Pricing freight rate options

Koekebakker, Steen; Ådland, Roar; Sødal, Sigbjørn

doi:10.1016/j.tre.2006.03.005

Cited by 50 publications

(36 citation statements)

References 33 publications

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“…During an economic downturn (low GDP expectation), this leads to enormous pressure on prices, which can translate into operational losses (Fakhr-Eldin and Notteboom, 2012). The random shock term is governed by a geometric Brownian motion (drift, interest rate, and volatility are detailed in Table 1); this is in line with previous shipping industry-related work by Adland and Cullinane (2006), Adland and Strandenes (2007), Bendall andStent (2005, 2007), Goncalves (1992), Koekebakker et al (2007), Sødal et al (2008), and Gkochari (2015). Possible alternatives are geometric mean reversion (Tvedt, 1997(Tvedt, , 2003, the Ornstein-Uhlenbeck process (Bjerksund and Ekern, 1995), or the assumption of stochastically cyclical markets (Balliauw, 2015;Ruiz-Aliseda and Wu, 2012).…”

Section: Price Functionsupporting

confidence: 80%

Investment into container shipping capacity: A real options approach in oligopolistic competition

Rau

Spinler

2016

Transportation Research Part E: Logistics and Transportation Re

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Section: Price Functionsupporting

confidence: 80%

Investment into container shipping capacity: A real options approach in oligopolistic competition

Rau

Spinler

2016

Transportation Research Part E: Logistics and Transportation Re

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“…Research on the relationship between the forward and spot markets in the shipping industry has received increasing attention with the rapid development of the freight derivatives markets (and the FFA market, in particular). The main research fields and studies include the following: (1) the price discovery function of the FFA market , (2) a pricing model of FFAs and freight options (Koekebakker et al, 2007) and (3) the FFA market function (Alizadeh, 2013;Nomikos and Doctor, 2013). The results indicate that the FFA market contains a price discovery function and that different routes have different characteristics.…”

Section: Literature Reviewmentioning

confidence: 99%

A study of the relationships between the time charter and spot freight rates

Hong

Zeng

2014

Applied Economics

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A time charter contract is a shipping contract that allows for freight rate risk avoidance and hedging. Defining the relationship between time charter and spot freight rates will illuminate the fluctuation mechanism of the spot freight market. In this article, three types of dry bulk ships -Capsize, Panamax and Supramax -are chosen to investigate the relationship between time charter and spot freight rates and to analyse the price discovery function of time charter contracts. A vector error correction model is developed, and an impulse response function is used to analyse the influence of time charter rates on spot freight rates. Empirical studies indicate that there are two-way lead-lag relationships between the time charter and spot freight rates and that a time charter contract has a price discovery function. Smaller ship sizes and longer durations lead to a stronger price discovery function.

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“…As the demand for sea transport is a derived demand, one would expect a positive relationship between 6 This finding has important implications regarding the calculation of implicit volatilities. Option pricing formulas that require a normal or a lognormal distribution (for example, Modified Black (1976), Turnbull-Wakeman approximation (1991), Levy (1997), or Koekebakker et al (2007)) should not be applied. Otherwise, estimation biases could occur, clearly showing the need for distributions that are able to capture fat tails more appropriately.…”

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

Dynamics of time-varying volatility in the dry bulk and tanker freight markets

Drobetz

Richter

Wambach

2012

Applied Financial Economics

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This study examines whether shocks from macroeconomic variables or asymmetric effects are more suitable for explaining the time-varying volatility in the dry bulk and tanker freight markets or whether both effects should be incorporated simultaneously. Using Baltic Exchange indices during the sample period from March 1999 to October 2011 on a daily basis, we separately analyse the impact of macroeconomic shocks and asymmetric effects on the conditional volatility of freight rates by using a GARCH-X model and an EGARCH model, respectively. Furthermore, we simultaneously investigate both effects by specifying an EGARCH-X model. Assuming not only a normal distribution but also a t-distribution in order to better capture the fat tails of error terms, three important conclusions emerge for modelling the conditional volatility of freight rates: (i) The assumption of a t-distribution is better suited than a normal distribution is. (ii) Macroeconomic factors should be incorporated into the conditional variance equation rather than into the conditional mean equation. In addition, the number of macroeconomic factors that exhibit explanatory power decreases under a t-distribution. (iii) While there seem to be no asymmetric effects in the dry bulk freight market, these effects are strongly pronounced in the tanker freight market. Our empirical findings have important implications for freight rate risk management.

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Pricing freight rate options

Cited by 50 publications

References 33 publications

Investment into container shipping capacity: A real options approach in oligopolistic competition

Investment into container shipping capacity: A real options approach in oligopolistic competition

A study of the relationships between the time charter and spot freight rates

Dynamics of time-varying volatility in the dry bulk and tanker freight markets

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