• Cover
• Table of Contents
• ABOUT THE AUTHOR
• ACKNOWLEDGEMENTS
• PREFACE
• ABOUT THE COMPANION WEBSITE
• INTRODUCTION
• CHAPTER 1: Advanced Positioning, Flow, and Sentiment Analysis in Commodity Markets
• CHAPTER 2: The Structure of the Positioning Data
• CHAPTER 3: Performance Attribution – An Insight into Sentiment and Behavioural Analysis?
• CHAPTER 4: Concentration, Clustering, and Position Size – Price Risks and Behavioural Patterns
• CHAPTER 5: ‘Dry Powder (DP)’ Analysis – An Alternative Way to Visualise Positioning
• CHAPTER 6: Advanced DP Analysis – Deeper Insights and More Variables
• CHAPTER 7: Decomposing Trading Flow and Quantifying Position Dynamics
• CHAPTER 8: Overbought/Oversold (OBOS) Analysis – The Intersection of Extremes
• CHAPTER 9: Advanced OBOS Analysis – Extremes in Sentiment and Risk
• CHAPTER 10: Sentiment Analysis – Sentiment Indices and Positioning Mismatches
• CHAPTER 11: Newsflow in Positioning Analysis
• CHAPTER 12: Flow Analysis – The ‘Flow Cube’ and the ‘Build Ratio’ in Commodity Markets
• CHAPTER 13: Chinese Commodity Markets – Analysing Flow
• CHAPTER 14: Machine Learning – A Machine's Perspective on Positioning
• APPENDIX 1: History of the COT ReportHistory of the COT Report
• APPENDIX 2: The COT ReportsThe COT Reports
• INDEX
• End User License Agreement