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

Basher, S., Haug, A. and Sadorsky, P. (2018). "The Impact of Oil-Market Shocks on Stock Returns in Major Oil-Exporting Countries", Journal of International Money and Finance, 86, 264-280.

Open Access Download

Abstract The impact that oil-market shocks have on stock prices in oil exporting countries has implications for both domestic and international investors. We derive the shocks driving oil prices from an oil market model that explicitly identifies speculative trading in the crude oil market. We study the nonlinear relationship of oil price shocks with stock market returns in major oil-exporting countries in a multi-factor Markov-switching framework. Flow oil-demand shocks have a statistically significant impact on stock returns in Canada, Norway, Russia, Kuwait, Saudi Arabia, and the UAE. Idiosyncratic oil-market shocks affect stock returns in Norway, Russia, Kuwait, