Volatility in freight rates and shipping demand poses financial risks for charterers and ship owners. Freight forward agreements (FFAs) are popular hedging tools for fixing freight rates in advance by specifying the amount of cargo to be transported at the maturity period of the agreement. Procurement decisions with FFAs require assessing future freight rates and shipping demand. Accepting an FFA price offer higher than future FFA and spot prices or procuring a larger amount than the actual demand constitutes risks for charterers. We consider the freight procurement problem of a charterer, minimizing the total expected cost using FFA and spot markets under price and demand uncertainty. We show that a state-dependent base-stock policy is optimal with non-decreasing base-stock levels as the demand period approaches when price and demand forecasts are not updated. To determine base-stock levels, we propose probabilistic forecast-based policies with updated forecasts and an increasing base-stock level policy (IBP) adjusting base-stock levels based on the number of periods left until the demand period. The proposed methods are compared with benchmark methods using synthetic data covering different market conditions and real data from 14 bulk and tanker routes. The evaluation period covers pre-crisis (2016–2019) and during-crisis periods (2020–2023), considering major events after 2019, such as the COVID-19 pandemic and the Russia–Ukraine conflict, which led to high market volatility. Numerical evaluations show that policies based on probabilistic forecasts outperform those based on point forecasts. Utilizing probabilistic demand forecasts results in lower costs than probabilistic price forecasts. Experiments on the market data show that IBP results in the lowest cost on average while avoiding excessive procurement due to being in line with the optimal procurement policy. IBP outperforms probabilistic forecast-based policies due to forecast biases in the volatile freight market.

中文翻译：

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在需求和价格不确定性下，海运远期货运市场中基于概率预测的采购


运费和航运需求的波动给租船人和船东带来了财务风险。货运代理协议 （FFA） 是一种流行的对冲工具，通过指定在协议到期期间要运输的货物数量来提前确定运费。使用 FFA 的采购决策需要评估未来的运费和运输需求。接受高于未来 FFA 和现货价格的 FFA 价格报价，或采购高于实际需求的金额，都会给租船人带来风险。我们考虑租船人的货运采购问题，在价格和需求不确定性下使用 FFA 和现货市场最小化总预期成本。我们表明，当价格和需求预测未更新时，随着需求期的临近，基础库存水平不降低，依赖于州的基础库存策略是最优的。为了确定基础库存水平，我们提出了基于概率预测的策略，其中包含更新的预测，以及根据需求期间之前剩余的期间数调整基础库存水平的递增基础库存水平策略 （IBP）。使用涵盖不同市场状况的合成数据以及来自 14 条散货和油轮航线的真实数据，将所提出的方法与基准方法进行了比较。评估期涵盖危机前（2016-2019 年）和危机期间（2020-2023 年），考虑到 2019 年之后的重大事件，例如 COVID-19 大流行和俄乌冲突，这些事件导致市场高度波动。数值评估表明，基于概率预测的策略优于基于点预测的策略。与概率价格预测相比，利用概率需求预测的成本更低。 对市场数据的实验表明，IBP 平均成本最低，同时由于符合最优采购政策而避免了过度采购。由于在动荡的货运市场中存在预测偏差，IBP 的表现优于基于概率预测的保单。