Time Charter Rates Research Articles

Analysis and forecasting of the dry bulk shipping market: structural VAR models using FFA-spot-time charter rates

ABSTRACT This study investigates dynamic interactive patterns of the dry bulk shipping markets through the lens of structural vector autoregression (VAR) models. There are two distinct hypotheses in the extant literature. One is that asymmetry between spot and forward freight agreement (FFA) markets causes FFA prices to respond more rapidly to new information than spot prices, termed the Physical-Paper Hypothesis in this paper. The other hypothesis is that there are some diverse shocks with different propagation mechanisms, termed the Shock-Diversity Hypothesis. This paper combines these two seemingly separate hypotheses at one time in two illustrative structural VAR models, based on a dataset of weekly spot, FFA, and time charter (TC) rates in the dry bulk shipping markets. The two structural VAR models show that spot, FFA, and TC rates have different, particularly dynamic responses to identified permanent shocks. Furthermore, they show that the reduced-form tri-variate FFA-Spot-TC VAR model produces more accurate forecasts of future spot rates than the bi-variate FFA-Spot and TC-Spot VAR models. Therefore, market participants can use VAR models as an information-processing tool for understanding of (e.g. data descriptions and structural inferences), and forecasting in, dry bulk shipping markets.

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

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.

EFFICIENCY OF TRAMP FLEET OPERATING UNDER THE CONTRACTS OF AFFREIGHTMENT

The paper considers the vessels operating on carriages of bulk cargoes to get the maximum profit for the shipowner as his main goal. The items in search are the long-term contracts of affreightment with some clauses indicated as indeterminate values, that can be described using a range of values. It leads to a range of voyage indicators. The vessels’ deployment for getting the maximum profit depends on the market situation that is to say possible changes in vessels' time-charter rates and freight rates. This paper presents the mathematical model, based on the fleet and volumes of carriages under a set of contracts of affreightment during the due time. It includes the necessity for the commitment fulfilment by owned and time-chartered vessels and takes into account possible changes in freight rates for cargoes carriages. The presented numerical example demonstrates the opportunity for practical implementation of the model.

Investment and trading strategies in the maritime sector: an application to the secondhand containership market

As shipping market players operate in a competitive and volatile business environment, their highly capital-intensive investment decisions to target value-generating projects are exposed to critical risks. Therefore, the paper investigates the efficiency of investment strategies based on the combination of technical trading rules and fundamental analysis in selling and purchasing ships in the container shipping market. Using historical datasets of second-hand vessel prices and time-charter rates from October 1996 to June 2021, long-run cointegrating implications and short-run causality spillover effects are examined for three groups of containerships, distinguished by their transportation capacity, viz. 725 TEUs, 1700 TEUs, and 3500 TEUs. In addition, the moving average trading rules are used to indicate the timing of investment or divestment decisions through the analysis period. The results for vessel prices and earnings for 3500 TEU containerships appeared to be more volatile compared to smaller ships (725 TEUs and 1700 TEUs), while time-charter earnings are seen to exert an impact on second-hand prices across all vessel types. Moreover, due to higher volatility, the trading strategies based on price-earning ratios significantly outperform the buy-and-hold strategies for the 3500 TEU and the 1700 TEU containerships. On the contrary, the decision to buy-and-hold smaller container ships (725 TEU) yields higher profits than the active sale and purchase strategy. The insights provided in this paper can be used by multiple stakeholders, such as liner operators, investors, lessors, and researchers.

