Investment Papers
World fund managers’ dialog on ESG investment
More to come...
Abstract of Paper:
We use a propensity score matching procedure to compare the returns of sukuk and conventional bond issuances in the primary market in the period 2000-2021. The results of our analysis show that sukuk are issued at lower overall coupon levels than conventional bonds. We find that the difference is between -11 and -28 basis points, depending on the matching technique used. Our analysis also shows that the difference is larger in corporate issuances than noncorporate issuances. We believe that these findings can be explained by the higher demand for sukuk issuances due to the limited investment universe available to Islamic investors.
Is ESG investing an 'equity vaccine' in times of crisis? Evidence from the 2020 Wuhan Lockdown and the 2022 Shanghai Lockdown
Yuwen Dai
Abstract of Paper:
In the literature on sustainable investing, most studies assume normal market conditions. However, research is limited regarding the specific role of sustainable investing during stressed market conditions. In this paper, we contribute to the literature by investigating the role of ESG investing in market turbulence for the case of China. To that end, we examine the performance of ESG equity indices and compare against their benchmarks amid market turmoil in China, which were triggered in response to the 2020 Wuhan Lockdown and the recent 2022 Shanghai Lockdown. Specifically, we address two key issues that are of particular concern to most investors: (i) is ESG investing safe haven in times of crisis?; and (ii) can ESG investing improve portfolio diversification? Overall, our findings shed light on the role of sustainable investing amid uncertainty in turbulent times.
State-dependent hedge strategy for crude oil spot and futures markets
Xing Yu, Yanyan Li, Xilin Shen, Yunjie Rao, Yongjun Liu
Abstract of Paper:
Relying on the hidden Markov model improved by the particle swarm optimization algorithm (PSO-HMM), we develop a dual-decision method to address the issue of state-dependent futures hedging. Our approach is attractive in two ways. First, it uses the PSO algorithm to overcome the shortcomings of the traditional algorithm, which can easily fall into the local optima to estimate parameters in a hidden Markov mode. Second, this paper proposes a new hedge position adjustment method based on the identified market states, instead of sticking to the hedge position calculated by the commonly used GARCH-type models to achieve a better trade-off between risk hedging and return acquisition. Specifically, we first improve the accuracy of parameter measurement and employ the PSO-HMM to identify two market states, bear and bull, and fully illustrate the rationality and effectiveness of the proposed model. Based on the market states identified, we then adjust the hedge ratio estimated by GARCH-type models and compare the hedging effects of no hedge, model-driven, and state-dependent strategies. Our empirical results show that the PSO-HMM method can improve the accuracy of state identification over the classical HMM. The market state-dependent hedging strategy has better performance than other strategies when it comes to the trade-off between the return and the risk of a hedged portfolio. Furthermore, robustness checks under different conditions confirm that the state-dependent hedging strategy outperforms the model-driven hedging and no hedge strategies. Thus, our research sheds new light on conventional hedging models.