Date of Graduation

8-2024

Document Type

Thesis

Degree Name

Master of Science in Agricultural Economics (MS)

Degree Level

Graduate

Department

Agricultural Economics and Agribusiness

Advisor/Mentor

McKenzie, Andrew

Committee Member

Anderson, Andrew

Second Committee Member

Park, Eunchun

Keywords

Agriculture; Commodities; Futures; Trading

Abstract

This thesis investigates the economic impact of private analyst forecasts on trading strategies in agricultural commodities markets. The primary objective is to assess whether private forecasts of world ending stocks contained in the USDA’s WASDE report provide valuable information for forming profitable trading strategies. The study utilizes panel regression models to analyze the relationship between private forecast accuracy and strategic returns derived from trading strategies based on these forecasts. The research employs unbalanced panel data spanning from January 2011 to April 2021, integrating monthly and yearly indicators to capture temporal patterns. The dataset includes observations from multiple firms, allowing for the exploration of both common behaviors and individual firm effects over time. Statistical analyses reveal that private analyst forecasts significantly influence trading outcomes, with both corn and soybean regression models demonstrating positive and highly significant coefficients for private forecast accuracy. Specifically, traders following strategies based on these forecasts could achieve returns of 6.4819% for corn and 5.1294% for soybeans, underscoring the economic value of private forecasts in agricultural commodities markets. Additionally, market structure dynamics play a crucial role in trading strategy profitability. The analysis identifies significant relationships between market carry and inverse market conditions and strategic returns. Carry markets, characterized by higher futures prices for deferred contracts, yield higher returns, while inverse markets, where deferred contracts trade at lower prices, also provide profitable opportunities, albeit with different dynamics. These findings suggest that understanding market structure is essential for optimizing trading strategies based on private forecasts. Moreover, the persistence of forecasting performance among analysts is explored using Fisher Exact and Chi-Squared Tests. Contrary to expectations, the results indicate no statistically significant association between an analyst's performance in consecutive periods for corn, soybeans, and wheat. This implies that past forecasting accuracy does not reliably predict future performance, challenging the notion of consistent forecasting superiority or inferiority among analysts over time. The implications of these findings are important for traders, market participants, and policymakers. Incorporating private analyst forecasts into decision-making processes can enhance trading strategies and mitigate price risk in agricultural commodities markets. However, caution is advised against relying solely on past performance as an indicator of future forecasting success.

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