Publications Database
Welcome to the new Schulich Peer-Reviewed Publication Database!
The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:
- Faculty Member’s Name;
- Area of Expertise;
- Whether the Publication is Open-Access (free for public download);
- Journal Name; and
- Date Range.
At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.
If you have any questions or input, please don’t hesitate to get in touch.
Search Results
Yi-Shuai Ren, Tony Klein, Yong Jiang, Pei-Zhi Liu, Olaf Weber (2025). "Dynamic Connectedness Between Crude Oil Futures and Energy Industrial Bond Credit Spread: Evidence From China", Energy Economics, 143, 108294.
Abstract
This study utilizes a connectedness approach that is based on the quantile vector autoregressive model to analyze the level of connectedness between China's crude oil future market (INE) and the energy industrial bond credit spread across various markets. The findings of our study indicate that (1) The total connectedness index (TCI) exhibits a U-shaped pattern that changes according to conditional quantiles. This suggests that the spillover between the energy industry bond market and oil futures market is greater during extreme market conditions (bullish and bearish markets) compared to normal markets; (2) The TCI increased in size and volatility during the COVID-19 pandemic and the Russia-Ukraine conflict; (3) The electricity sector consistently transmits shocks, whereas INE consistently receives them, irrespective of the market states; (4) The credit risk of the energy sector has a significant impact on INE, particularly in bullish and bearish markets, while the former has a little impact on the latter. The coal and electricity sectors are the primary net spillover transmitters for INE in both bullish and bearish markets. Conversely, the gas sector is the largest net spillover transmitter for INE in a typical market. Lastly, our research offers novel perspectives on the information-sharing channels for the energy sector's bonds and oil futures markets, which could assist traders and investors in making more informed investment decisions.Sreelakshmi Ramesh ,Sabuj Kumar Mandal & Perry Sadorsky (2024). "Does the Source of Oil Price Shock Matter for Indian Sectoral Stock Returns? A Time-Frequency Approach to Analyse Dynamic Connectedness and Spillovers", Applied Economics, 56(56), 7469–7486.
