Forecasting, Efficiency and Speed in Maritime Shipping
On Tuesday September 8, Lisa Maria Assmann will hold a trial lecture on a prescribed topic and defend her thesis for the PhD degree at NHH.
Prescribed topic for the trial lecture:
Efficiency vs. inefficiency of the freight and freight forward contract markets: A timeline review of literature and of its market context
Trial lecture:
10:15, Zoom video conference, NHH
Title of the thesis:
Forecasting, Efficiency and Speed in Maritime Shipping
Summary:
The thesis consists of four articles exploring two aspects of maritime shipping economics: the empirical analysis of vessel speeds and the prediction of freight and freight forward rates. The focus of the analysis for all articles is on Very Large Crude Oil Carriers (VLCC) market.
Chapter one investigates the choice of speeds of VLCCs in response to changing market conditions, with data from Automated Identification System (AIS) signals. The study finds significant elasticities of speeds with respect to freight rates and bunker prices, however of smaller magnitude than expected from economic theory. The findings have implications for the formulation of CO2 regulations in maritime shipping and indicate that there are potential gains for ship operators from a more extensive adaption of speed optimisation.
Chapter two compares directional and point forecasting methods for freight forward rates, focusing on the economic consequences of short-term predictions by mimicking a trader's decision in the market. With the assumption that trading signals based on closing prices can be executed without delay, significant profits can be found. If allowing for a more onerous assumption of one day price slippage, resulting profits are diminished, challenging the robustness of the conclusion of an inefficient FFA market.
Chapter three investigates how to successfully forecast the directional change of an economic time series, using Monte Carlo simulations where the simulated data generating processes are chosen based on estimates from real world data in shipping and finance. The results show that there are situations where the benefit of correctly specifying a model has the cost of producing inferior forecasts for the future direction of the time series compared to a simplified using data that was reduced to an indicator variable before predicting it.
Chapter four studies to improve short term predictions of crude oil tanker freight and forward rates using market fundamentals. Variable selection methods known from statistical learning are applied to identify the best predictors amongst a set of theoretical reasonable fundamental predictors. Results show that the fundamental variables included, only add limited value when forecasting freight forwards compared to using past price information only.
Defense:
12:15, Zoom video conference, NHH
Members of the evaluation committee:
Professor Endre Bjørndal (leader of the committee), Department of Business and Management Science, NHH
Professor Helen Thanopoulou, University of the Aegean
Professor Amir Alizadeh, Cass Business School
Supervisors:
Professor Jonas Andersson (main supervisor), Department of Business and Management Science, NHH
Professor Gunnar Eskeland, Department of Business and Management Science, NHH
Professor Roar Os Ådland, Department of Business and Management Science, NHH
The trial lecture and thesis defence will be open to the public. Copies of the thesis will be available from presse@nhh.no.