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Ship funds as a new asset class: An empirical analysis of the relationship between spot and forward prices in freight markets

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Abstract

Over the last decade, various new asset classes have emerged as alternatives to the more traditional investments. Although they appear attractive at a first glance, there exists hardly any historical performance track record, and experience with the return generating variables is limited. For ship funds and the valuation of shipping projects, the prevailing freight rates are important price-determining factors. Therefore, knowledge about the time series properties of spot and forward freight rates is essential for a better understanding of the return generating process of ship funds. There are, however, several peculiarities. Because shipping is a nonstorable service, forward prices need not to be linked to spot prices by any direct arbitrage relationship. We test the implications of this notion by using data for Panamax size bulk carriers and find that even in informationally efficient markets spot freight rates are highly autocorrelated. In addition, spot and forward freight rates are cointegrated, and the equilibrium is established by spot rates converging to forward rates. An extension of the standard vector error correction model reveals time-variation in the adjustment speed. Overall, our empirical findings suggest that the time series properties of freight rates need to be well understood before investing in ship funds. Another important aspect is whether ship funds should hedge their freight rate exposure in the forward market to reduce the return volatility or whether investors can achieve the same outcome by holding ship funds in a portfolio context.

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Notes

  1. Recently, however, several German initiators have established secondary markets, where ship fund participations can be traded (Drobetz et al., 2008).

  2. For a similar argument applied to the airline industry, see Shleifer and Vishny (1992).

  3. The cash flow position of a ship fund investor is strongly influenced by changes in the vessel price. The contribution of ‘asset plays’ to the ship owner's profitability can be greater than the operation of the vessel itself.

  4. The literature on corporate risk management suggests that firms can benefit from hedging market risk. Bessembinder (1991), Froot et al. (1993), and Stulz (1990) present models suggesting that a policy of hedging market risks can result in more efficient capital investments. Smithson and Simkins (2005) provide a recent survey. Whether the results from this literature can be applied to the shipping industry has not yet been addressed.

  5. See Heijdra and von der Ploeg (2003) for a textbook treatment. Kawai's (1983) model looks at futures prices, but in what follows we assume that his implications also apply to forward markets.

  6. With increasing freight rates, there is no lay up of vessels and new vessels are not available at short notice. In this case, the supply curve for freight services is almost vertical. See Kavussanos and Visvikis (2006a).

  7. In contrast, Garbade and Silber (1983) and Purcell and Hudson (1985) argue that the lack of storage facilities casts suspicion on the price discovery function in nonstorable futures markets.

  8. This result does not depend on whether the underlying asset is storable or not. Their findings are in contrast to those in Fortenbery and Zapata (1993) and Covey and Bessler (1995). They argue that cointegration should be expected between cash and forward prices of storable commodities, but not for nonstorable commodities.

  9. Moreover, because the FFA market is a ‘paper’ market rather than a physical market and allows for arbitrage, the forward rate should instantaneously incorporate all relevant information. Possible obstacles, however, are the thinness of the FFA market and the absence of strong speculative forces.

  10. Expectations for the magnitude of the average adjustment speed can be derived from the spread between spot and forward rates. The biggest deviation between spot rates and the +1A FFA rates occurred in March 2005, with spot rates being about $17,000 above FFA rates. At that time, the number of days until the middle of the FFA settlement period was about 650 days, implying an adjustment speed of $26 per day (or 0.154 per cent (=1/650) in terms relative to the deviation). The reciprocal value of the remaining days, however, is only a first-order estimation.

  11. Using the estimated cointegration vector does not qualitatively change our empirical results.

  12. According to the Baltic Exchange, route 4 is defined as follows: delivery for the Japan/South Korea range for a trip via US West Coast–British Columbia range, redelivery Skaw–Gibraltar range, duration 50/60 days, size of vessel 70.000 dwt. This route has a weight of 15 per cent in the Baltic Panamax Index (BPI).

  13. The aim of a constant underlying is only partly accomplished. The series +2A and +1A reflect the market expectation of the average spot rates in 2006, while the series +3Q, +2Q, and +1Q reflect the expected average spot rates in the last quarter of the year. We choose this approach to obtain a sufficient number of observations.

  14. In contrast, looking at electricity, which is also a nonstorable commodity, Shawky et al. (2003) find that volatility in the spot price series is significantly higher than the volatility in the future price series. They also do not find autocorrelation in the spot return series, a result they interpret as evidence for weak-form market efficiency. An explanation could be that the supply in the electricity market is much more elastic than in the shipping market.

  15. As a robustness check, we also tested an ARIMA model on the differences of the logarithmic spot rates. In this specification, however, the moving average terms were never significant.

  16. Attenuation measures the time period within which the amplitude of a distortion from equilibrium is reduced to 1/e times its original value, where e denotes Euler's number.

  17. Results from the KPSS-test (Kwiatkowski et al., 1992) support this conclusion. In this case, the null hypothesis of stationarity cannot be rejected for all contracts.

  18. The results do not change qualitatively if the estimated cointegration vectors from Table 4 are used. Our results are also robust when we use Johansen's (1991) one-step maximum likelihood approach to estimate bivariate error correction models.

  19. See Jüttner (1984, p. 460).

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Authors and Affiliations

  1. Justus-Liebig-University Giessen, Licher Strasse 74, Giessen, Germany

    Wolfgang Bessler

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  1. Wolfgang Bessler
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  2. Wolfgang Drobetz
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  3. Jörg Seidel
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Correspondence to Wolfgang Bessler.

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2holds the chair for Corporate Finance and Ship Finance at the University of Hamburg. Previously, he taught at the University of Basel, the University of St Gallen, and the WHU Otto Beisheim Graduate School. His research interests are corporate finance, asset pricing, and asset management. He serves as a member on the editorial board of various international finance journals and consults firms in the financial services industry.

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Bessler, W., Drobetz, W. & Seidel, J. Ship funds as a new asset class: An empirical analysis of the relationship between spot and forward prices in freight markets. J Asset Manag 9, 102–120 (2008). https://doi.org/10.1057/jam.2008.14

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