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A Structural Model for Forecasting the Shipping Market

The aim of this study is to develop an econometric model describing the evolution of new-build and second-hand ship prices. While this model was developed originally to address internal needs within the Piraeus Bank Group, we believe that both our modelling methodology and the broader “philosophy” of our approach could be of wider interest. Consequently, the ability to identify the factors that affect the shipping market can be used in a number of ways, such as.

  1. Estimate the “fair” value in the new-build and second-hand market and assess current market pricing vs fair-valuation levels.
  2. Allow banks to assess the future evolution of the value of shipping loan collaterals (i.e. the value of the ship underlying the loan).
  3. For risk management purposes by assessing the sensitivity of the collaterals under a series of explanatory factors.
  4. Create long term forecasts under alternative macroeconomic scenarios.

Nevertheless, despite its wide range of applications modelling ship prices is extremely difficult since loosely speaking the price of a vessel can be thought of as a “derivative” contract upon another “derivative” contract. This means that the price of a vessel depends on expectations about the future evolution of freight rates which in turn are determined by the interplay between global demand for shipping services (as a result of global growth and commodity prices) and supply of shipping services (determined by the current transportation capacity of world fleet and demolition volumes).

By nature, demand as a function of economic growth and commodity prices is extremely volatile and fast changing. On the contrary, supply can adjust only at a very gradual pace due to the natural time-lag between new orders for ships and actual delivery by shipyards. The interplay between a fast moving demand and a slow adjusting supply gives rise to the main characteristic of the shipping industry, which is none other than its extreme cyclicality.

Our approach towards modelling new-build and second-hand prices is to bypass the freight market and focus on the underlying forces of demand and supply. In particular, we devise proxies for the theoretical concepts of “demand” and “supply” of shipping services and express ship prices as a function of the imbalance between the two. Furthermore, to improve the statistical behaviour of the model we also include a few exogenous variables such as oil prices and the USD exchange rate.

In turn, when it comes to modelling the price of new-build ships we find that developments in the second-hand markets also contain information we can exploit. The fact that vessel prices in our model are allowed to be driven by supply and demand factors makes our model one of the “structural” models of the global shipping industry.

Finally, we use the aforementioned model to construct long-term projections for ship prices under prespecified macroeconomic scenarios. The baseline scenario refers to a recovery in global output growth and therefore seaborne trade that is expected to reverse the downward path of ship prices. Second-hand prices are expected to rise first in response to anticipated fleet shortages sector since the orderbook adjustment over the past years contributed to low capacity utilization of shipyards. New-build prices will gradually increase over the next three years, with their growth rate expected to reach a peak in 2019. However, despite the fact that economic activity in the US, Europe and emerging markets started to gain momentum, this development is still associated with substantial downside risks around the global macroeconomic environment.