Annual dilated convolutional LSTM network for time charter rate forecasting

Time charter rates must be predicted accurately to assist sensible decisions in the global, highly volatile shipping market. Time charter rates are affected by multiple factors, such as second-hand ship prices, order book, Libor interest rate, etc. However, not all factors convey predictive features to anticipate the future of time charter rates. Therefore, extracting predictive features from multiple driving time series from the shipping market is crucial for forecasting purposes. Accordingly, this paper proposes a novel convolutional recurrent neural network for time charter rates forecasting under the multi-variate phenomenon. The proposed network first extracts features from the monthly time series using a novel convolutional filter, the annual dilated filter. The annual dilated convolutional filter can extract the predictive features effectively and impose a sparse input structure to prevent overfitting. Then, a recurrent neural network learns the temporal information from the convoluted features. An extensive comparison study with many baseline models, including the persistence (Naïve I), statistical models, and the state-of-art networks, is conducted on the time charter rates of six kinds of ships. The empirical results demonstrate the proposed model’s superiority in forecasting the time charter rates.

Bulk Cargo Marine Transportation Industry

Bulk cargo is being transported in large parcels to reduce transportation cost calculated per unit of cargo. Its main categories are: liquid cargo, dry bulk cargo and special bulk cargo. The deadweight of the fleet of ships carrying bulk cargo by sea increased 3.4 times in 1990-2020. Dry carriers account for 55% of the fleet and their deadweight increased 4.4 times during the same period. The Oil and oil products tankers account for 37% of the deadweights which has been increased by 2.4 times. The majority of the oil tanker tonnage (over 98%) comes from VLCC, Suezmax and Aframax type vessels. 60% of this is 200 thousands tankers sized more than dwt. The oil tanker freight market in 2002-2019 was characterized by a high level of volatility. VLCC tanker time-charter equivalent ranged from $ 8.7-95.2 thousand in 2002-2019. The variability of time-charter rates in other oil tanker categories was similar. The major part of the tonnage of product tankers (more than 90%) is derived from from LR2, LR1 and MR2 type of vessels. 43% of these are LR2 tankers. This segment of the freight market was also highly variable. LR2 tanker time-charter equivalent ranged from $ 7.5-28.8 thousand in 2011-2019 years. The main part of the tonnage of dry cargo vessels (over 69%) comes from Capesize, Panamax and Supramax type vessels. This segment of the freight market has been declining and highly volatile in recent years. The capesize-type ship time charter equivalent ranged from $ 3.5-30.8 thousands in 2011-2019. Keywords: bulk cargo, oil tanker, bulk carrier, gas carrier, chemical tanker, time charter equivalent.

The Effect of Ship Owner-Ship Operator Separation on the Market Risk Split

Purpose - There are three different business models in shipping: owner-operators, operators, and owners. This paper analyzes the effect of separating owner-operators into tonnage providers and operators, and considers this effect from the perspective of risks and returns. Design/Methodology/Approach - A historical simulation was performed to measure realized operating profits and the volatility of each type of player. Time series data from 1992 was adopted from Clarkson Research and Drewry Maritime Research to simulate revenues, capital costs, and operating costs for 229 investment cases. A bootstrap sampling enhances the robustness of the results. Findings - The results show that the operating profits of owner-operators are divided into those of two separate players. The same, however, cannot be said for market risk. Against general expectations, operator market risk was not significantly reduced by separation; in the case of Panamax, it even increased. This can be explained by a negative correlation between spot rates and actually-applied time charter rates. Research Implication - Most papers on market risk have so far focused on the measurement and forecast of return volatility. This paper, on the other hand, is a novel attempt to analyze the effect of business model separation on market risk. The public-sector owner model is widely discussed in Korean shipping circles, and this paper is expected to provide meaningful insight to policymakers. Additionally, the risk-return profile of the pure owner model provides a good basis to develop the model for the balanced growth of the Korean shipping industry.

Second-hand vessel valuation: an extreme gradient boosting approach

ABSTRACT We investigate the efficacy of the Extreme Gradient boosting (XGBoost) machine learning technique in desktop vessel valuation and compare it to benchmark models consisting of a LASSO regression, a Generalized Additive Model (GAM) and a Generalized Linear Model (GLM). Our data consists of of 1880 sale and purchase transactions for Handysize bulkers between January 1996 and September 2019. Using vessel-specific and market variables, we find that the XGBoost algorithm outperforms the GAM approach in its ability to model complex non-linear relationships between multiple variables. When fitting the XGBoost model, we find that vessel age, timecharter rates and fuel efficiency are the most important variables. Our findings are important for investors, shipowners and ship financiers in the maritime industry.

