Since the prices in the agricultural commodity market surged in 2008 and 2011 many articles investigated these turbulences from different perspectives.
However, neither fundamental factors nor increased financial speculation provides a completely satisfactory explanation on this complex topic. Our study therefore tries to capture all these factors in a single approach and investigates the impact of investor sentiment on wheat futures returns. We construct an investor sentiment index out of monthly data from the period 2000 to 2013 by conducting a principal component analysis (PCA) with a set of well-established sentiment proxies. In particular, we employ three equity market proxies suggested by Baker & Wurgler (2007) and three wheat market specific sentiment proxies, in order to obtain a tailored investor sentiment index.
The sentiment index is statistical significant at the 95 per cent significance level and predicts about 2.45 per cent of the total variation in the subsequent month wheat futures returns. The results are also robust after controlling for fundamental factors in an extended multiple linear regression analysis. Our sentiment index therefore proves that investor sentiment impacts wheat futures returns, although further research is needed to verify this relationship.
Table of Contents
1 INTRODUCTION
2 LITERATURE REVIEW
2.1 Fundamental and political factors influencing food prices
2.1.1 Demand from developing countries
2.1.2 Increasing oil price
2.1.3 Expanded biofuel production
2.1.4 Low stocks in agricultural commodities
2.1.5 Adverse meteorological conditions
2.1.6 Food policies
2.1.7 Other fundamental factors
2.2 Financialization in the agricultural commodity market
2.2.1 Increasing financial speculation has no impact on agricultural commodity markets
2.2.2 Increasing financial speculation is beneficial
2.2.3 Financial speculation is harmful to agricultural commodity markets
2.3 Evidences for the impact of investor’s sentiment on asset prices
3 ANALYSIS OF POTENTIAL SENTIMENT PROXIES
3.1 AAII Investor Sentiment Survey
3.1.1 AAII data and limitations
3.2 Implied volatility of S&P500 index options
3.3 First-day returns on initial public offerings
3.3.1 First-day IPO returns data and limitations
3.4 Closed-end fund discount
3.4.1 Closed-end fund discount data and limitation
3.5 Open interest in the wheat futures market
3.5.1 Open interest data and limitations
3.6 Trading volume in the wheat futures market
3.6.1 Trading volume data and limitation
3.7 Wheat futures returns
3.7.1 Limitations of wheat futures returns
4 EMPIRICAL EVIDENCE
4.1 Descriptive Statistics of relevant variables
4.2 Construction of the composite sentiment index
4.2.1 Preliminary sentiment index
4.2.2 Controlling for macroeconomic influences
4.2.3 Controlling for the capital market
4.2.4 Comparison to other sentiment indices
4.2.5 Does the sentiment index capture mood swings in the wheat market?
4.3 Interdependence between investor sentiment and returns on wheat futures
4.3.1 Interdependence between SENT┴# and returns on wheat futures
4.4 Dependence between investor sentiment and returns on wheat futures
4.4.1 Simple linear time series regression analysis
4.4.2 Multiple linear time series regression analysis
5 CONCLUSION
Research Objectives and Themes
The research investigates the influence of investor sentiment on wheat futures returns from 2000 to 2013, seeking to determine if mood swings beyond fundamental factors explain market price fluctuations.
- Construction of a bespoke investor sentiment index for agricultural commodity markets.
- Evaluation of the impact of financialization on wheat futures returns.
- Analysis of the relationship between behavioral finance proxies and market price discovery.
- Application of principal component analysis (PCA) to derive a composite sentiment measure.
- Empirical testing of predictive power through linear and multiple regression models.
