Risk and Reward: Analysing Investor Sentiments in Commodity Market Trading

Abstract

This study aims to explore the dynamics of investor sentiments in commodity market trading, focusing on how risk perception and reward expectations influence decision-making. The research investigates behavioural patterns, market trends, and sentiment-driven trading strategies in emerging economies, with an emphasis on India.
The research employs a mixed-methods approach, combining quantitative analysis of trading data with qualitative surveys of retail and institutional investors. A dataset comprising historical commodity market transactions and sentiment indicators was analysed using econometric and machine learning models. Surveys and interviews were conducted to gather insights into investor perceptions and behavioural biases. Statistical tools and sentiment analysis algorithms were applied to identify patterns, correlations, and the impact of sentiment on market volatility and trading outcomes. The findings reveal a significant correlation between investor sentiment and market performance, with sentiment-driven trading contributing to price volatility. Risk-averse investors demonstrated cautious behaviour during market downturns, while risk-tolerant investors capitalized on speculative opportunities. The study highlights the role of awareness and market education in mitigating behavioural biases and enhancing decision-making. Understanding investor sentiment is pivotal in developing strategies to manage risk and optimize trading outcomes in commodity markets. The study underscores the importance of sentiment analysis tools and investor education programs in promoting market stability and informed trading practices. These insights are particularly valuable for policymakers, market regulators, and investment advisors aiming to foster resilient commodity markets.