The cyclical properties of the Baltic Dry Index (BDI) and their implications for forecasting performance are investigated. We find that changes in the BDI can lead to permanent shocks to trade of major exporting economies. In our forecasting exercise, we show that commodities and trigonometric regression can lead to improved predictions and then use our forecasting results to perform an investment exercise and to show how they can be used for improved risk management in the freight sector.

No abstract

We compare the performance of two volatility scaling methods in momentum strategies: (i) the constant volatility scaling approach of Barroso and SantaClara (2015), and (ii) the dynamic volatility scaling method of Daniel and Moskowitz (2016). We perform momentum strategies based on these two approaches in a diversified portfolio consisting of 55 global liquid futures contracts, and further compare these results to the time series momentum and buy-and-hold strategies. We find that the momentum strategy based on the constant volatility scaling method is the most efficient approach with an annual return of 15.3%.

This paper empirically studies the reversal pattern following the formation of trend‐following signals in the time series context. This reversal pattern is statistically significant and usually occurs between 12 and 24 months after the formation of trend‐following signals. Employing a universe of 55 liquid futures, we find that instruments with sell signals in the trend‐following portfolio (‘losers’) contribute to this type of reversal, even if their profits are not realised. The instruments with buy signals in the trend‐following portfolio (‘winners’) contribute much less. A double‐sorted investment strategy based on both return continuation and reversal yields to portfolio gains which are significantly higher than that of the corresponding trend‐following strategy.

Recent studies show that most financial market anomalies exhibit a momentum effect. Based on two datasets, (i) an original 22-factor sample and (ii) a more comprehensive 187-factor sample, we find that factor momentum effect is weak at the individual factor level. In both samples, only about 22%-27% of the factors exhibit strong return continuation and dominate the factor momentum portfolio while the remaining factors do not. The factor momentum strategies do not outperform the corresponding long-only strategies in either sample. The choice of factors affects the ability of factor momentum to explain individual stock momentum.