Trend Following

A Better Long Only Commodity Product

We show some examples of how to create a better long only commodity product and add some shameless plugs at the end.

Daily Pseudo Bridgeton File Explanation

Introduction Some time ago we performed an events study on the Bridgeton Orders. In this write-up we tried to see if there were any short term signals we could possible extract from their daily data. The results were inconclusive but the interest in the data still remains. The data they generate basically amounts to reverse engineering trend following CTA signals to find prices where there might be significant buying and selling.

Debunking Long-Only Commodity Inveting

A question we get asked often is if we have a long-only commodities product or if we can give investors access to long only commodities exposure. In this talk, we show why this is, in general, not a good idea. We do this by studying the Bloomberg …

Debunking Long-Only Commodity Investing

1 Introduction 2 Bloomberg Commodities Index 3 Reconstructing Bloomberg Commodities Index 3.1 Simplifying the weights 3.2 Curve Shape 3.3 The effect of roll yield 3.4 Index Proxy 3.5 Index Proxy Performance Attribution 3.6 Curve Shape and Annualised Return 3.7 Long Backwardated Commodities 3.8 Short Contango Commodities 3.9 Combination Portfolio 4 Trend System 4.1 BCOM commodities 4.2 Larger universe of commodities 5 Conclusions 1 Introduction We get asked often is if we have a long-only commodities product or if we can give investors access to long-only commodities exposure.

Polar Star Quantitative Commodity Fund

We give an overview of our thesis in systematic investing in the global commodities markets.

Designing a trend strategy

1 Introduction 2 P&L by trendy series 3 P&L by trendy series and rules 3.1 SN1 3.2 SN2 3.3 SN3 3.4 SN4 3.5 SN5 3.6 SN6 3.7 SN7 3.8 TR1 3.9 TR2 3.10 TR3 3.11 TR4 3.12 TR5 3.13 TR6 3.14 TR7 4 Adding bells and whistles 4.1 Instrument weight estimates (IWE) 4.2 Instrument and forecast weight estimates (IFWE) 4.3 Instrument, forecast weight and diversification multiplier estimates (IFDWE) 4.