Unveiling Investor Sentiment's Impact on Dry Bulk markets
Keywords:
BDI, MARITIME STOCKS, Out-of-sample forecast performance, LSTM neural networks, freight rates, DJIA, Market sentiment, LiquidityAbstract
Our research focuses on the maritime industry, specifically the dry bulk market, contributing to the emerging research agenda regarding the influence of financial markets on the real economy. Motivated by the documented relationship between the Baltic Dry Index (BDI) and financial markets, we study how different types of investors’ sentiment in the US stock market influence the BDI. Employing Granger causality tests and impulse response functions, we examine how investors’ confidence and ensuing liquidity in both the US maritime and the broader US stock markets impact corporate decisions related to freight rates and secondhand vessel investments.
Our findings highlight the critical role of investor sentiment for stakeholders in the dry bulk market and the significance of the BDI in shaping traders’ investment in the US capital market. Additionally, by comparing our results with previous studies, we provide fresh evidence regarding the identity of traders in the maritime capital market. We also employ Long Short-Term Memory (LSTM) neural networks to establish the out-of-sample predictive power of our sentiment proxies, positioning them
as novel BDI determinants. The results provided align with signal theory, challenge the efficient market hypothesis, and offer valuable insights for optimizing profitability and fostering economic sustainability in various industries.
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Copyright (c) 2024 DIMITRIS GEORGOULAS, Stratos Papadimitriou
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