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Khorramshahr University of Marine Science and Technology
Abstract: (22 Views)
For maritime shipping companies, stock-return volatility and predictability are not only a finance question but also an indirect signal of the health of the industry’s investment cycle. Improving the accuracy of such forecasts, and quantifying the contribution of individual macroeconomic and commodity factors, therefore matters to both investors and maritime-industry stakeholders, yet remains a challenging task. This paper employs a recursive modelling approach that simulates investor behaviour to test whether macroeconomic and commodity variables help forecast the stock returns of tanker shipping companies. Methods: We follow the recursive approach of Pesaran and Timmermann (2000) and Pourkermani (2023a). A dedicated Matlab routine allows the model structure to change at every step and evaluates the out-of-sample forecasting performance of a set of eight macroeconomic and commodity regressors for five Maritime Company’s companies (Frontline, Knightsbridge Tankers, Nordic American Tankers, and Teekay Corporation) benchmarked against the S&P 500. Results: Contrary to part of the prior literature, we find that permutation-based, information-criterion-selected models do not outperform a fixed model that retains all regressors; the all-variable model consistently delivers the highest net-of-cost return. Conclusion: This paper contributes to the literature by (i) applying the recursive out-of-sample forecasting framework specifically to Maritime Company’s equities, (ii) explicitly accounting for transaction costs when evaluating switching strategies, and (iii) comparing statistical, Akaike, and Bayesian information criteria for model selection in this context. Research Limitation: The model uses historical macroeconomic and commodity data and does not incorporate maritime-specific operational variables such ::as char::ter rates or bunker fuel prices, which we identify as a direction for future research.
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Highlights
- Applies a recursive out-of-sample forecasting framework to five tanker-shipping stocks vs. the S&P 500.
- Shows the fixed All-Variable model beats all criterion-selected models (R², AIC, BIC), net of costs.
- Reveals a large gross-vs-net return gap once 20% transaction costs are applied to switching strategies.
- Identifies crude oil and broad commodity indices as the most consistently retained predictors.
- Frames shipping-equity predictability as a market-risk proxy for fleet-investment decisions.
Type of Study: Research Paper |
Subject:
Numerical Investigation
Received: 2025/07/19 | Accepted: 2026/08/2
Received: 2025/07/19 | Accepted: 2026/08/2
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