Shipping equity risk behavior and portfolio management

Abstract

This paper investigates the dynamics of stock price volatility for different vessel-type segments of the U.S, water transportation industry. We measure market exposure by a portfolio of tanker, dry bulk, container, and gas stocks to examine tail behavior and tail risk dependence. The role of mixture distributions in predicting future volatility is studied from both statistical and economic perspectives. We further test for predictability in co-movements in the tails of sectors returns. Findings indicate that large losses are strongly correlated, supporting asymmetric transmission processes for financial contagion. Finally, using a non-parametric approach, we extend the model to the multivariate case and assess the value of volatility and correlation timing in optimal portfolio selection. The results can help to improve the understanding of time-varying volatility, correlation and tail systemic risk of shipping stock markets, and consequently, have implications for risk management and asset allocation practices, as well as regulatory policies.

Tail risk connectedness between US industries

“…Using Hong et al (2009) causality test for VaR exceedance, they report the prevalent left tail spillovers between consumer service industries. In similar spirit, Pouliasis, Papapostolou, Kyriakou, and Visvikis (2018) report strong tail risk spillover between segments of US shipping sectors. Reboredo (2015) finds evidence of the tail dependence between oil and energy sectors.…”

Determinants and effects of trade credit financing: Evidence from the maritime shipping industry

“…Maritime shipping companies are defined as the companies that offer seaborne transportation services to charterers and shippers via ownership of vessels. TradeWinds is a reliable source of shipping data and it has been previously used in shipping‐related empirical studies (see Andrikopoulos et al, 2022; Grammenos et al, 2007; Pouliasis et al, 2018). Maritime shipping companies, that is, holding companies that consolidate ship‐owning subsidiaries, were selected as our sample (shipping sample) because these are asset‐ and capital‐intensive companies, requiring multiple sources of capital.…”

International tail risk connectedness: Network and determinants

“…Wang et al (2018) investigate the cross-sectoral connectedness between banks, security firms, and insurers and find that when systemic events occur, crosssectoral spillover may be more prominent than inter-sectoral spillover, posing a significant risk to the stability of the financial system. Evidence for the tail risk linkage between non-financial sectors can be found in Pouliasis et al (2017) and Pouliasis et al (2018), among others.…”