What moves shipping markets?: A variance decomposition of price–charter ratios

ABSTRACT This paper studies the dynamic relationship between ship prices and operating profits by using the fact that these two factors are cointegrated. To conduct an empirical analysis, we select Panamax 76K 5-year second-hand prices and 1-year time charter rates, and then define their linear combination as a log price–charter ratio. We find that almost all variations in price–charter ratios correspond to changing expectations about future returns. This finding implies that the mean reversion in price–charter ratios arises mainly from ship prices as prices tend to move toward operating profits. The implication is that price–charter ratios can be used to schedule ship investment timing. When unexpected down-side risks occur, one preemptive action to minimize additional losses is to lower vessel exposure right away before ship prices plummet in accordance with movements in the freight market.

Shipping market forecasting by forecast combination mechanism

ABSTRACT The volatile characteristics of the tanker market pose challenges to forecasting. In addition, the volatile characteristics of newbuilding and secondhand ship prices, time charter rates, and scrap values make developing a unified framework of forecasting difficult. Most researchers have developed forecasting models and evaluated their performance based on a specific market. Such narrow development imposes difficulty for practitioners to choose a suitable model. Due to the boom of machine learning, many researchers are trying to boost the forecasting accuracy of shipping markets using machine learning. However, there are many hyper-parameters of the complex machine learning models and a slight variation of the model may cause significant performance degradation. This paper utilizes a forecast combination mechanism to forecast many time series collected from the shipping market, including newbuilding and secondhand ship prices, scrap values, and time charter rates. The models inside the combination pool are just linear functions. Finally, we compare their performance with conventional machine learning models and naïve forecasts using three error metrics and statistical tests. The statistical tests show that the combination of linear models is superior. The findings of this study also indicate that complex models do not boost forecasting accuracy necessarily.

Identifying shipowners’ risk attitudes over gains and losses: Evidence from the dry bulk freight market

This study examines the risk-return trade-off in the dry bulk freight market under different scenarios such as risk measures, risk attitudes and controlling for variables associated with the freight rate cycle. For long-term contracts, there exists a negative association between risk and return, suggesting that shipowners are willing to offer a discount on time-charter rates over spot rates to compensate for the loss of flexibility. Additionally, shipowners are not uniformly risk averse, as finance theory suggests, since their utility functions are concave (risk-averse) for losses and convex (risk-seeking) for gains.

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

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.

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

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.

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

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.

Effect of risk preference on the valuation of time charter contracts with extension options

ABSTRACTThe literature on valuation of time charter contracts and real options in shipping generally relies on the complete markets hypothesis and the risk-neutrality of agents. However, these assumptions fail completely in some shipping market segments. This study proposes a numerical approach—based on discounting the certainty equivalent payoff at the risk-free rate—which incorporates the agent’s risk preferences through an exponential utility function. The method comprises an iterative Monte Carlo nested simulation with the real probability measure. This method is applied to a case of Suezmax tankers. The stochastic evolution of the time charter rates is modelled as a geometric mean-reverting process. The case study supports the applicability of the proposed method and evidences that the effect of risk preference may be significant, mainly for more risk-averse agents. Although the method involves intensive computation, it has the benefits of theoretical ease and flexibility, which could encourage utilisation by practitioners.

