Asset pricing with mean reversion: The case of ships

Moutzouris, Ioannis C.; Nomikos, Nikos K.

doi:10.1016/j.jbankfin.2019.105708

Cited by 19 publications

(13 citation statements)

References 24 publications

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“…Significant construction lags meant that these vessels were delivered, just as the financial crisis was unfolding and the shipping market contracted. 13 The pattern of overinvestment at the peak of the market cycle is a key feature of the shipping industry (e.g., Kalouptsidi, 2004;Greenwood and Hanson, 2015;Moutzouris and Nomikos, 2020). Finally, the gradual decline in time charter rates from 2009 to 2014 is seen to be the result of a combination of lower tanker demand, lower utilization, and higher tanker supplies.…”

Section: Real Vlcc Time Charter Ratesmentioning

confidence: 99%

A Quantitative Model of the Oil Tanker Market in the Arabian Gulf

Kilian¹,

Nomikos²,

Zhou³

2020

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Using a novel dataset, we develop a structural model of the Very Large Crude Carrier (VLCC) market between the Arabian Gulf and the Far East. We study how fluctuations in oil tanker rates, oil exports, shipowner profits, and bunker fuel prices are determined by shocks to the supply and demand for oil tankers, to the utilization of tankers, and to bunker fuel costs. Our analysis shows that time charter rates respond only slightly to fuel cost shocks. In response to higher fuel costs, voyage profits decline, as cost shocks are only partially passed on to round-trip voyage rates. Oil exports from the Arabian Gulf also decline, reflecting lower demand for VLCCs. Positive utilization shocks are associated with higher profits, a slight increase in time charter rates and slightly lower fuel prices and oil export volumes. Tanker supply and tanker demand shocks have persistent effects on time charter rates, round-trip voyage rates, the volume of oil exports, fuel prices, and profits with the expected sign.

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Section: Real Vlcc Time Charter Ratesmentioning

confidence: 99%

A Quantitative Model of the Oil Tanker Market in the Arabian Gulf

Kilian¹,

Nomikos²,

Zhou³

2020

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“…Significant construction lags meant that these vessels were delivered, just as the financial crisis was unfolding and the shipping market contracted. The pattern of overinvestment at the peak of the market cycle is a key feature of the shipping industry (e.g., Kalouptsidi, 2004;Greenwood and Hanson, 2015;Moutzouris and Nomikos, 2020). As is the case for other variables, the main driver of the increase in bunker fuel prices until mid-2008, their decline in late 2008, and their recovery in 2009 was tanker demand shocks.…”

Section: Real Vlcc Time Charter Ratesmentioning

confidence: 99%

A Quantitative Model of the Oil Tanker Market in the Arabian Gulf

2020

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Using a novel dataset, we develop a structural model of the Very Large Crude Carrier (VLCC) market between the Arabian Gulf and the Far East. We study how fluctuations in oil tanker rates, oil exports, shipowner profits, and bunker fuel prices are determined by shocks to the supply and demand for oil tankers, to the utilization of tankers, and to the cost of operating tankers, including bunker fuel costs. Our analysis shows that time charter rates are largely unresponsive to tanker cost shocks. In response to higher costs, voyage profits decline, as cost shocks are only partially passed on to round-trip voyage rates. Oil exports from the Arabian Gulf also decline, reflecting lower demand for VLCCs. Positive utilization shocks are associated with higher profits, a slight increase in time charter rates and lower fuel prices and oil export volumes. Tanker supply and tanker demand shocks have persistent effects on time charter rates, round-trip voyage rates, the volume of oil exports, fuel prices, and profits with the expected sign. JEL code:Q43, R41.

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“…Shipping has served as a frutiful setting for behavioral research given its notorious volatility (see Alexandridis et al, 2018;Scarsi, 2007) that drives investors to rely both on fundamentals (Moutzouris & Nomikos, 2020) and on sentiment (Melas & Michail, 2020b;Papapostolou et al, 2014) when their economic decisions are concerned.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The overall literature of the field lies primarily in three different pillars of the behavioral research agenda, namely, overextrapolation (Greenwood & Hanson, 2015), herding behavior (Papapostolou et al, 2017) and sentiment (Papapostolou et al, 2016). While over-extrapolation has been thoroughly researched for the last 70 years (Zannetos, 1959) and sentiment has long been documented to affect the equilibrium of the industry (Melas & Michail, 2020b) as well as the stock markets (Papapostolou et al, 2014), little attention has been given up to now in the herding behavior that shipping investors exhibit.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The combination of these two specificities in the maritime sector makes decision-making in the shipping industry more burdensome and forces investors to rely heavily on factors like market sentiment (see Duru (2018) as well as Moutzouris & Nomikos (2020) for a detailed review on the matter). Moreover, have additionally shown that investors follow a herding behavior in the acquiring process of assets rather than in their scrapping decision.…”

Section: Introductionmentioning

confidence: 99%

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How Long Do We Keep Up With the Joneses? Herding Time Horizons in the Dry Bulk Shipping Markets

Michail

Melas

2020

SSRN Journal

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We estimate intentional and unintentional herding in the dry-bulk, ocean-going segment that spans from August 1998 to January 2020 and measure how this can impact vessel orders. As the results suggest, while intentional herding has a large effect on the orders of the newbuilding vessels, the impact is very shortlived. On the contrary, unintentional herding, related to common environmental factors, has a smoother but more time persistent effect on the newbuilding vessels. The findings suggest that the key players in the market do not only affect the dry-bulk market with their decisions but also the logistics trade and ultimately the world economy. Thus, the inclusion of the dry bulk key shipowners by the policymakers in the discussions before reaching an important decision could minimise the volatility of the overall sector.

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Asset pricing with mean reversion: The case of ships

Cited by 19 publications

References 24 publications

A Quantitative Model of the Oil Tanker Market in the Arabian Gulf

A Quantitative Model of the Oil Tanker Market in the Arabian Gulf

A Quantitative Model of the Oil Tanker Market in the Arabian Gulf

How Long Do We Keep Up With the Joneses? Herding Time Horizons in the Dry Bulk Shipping Markets

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