The Baltic Dry Index: cyclicalities, forecasting and hedging strategies

Papailias, Fotis; Thomakos, Dimitrios D.; Liu, Jiadong

doi:10.1007/s00181-016-1081-9

Cited by 47 publications

(34 citation statements)

References 21 publications

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“…(Bildirici et al, 2015). Vessel supply "is very inelastic" while demand for vessel usage "tends to be very elastic" (Papailias et al, 2017). As a result, configurations and markets served tend to focus "on the long-term trend" (Grama, 2012).…”

Section: Vessel Utilization and Freight Ratesmentioning

confidence: 99%

“…A risk management analysis conducted using a 12-month forecast found "potential benefits of using sign-based timing for investing or hedging the BDI" (Papailias et al, 2017). Another study evaluating the time period 1988-2010 shows support for "the growth of the market of freight rates options, a safe hedging instrument for farmers and cooperatives that ship their grains to distant destinations" (Geman & Smith, 2012).…”

Section: The Bdi As a Predictormentioning

confidence: 99%

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Are Bulk/Container Shipping Companies Improving Compared to the Baltic Dry Index?

Barrows¹

2019

ASS

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This study evaluates the 2000-2017 time frame and assesses the performance of the bulk/container shipping industry before and after the Great Financial Crisis (GFC) in relation to the Baltic Dry Index (BDI) and two other benchmarks in a variety of combinations. This study evaluates two different period portfolios of shipping companies based on their stock price total return performance. Five cases are presented that demonstrate portfolio improvement when comparing performance after the GFC with performance before the GFC in relation to the BDI and the other benchmarks. Included are discussions on shipping industry competition, vessel utilization and freight rates plus the BDI as an economic activity predictor.

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Section: Vessel Utilization and Freight Ratesmentioning

confidence: 99%

Section: The Bdi As a Predictormentioning

confidence: 99%

Are Bulk/Container Shipping Companies Improving Compared to the Baltic Dry Index?

Barrows¹

2019

ASS

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“…As minerals and iron ore are products shipped in bulks, demand for dry bulk is determined by price of these products to a large extent (UNCTAD, 2017a). Besides, the relationship between BDI and various commodities including iron, copper, tin and wheat are investigated in a recent study by Papailias et al (2017). As a result, commodity price index for minerals, ores and metals is included in this study due to its comprehensive structure for representing demand side with especially iron ore and phosphate prices as well as copper, zinc, nickel and primary aluminium prices.…”

Section: Datamentioning

confidence: 99%

“…Another indicator is Special Drawing Rights (SDR) which is formed as an international reserve asset to better reflect trade growth and financial flows (IMF, 2016). After Papailias et al (2017) investigate the relationship between exchange rates and BDI, US$/SDR exchange rate is included in the set of explanatory variables. Commodity price indices for minerals, ores and metals along with for food are sourced from UNCTAD (2017b).…”

Section: Datamentioning

confidence: 99%

“…It incorporates the cost of transporting various raw materials worldwide. Furthermore, it is a fundamental indicator for direction of input prices and economic activity (Papailias et al, 2017) as average raw material prices such as coal, iron ore, cement and grains are embedded. Thus, it is closely related to economic conditions and therefore global trade.…”

Section: Introductionmentioning

confidence: 99%

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Predicting Baltic Dry Index With Leading Indicators

Şahan¹,

Memilşoğlu²,

Başer³

2018

Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi

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The Baltic Dry Index (BDI) is issued by the Baltic Exchange on a daily basis and it signals for the average cost of shipping raw materials on a number of shipping routes. Baltic Dry Index is considered by both the private and public authorities as an important indicator for freight rates, international trade and economic activity. Conducting a long-term prediction for dry bulk indices is challenging due to the high volatility of the dry bulk freight market; therefore, a linear prediction spanning a shorter time period offers both greater accuracy and can be used as a tool for speculation. The goal of this paper is to form a linear benchmark model through Box-Jenkins approach including explanatory variables selected rigorously to forecast Baltic Dry Index. Using monthly data between January 2010 and June 2017, the analysis results point out an ARIMAX (10,1,0) model with spot prices of gold and silver, United States 10-year bond yield and commodity price index composed of minerals, ores and metals.

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A novel forecasting model for the Baltic dry index utilizing optimal squeezing

Makridakis

Merikas

Merika

et al. 2019

Journal of Forecasting

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Marine transport has grown rapidly as the result of globalization and sustainable world growth rates.Shipping market risks and uncertainty have also grown and need to be mitigated with the development of a more reliable procedure to predict changes in freight rates. In this paper, we propose a new forecasting model and apply it to the Baltic Dry Index (BDI). Such a model compresses, in an optimal way, information from the past in order to predict freight rates. To develop the forecasting model, we deploy a basic set of predictors, add lags of the BDI and introduce additional variables, in applying Bayesian Compressed Regression (BCR), with two important innovations. First, we include transition functions in the predictive set to capture both smooth and abrupt changes in the time path of BDI; second, we do not estimate the parameters of the transition functions, but rather embed them in the random search procedure inherent in BCR. This allows all coefficients to evolve in a time-varying manner, while searching for the best predictors within the historical set of data. The new procedures predict the Baltic Dry Index with considerable success.

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The Baltic Dry Index: cyclicalities, forecasting and hedging strategies

Cited by 47 publications

References 21 publications

Are Bulk/Container Shipping Companies Improving Compared to the Baltic Dry Index?

Are Bulk/Container Shipping Companies Improving Compared to the Baltic Dry Index?

Predicting Baltic Dry Index With Leading Indicators

A novel forecasting model for the Baltic dry index utilizing optimal squeezing

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