Crude oil contango arbitrage and the floating storage decision

We investigate charterers’ ability and willingness to exploit floating storage arbitrage opportunities. Using time-series and fixtures data on time-charter rates, we find that arbitrage opportunities were present during the Financial Crisis and the recent Oil Glut. An investigation of storage profits across storage horizons suggests that positive oil supply shocks favour longer storage horizons than negative oil demand shocks. Evidence from spatial ship-tracking data suggests charterers are reluctant to exploit the arbitrage opportunity when the implied value of transportation from Forward Freight Agreements (FFAs) exceeds the storage profit. Our findings are of interest to maritime economists and oil market participants.

Freight Calculation Model: A Case Study of Coal Distribution

Coal has been known as one of energy alternatives that has been used as energy source for several power plants in Indonesia. During its transportation from coal sites to power plant locations is required the eligible shipping line services that are able to provide the best freight rate. Therefore, this study aims to obtain the standardized formulations for determining the ocean freight especially for coal distribution based on the theoretical concept. The freight calculation model considers three alternative transport modes commonly used in coal distribution: tug-barge, vessel and self-propelled barge. The result shows there are two cost components very dominant in determining the value of freight with the proportion reaching 90% or even more, namely: time charter hire and fuel cost. Moreover, there are three main factors that have significant impacts on the freight calculation, which are waiting time at ports, time charter rate and fuel oil price.

Impacts of Kra Canal and its toll structures on tanker traffic

ABSTRACTThis article discusses the proposed Kra Canal and its impacts on the tanker market from an economic perspective. We forecast tanker size distributions and further analyze the impacts of toll structures on tanker traffic. The forecast for tanker size distributions is based on distance savings for tankers as potential users of the Kra Canal. The database covers 105 busiest oil transport routes through the Strait of Malacca for the three-year period 2013–2015. Forecasts for individual routes are achieved using an autoregressive model. Two toll polices, namely the willingness-to-pay policy and the differential-pricing policy, are analyzed in order to maximize the annual toll income of the Kra Canal. The findings for the proposed Kra Canal will attract large vessels from the Strait of Malacca. An interesting finding is that the Kra Canal becomes more profitable during an unfavorable tanker market situation when the time-charter rate is low and fuel price is high. The article concludes with a policy that satisfies the goals of canal operator and government.

Duration analysis for recurrent ship accidents

ABSTRACTAbout 63% of the world’s shipping accidents are recurrent—they occur to ships that have already experienced at least one prior accident. Therefore, reducing recurrent accidents can contribute significantly to maritime safety. We study the factors affecting both first and recurrent accidents, by focusing on the duration between two accidents. Cox proportional hazard models are applied to ship accident data from 1996 to 2015, and the results identify which ships have a high risk of recurrent accidents, based on ship attributes, ship supply and market conditions, shipbuilding country, previous accident type, and ship type. The recurrent rate is high when the ship involved in the accident is old, small, flies a flag of convenience, and has no detention record. In addition, the accident risk increases when the shipping market faces a high bunker price, overcapacity in supply, a high time charter rate, or low newbuilding price. On the other hand, ships built in China and Japan have lower recurrent accident rates than those built elsewhere, although ships built in China have earlier first accidents than do others. General cargo ships have the highest recurrent accident rate, followed by dry bulkers, container ships, and tankers, in that order.

Economic information transmissions and liquidity between shipping markets: New evidence from freight derivatives

Economic return and volatility spillovers of derivatives markets on a number of assets have been extensively examined in the general economics literature. However, there are only a limited number of studies that investigate such interactions between freight rates and the freight futures, and no studies that also consider potential linkages with freight options. This study fills this gap by investigating the economic spillovers between time-charter rates, freight futures and freight options prices in the dry-bulk sector of the international shipping industry. Empirical results indicate the existence of significant information transmission in both returns and volatilities between the three related markets, which we attribute to varying trading activity and market liquidity. The results also point out that, consistent with theory, the freight futures market informationally leads the freight rate market, though surprisingly, freight options lag behind both futures and physical freight rates. The documented three-way economic interactions between the related markets can be used to enhance budget planning and risk management strategies, potentially attract more investors, and thus, improve the liquidity of the freight derivatives market.