Excerpt from the Book
1 Introduction
World market prices for several staple foods reached an all-time high in 2008 with price increases of up to 431 per cent (rice) compared to the price level in January 2002 (Trostle 2011). This enormous price surge particularly affected people in developing countries, who spend a high percentage of their total income on food. Afterwards food riots and demonstrations against rising food prices caused political instability and social unrest in some parts of Asia and Africa. For instance, in Bangladesh, 20 people were injured by the police while protesting against rising food prices (Al Jazeera 2008). High agricultural commodity prices are even thought to have played an important role in the emergence of the ‘Arab Spring’ in 2010, because many North African countries have to import a majority of their food at world market prices (The Economist 2012).
The global media drew attention to these protests and investigated the causes of soaring prices for staple crops. A large public debate emerged, attempting to explain the ‘food price crisis’. A shortcoming of the debate was that it gave primarily consideration to only two factors. First the growing demand from developing countries like China was thought to be the main fundamental driver of food prices. Second the ever increasing speculation by financial institutions was brought to light by the NGOs and media, accusing the speculators of distorting commodity prices. The reputation, and trustworthiness of financial institutions was already damaged due to the Financial Crisis of 2008 and after. Their reputation was further damaged when prominent people, working within the financial industry, agreed that speculation had boosted food prices. But this highly complex topic was often simplified down to easy, one dimension, causalities, and lacked findings based on in-depth analysis. Resentment of financial speculators is not a new phenomenon, dating as far back as Hume (1888) and Smith (1893), who both already accused commodity traders of causing market distortions. This mistrust is often built on insufficient information and knowledge about the workings of the financial markets, and particularly the futures market.
Summary of Chapters
1 INTRODUCTION: This chapter provides context regarding the global food price crisis and the debated roles of fundamental drivers and financial speculation.
2 LITERATURE REVIEW: An overview of existing academic research on fundamental factors and the financialization of agricultural commodity markets is provided.
3 ANALYSIS OF POTENTIAL SENTIMENT PROXIES: This section details the selection and limitations of various indicators used to quantify investor sentiment in the US market.
4 EMPIRICAL EVIDENCE: This chapter covers the construction of a composite sentiment index, its validation, and its predictive power regarding wheat futures returns through regression analysis.
5 CONCLUSION: The study summarizes the findings, confirming that investor sentiment serves as a significant predictive factor for wheat futures returns.
Keywords
Agricultural Commodities, Wheat Futures, Investor Sentiment, Financialization, Speculation, Efficient Market Hypothesis, Principal Component Analysis, Commodity Index Traders, Market Volatility, Behavioral Finance, Predictive Modeling, Regression Analysis, Food Price Crisis, Risk Premium, Market Liquidity.
Frequently Asked Questions
What is the core focus of this research?
The research examines whether investor sentiment, beyond fundamental economic factors, influences the returns of wheat futures contracts.
What are the primary thematic areas covered?
The study spans fundamental drivers of food prices, the role of financial speculation, and the application of behavioral finance theories to the agricultural commodity sector.
What is the main research question?
The primary question is whether an aggregated investor sentiment index can effectively predict returns in the wheat futures market.
Which scientific methods are employed?
The author utilizes Principal Component Analysis (PCA) to construct a sentiment index, followed by univariate and multiple linear regression models to test predictive validity.
What does the main body of the paper discuss?
The main body evaluates various sentiment proxies, details the methodology for creating a composite index, and presents empirical results from regression models controlling for macroeconomic variables.
How can this work be described using keywords?
Key topics include wheat futures, investor sentiment, financialization, behavioral finance, and commodity price discovery mechanisms.
How is the investor sentiment index constructed?
The index is built by performing a PCA on six distinct sentiment proxies—including VIX, IPO returns, and closed-end fund discounts—after controlling for macroeconomic factors.
What is the conclusion regarding the relationship between sentiment and wheat prices?
The study concludes that investor sentiment is a statistically significant factor that influences future wheat returns, effectively closing a literature gap in the agricultural commodity market.
- Citar trabajo
- Simon Scholl (Autor), 2013, Drivers of agricultural commodity prices since 2000, Múnich, GRIN Verlag, https://www.grin.com/document/264600
