Non-linear dynamics of global liquidity and energy sector profitability

This study examines how global liquidity influences the profitability of companies in the energy sector using a non-linear approach. Applying Functional Principal Component Analysis (FPCA) to sparse data, we reconstruct the profitability history of 497 energy companies in various subsectors, including coal, oil and gas, oil and gas-related equipment and services, renewable energy, and uranium. We use a Distributed Delay Nonlinear Model (DLNM) to estimate the impact of global liquidity on profitability. Our results reveal distinct nonlinear patterns in the response of these subsectors to changes in global liquidity. For example, in the oil and gas subsector, an extreme quantile (99%) of global liquidity is associated with a significant 5.19% increase in profitability in the first quarter after the shock. In contrast, in the renewable energy subsector, a lower quantile (25%), corresponding to a moderately downward trend, is associated with a 0.73% increase in profitability over the same period. These finings are crucial to improving risk management, investment and policy development strategies within the energy sector, offering a deeper understanding of the dynamics in the global financial and economic landscape.