# Relative Value

## KW vs CA Hedging Ratio

Introduction In this write-up we study the historical optimal hedging ratio for the KW vs CA spread. This work follows from previous research on the optimal hedging ratio of the C vs S spread. The table below gives the contract specifications of KW and CA. Notice that the tons per contract is basically equivalent, i.e. when sizing up the positions on a ton for ton basis we make use of a one to one ratio.

## Relative Value Long to Short Ratio

Introduction When a simple question does not have a simple answer it might point to something interesting that is worth threading out. The simple question we attempt to solve deals with how to size up a relative value futures pairs trade so that it gives the best risk adjusted return. A couple examples we will consider include Ton for ton Equal notional exposure Equal volatility adjusted notional exposure Equal (at the money) implied volatility adjusted notional exposure Hedging ratio from cointegration test Machine Learning solution We also explore the possible evolution of the hegding ratio as a function of fundamentals or seasonal input features, or even the shape of the futures curves of the underlying commodities.

What is the optimal way to manage a relative value commodity futures trade after it has been identified as a possible opportunity?

## Corn vs European Wheat Fundamental Model

Introduction In previous posts we have explored ideas on how to construct fundamental models for forecasting the price of corn and soybean. These models used as input parameters the stock-to-usage numbers calculated from the monthly WASDE reports together with the Dollar index, the mean value of crude in the previous month and the Ruble vs Dollar exchange rate. The aim of this report is to extend these results to a spread between two related commodities, in this case Corn and European wheat.

## Kansas vs European Wheat Fundamental Model

Introduction In previous posts we have explored ideas on how to construct fundamental models for forecasting the price of corn and soybean. These models used as input parameters the stock-to-usage numbers calculated from the monthly WASDE reports together with the Dollar index, the mean value of crude in the previous month and the Ruble vs Dollar exchange rate. The aim of this report is to extend these results to a spread between two related commodities, in this case Kansas and European wheat.

## Corn vs Soybean Fundamental Model

Introduction In previous posts we have explored ideas on how to construct fundamental models for forecasting the price of corn and soybean. These models used as input parameters the stock-to-usage numbers calculated from the monthly WASDE reports together with the Dollar index, the mean value of crude in the previous month and the Ruble vs Dollar exchange rate. The aim of this report is to extend these results to a spread between two related commodities, in this case corn and Soybeans.

## Corn vs Kansas Wheat Fundamental Model

1 Introduction 2 Modeling the Spread 3 Modeling the Ratio 4 Roll Structure 4.1 Corn Calendars 4.2 Kansas Wheat Calendars 5 Hypothetical Scenario 6 Remarks 1 Introduction In previous posts we have explored ideas on how to construct fundamental models for forecasting the price of corn and wheat. These models used as input parameters the stock-to-usage numbers calculated from the monthly WASDE reports together with the Dollar index, the mean value of crude in the previous month and the Ruble vs Dollar exchange rate.

## Relative Value Commodity Universe

1 Introduction 2 Nomenclature 3 Curve Shape 3.1 Backwardation and Contango 3.2 The driver of long-term returns 4 Relative Value commodity Universe 4.1 Calendar Spreads 4.1.1 Bull Spreads 4.1.2 Bear Spreads 4.2 Inter-Commodity Spreads 4.2.1 Convergence Trades 4.2.2 Divergence Trades 1 Introduction In this document, we give some detail about the relative value commodity universe in which the Polar Star Limited fund invests.