ASYMMETRIC EFFECTS OF INVESTOR SENTIMENT ON MALAYSIAN SECTORAL STOCKS: A NONLINEAR AUTOREGRESSIVE DISTRIBUTED LAG APPROACH

Extant literature fails to conclusively shed light on the asymmetric effects of market sentiment during bulls and bears, especially for small open markets like Malaysia. This study constructs a sentiment index for Malaysia using Principal Component Analysis. A nonlinear Autoregressive Distributed Lag (ARDL) model is applied to capture and distinguish the optimistic and pessimistic sentiments to justify sectoral stock price movements. Our threefold findings reveal the significant explanatory power of sentiment on sectoral stock prices for both market phases, validated by bound test statistics and error correction terms. Furthermore, the study uncovers long-run asymmetric effects in most sectors (excluding technology) and emphasises their insignificance in the short run, attributable to limited and regulated short selling. Dynamic multiplier graphs underscore the temporal nature of sentiment effects, peaking in the 3rd to 7th months for most stocks, with technology stocks exhibiting an overreaction to negative sentiments. Notably, most stocks respond to positive adjustments, indicating that investors are not driven by loss aversion stemming from diverse market news. These insights are vital for individual traders, fund managers, and regulatory bodies involved in risk assessment and hedging strategy formulation. The study contributes to non-conventional equity analyses, offering valuable perspectives for navigating the complexities of small open markets.