Wheat

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 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.

Wheat price vs Stock-to-Usage

1 Introduction 2 Deterministic Model 2.1 Deterministic Model Sensitivity 2.2 Deterministic Curve Prediction 3 Probabilistic Model 3.1 United States HRW Stock-to-Usage 3.2 United States Total Wheat Stock-to-Usage 3.3 World Stock-to-Usage 3.4 World Stock-to-Usage without China 3.5 Mean Crude 3.6 Dollar Index 3.7 Ruble 4 Ensemble Model 4.1 Crude Sensitivity 4.2 United States HRW Stock-to-Usage Sensitivity 4.3 World Stock-to-Usage Sensitivity 4.

Chicago and Matif Wheat Correlations

1 Introduction 2 Lead-Lag 3 Return Distributions 4 Return Correlations 5 Linear Model 6 The Spread 7 Remarks 1 Introduction Our bread and butter trades are intercommodity spreads. In this write-up we perform a correlation study between Chicago and Matif wheat. 2 Lead-Lag It has been stated that Historically, during the May-Aug weather period CBOT has had a tendency in certain years to rally appreciably with a notable lag in CA prices.