Using PLS Methodology For Understanding Commodity Market Behaviour And Improving Decision-Making Process
After a long and unexpected financial crisis, a period of rapid growth in China and emerging markets, unstable commodity prices behavior, the commodity trading sector confronts a very different landscape, now. In this context, our paper aims to better anticipate commodity market behavior in order to help the commodity investors to improve their decision-making process.Using the PLS methodology (partial least square) and fundamental drivers of commodity market price behavior (macroeconomic and specific indicators), our research proposes to elaborate a rational model to better understand and predict the commodity market movements. Our selecting research methodologies enables to extract the most relevant factors, key drivers,of commodity market behavior and seem to be able to capture a substantial part of systemic market risk. Furthermore, we use bootstrap techniques to identify the optimal model for market behavior. Our results are validated using widely measures used in PLS literature such as: AVE and composite reliability for the outer model validation and R-square and redundancy index for the inner model validation. The empirical results, the path coefficients and the high reliability score, come to confirm the validity of the proposed PLS model and its contribution in assisting the governments and investors in their decision-making process to improve commodity market stability and efficiency.
Key Words- commodity market behavior, key drivers, SEM, PLS model, crisis, decision making