MARK J S KEENAN is Managing Director, Global Commodities Strategist, and Head of Research for Asia-Pacific at Société Générale Corporate & Investment Bank (SG CIB) based in Singapore. He has over 20 years of research, trading and investment experience across all major commodity markets. Mark has worked in asset management, risk management and investment banking in both London and Singapore and developed a number of innovative trading, investment and risk management solutions for corporates, trade houses, investment institutions and hedge funds. He appears regularly on CNBC and Bloomberg television and is quoted widely in global press and media channels. He has a master's degree in Molecular and Cellular Biochemistry from Oxford University.

About the Author xi

Acknowledgements xiii

Preface xv

About the Companion Website xvii

Introduction 1

Chapter 1 Advanced Positioning, Flow, and Sentiment Analysis in Commodity Markets 7

1.1 Positioning Analysis – What is It? 8

1.2 The History of Positioning Data, the COT Report, and the Agencies that Provide the Data 10

1.3 Misunderstandings and Issues in Positioning Analysis 10

1.4 Futures and Options Data 17

Chapter 2 The Structure of the Positioning Data 19

2.1 The Structure of Positioning Data 20

2.2 Positioning Data for the London Metal Exchange (LME) – The MiFID Classifications 28

2.3 Other Types of Positioning and Flow Data 33

2.4 The Structure of Commodity Markets 34

Chapter 3 Performance Attribution – An Insight into Sentiment and Behavioural Analysis? 45

3.1 The Proliferation of Speculative Positioning Data 46

3.2 Why is Positioning Data Interesting 47

3.3 Measuring the Skill or Performance of MMs 48

3.4 Net Futures Positioning vs Net Trader Number Positioning or Alignment 55

Chapter 4 Concentration, Clustering, and Position Size – Price Risks and Behavioural Patterns 59

4.1 Concentration, Clustering, and Position Size 60

4.2 Concentration, Clustering, Position Size, and Their Relationship to Price Over Time 62

Chapter 5 ‘Dry Powder (DP)’ Analysis – An Alternative Way to Visualise Positioning 71

5.1 Dry Powder (DP) Analysis 72

5.2 DP Indicator Variations 75

5.3 DP Indicators and Trading Signals 82

Chapter 6 Advanced DP Analysis – Deeper Insights and More Variables 87

6.1 Advanced DP Indicator Charts 88

6.2 DP Indicators, Price, and Curve Structure 96

6.3 DP Hedging Indicators 99

6.4 DP Factor, Fundamental, and Currency Indicators 101

Chapter 7 Decomposing Trading Flow and Quantifying Position Dynamics 111

7.1 Decomposing Net Positioning – The Methodology 112

7.2 Decomposing Long and Short Positioning – The Methodology 115

7.3 Who Has Been Driving Prices? 116

7.4 Who is Trading with Whom? 118

7.5 The Impact on Prices 122

7.6 Speed of Positioning Changes 124

Chapter 8 Overbought/Oversold (OBOS) Analysis – The Intersection of Extremes 127

8.1 The Overbought/Oversold (OBOS) Philosophy 128

8.2 Constructing the Framework 128

8.3 The OBOS Concentration Indicator 132

8.4 Key Attributes of the OBOS Approach 133

8.5 Behavioural Patterns within the Boxes 134

8.6 OBOS Variations 138

8.7 The DP/OBOS Hybrid Indicator 141

Chapter 9 Advanced OBOS Analysis – Extremes in Sentiment and Risk 147

9.1 The OBOS Framework – Clustering and Position Sizes 147

9.2 OBOS Factor Indicators 155

9.3 Commodity Risk Premia – Positioning Analysis and Risk Management 159

Chapter 10 Sentiment Analysis – Sentiment Indices and Positioning Mismatches 163

10.1 The Difference between Trader Numbers and Open Interest 164

10.2 Trader Sentiment (TS) Indices 166

10.3 Mismatches in Positioning and Price Inflexion Points 172

Chapter 11 Newsflow in Positioning Analysis 177

11.1 Newsflow Data in Commodity Markets 178

11.2 Building Basic Newsflow Indices 181

11.3 Combining Newsflow with Positioning 186

11.4 Economic Policy Uncertainty 190

Chapter 12 Flow Analysis – The ‘Flow Cube’ and the ‘Build Ratio’ in Commodity Markets 191

12.1 The Flow Cube 192

12.2 The Flow Cube down the Forward Curve 198

12.3 The LBMA-i Trade Data 202

Chapter 13 Chinese Commodity Markets – Analysing Flow 203

13.1 The Chinese Commodity Exchanges 203

13.2 The Size of the Chinese Commodity Exchanges 205

13.3 Speculative vs Hedging Activity in Chinese Commodities 208

13.4 The Flow Cube and Build Ratio in Chinese Commodities 210

13.5 The OBOS Framework and the Speculation Ratio 212

Chapter 14 Machine Learning – A Machine’s Perspective on Positioning 215

14.1 Introduction to Machine Learning (ML) 216

14.2 Decision Trees 217

14.3 Feature Importance 227

14.4 Random Forests 229

14.5 Using ML to Trade 232

Appendix 1 History of the COT Report 235

Appendix 2 The COT Reports 237

Index 249

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