Introduction of sentiment makes it possible for us to quantify its impact on freight prices and further expands our understanding concerning the maritime business. Third, based on the above, we can, for the first time, empirically assess and analyze the conceptual model of provide and demand as described by Stopford. Finally, the existing study introduces the three-stage least squares model, which offers the most effective setting for an exploration of demand and supply equations (Amemiya 1977; Zellner and Theil 1962) and is often a methodology that has been tiny utilised within the maritime business (Luo et al. 2009). In addition, our outcomes are essential not merely for shipowners who can predict the equilibrium price tag in the marketplace, but also for the charterers who choose to transfer their goods. Lastly, our benefits are of use to the broader spectrum in the maritime industry (i.e., countries, shipyards, shareholders) in that they can compute any off-equilibrium deviations and take the actions required to enhance their respective positions. Following this introduction, the remainder of this paper is organized as follows: Section 2 gives a evaluation on the literature around the issue, Section 3 describes the methodology plus the data made use of, Section 4 discusses the empirical results obtained and Section five tends to make conclusions around the findings. 2. Literature Evaluation Shipping has served as a fruitful setting for behavioral studies provided its volatile nature (Scarsi 2007; Alexandridis et al. 2018). The overall literature within the field lies mostly in three different pillars of behavioral investigation, namely Adenosylcobalamin medchemexpress over-extrapolation, herding behavior and sentiment. The very first researcher that pointed out a common practice that is definitely applied by shipowners was Zannetos (1959), who implied that an extrapolation with the existing fundamentals takes location when investment decisions are taken. Triadimefon Inhibitor Interestingly, the first conceptual justification of such an extrapolation was made considerably later, by Tversky and Kahneman (1974). Inside the following years, each Metaxas (1971) and Beenstock and Vergottis (1989) looked in to the matter; however, the limited availability of data curtailed their potential to attain concrete conclusions around the benefits on the extrapolating behavioral bias of shipowners. Moreover, Bulut et al. (2013) similarly recommended that shipping companies are a lot more prone to invest through the boom on the cycle, and consequently have a drop in their return on equity. Additional recently, Alizadeh and Nomikos (2007) employed a dataset of monthly information for 28 years and showed that co-integrating strategies is often a lot more beneficial for shipping investors, again showcasing that fundamentals play a crucial part. These final results are complemented by Michail and Melas (2019), who showed that a co-integrating strategy primarily based on fundamentals is also valuable for stock trading purposes. Finally, in the same spirit as the earlier investigation, will be the study by Greenwood and Hanson (2015). In their research, they provided theoretical proof on the extrapolation of fundamentals by the shipowners. More precisely, they showed that shipping investors extrapolate the exogenous demand shocks, and thus additional vessels are ordered, making an endogenous shock. Nevertheless, offered the time lag in between ordering and getting a vessel that exists intrinsically in the shipping industry, investors come to be disappointed and thus generate a shorter than typical small business cycle. A lot more lately, Moutzouris and Nomikos (2020) created a conceptual behavioral model for the handysize dr.