Empirical research and application of ARIMA-GJRGARCH model on effectively creating Forward Freight Agreement trading signals

This study examines the volatility of the forward freight agreement (FFA) time series in the dry bulk shipping market. Series pattern analysis is first performed to determine the volatility and the characteristics of the unique FFA price time series. It then applies the ARIMA-GJRGARCH model to the Capesize FFA time charter (C5TC) and specific voyage charter one-month contracts (C3, C5 and C7), creating long or short signals, which helps market participants with FFA trading or hedging. In this study, these signals are collected and used to calculate the profit and loss for a specific period. Finally, the model-based return results are compared with the common buy-and-hold strategy. The empirical result suggests that this methodology is effective in generating trading signals, especially in the volatile periods, providing traders with prompt warnings about imminent market shocks. The purpose of the study is to examine whether this volatility-focused method is efficient in modelling FFA time series, and it also provides a handy method that may help market players make more accurate predictions when volatile days arrive