Container freight rate forecast integrating soft facts

Beschreibung

This study presents a novel approach to forecast freight rates in container shipping by integrating soft facts in form of information about sentiments, perceptions and/or confidence regarding past, present and/or future market activity as exogenous variables with the Far East to Northern Europe trade route under consideration. As a base case, we used the autoregressive integrated moving average (ARIMA) model and compared this with the ARIMAX and the Vector Autoregressive (VAR) modelling approach including soft facts. We found that incorporating the Logistics Confidence Index (LCI) by Transport Intelligence into ARIMAX model improved forecast performance greatly. Hence, it seems that a sampling of sentiments, perceptions and/or confidence from a panel of actors active in the container shipping market that comes close to nowcasting have a higher predictive power compared to hard facts. Moreover, we argue that this approach of including such soft facts can improve forecast performance on other trade routes, too, and probably allows a detection of market changes and/or economic development much earlier than hard facts, because the later are all quantitative measures collected mostly from past times.

Zeitraum	26 Juni 2019 → 28 Juni 2019
Ereignistitel	24th IAME 2019 Conference
Veranstaltungstyp	Keine Angaben
Bekanntheitsgrad	International