TY - JOUR
T1 - A hedging policy for seaborne forward freight markets based on probabilistic forecasts
AU - Sel, Burakhan
AU - Minner, Stefan
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/10
Y1 - 2022/10
N2 - Rate volatilities in seaborne freight markets lead charterers and ship owners to use financial agreements such as Forward Freight Agreements (FFA) for fixing freight rates in advance. The use of FFAs requires effective hedging policies since fixing freight rates in advance might cause both benefits and opportunity costs depending on future rate changes. We propose a data-driven hedging policy prescribing purchasing decisions for FFAs based on comparisons of FFA rates with future spot rate forecasts. The proposed approach is based on probabilistic forecasts instead of point forecasts because the most accurate forecasts in terms of predictive errors do not necessarily lead to the best decisions. We adjust spot rate forecasts by selecting percentiles that result in minimum prescriptive errors (i.e., cost) in cross-validation. Experiments on synthetic data show that the probabilistic forecast-based hedging policy outperforms the point forecast-based policies and benchmark policies, including data-driven policies from the literature. Experiments on Baltic Exchange data from 15 dry bulk and tanker routes confirm the performance of the proposed policy. Compared to two different point forecast-based policies defined in this study, the proposed approach achieves on average 3.31% and 3.02% total procurement cost reduction per route in 15 routes for four years testing period. It results in from 0.67% to 4.79% cost reductions against the benchmark policies.
AB - Rate volatilities in seaborne freight markets lead charterers and ship owners to use financial agreements such as Forward Freight Agreements (FFA) for fixing freight rates in advance. The use of FFAs requires effective hedging policies since fixing freight rates in advance might cause both benefits and opportunity costs depending on future rate changes. We propose a data-driven hedging policy prescribing purchasing decisions for FFAs based on comparisons of FFA rates with future spot rate forecasts. The proposed approach is based on probabilistic forecasts instead of point forecasts because the most accurate forecasts in terms of predictive errors do not necessarily lead to the best decisions. We adjust spot rate forecasts by selecting percentiles that result in minimum prescriptive errors (i.e., cost) in cross-validation. Experiments on synthetic data show that the probabilistic forecast-based hedging policy outperforms the point forecast-based policies and benchmark policies, including data-driven policies from the literature. Experiments on Baltic Exchange data from 15 dry bulk and tanker routes confirm the performance of the proposed policy. Compared to two different point forecast-based policies defined in this study, the proposed approach achieves on average 3.31% and 3.02% total procurement cost reduction per route in 15 routes for four years testing period. It results in from 0.67% to 4.79% cost reductions against the benchmark policies.
KW - Freight forward agreements
KW - Freight rate forecasting
KW - Hedging
KW - Prescriptive analytics
UR - http://www.scopus.com/inward/record.url?scp=85138828753&partnerID=8YFLogxK
U2 - 10.1016/j.tre.2022.102881
DO - 10.1016/j.tre.2022.102881
M3 - Article
AN - SCOPUS:85138828753
SN - 1366-5545
VL - 166
JO - Transportation Research Part E: Logistics and Transportation Review
JF - Transportation Research Part E: Logistics and Transportation Review
M1 - 102881
ER -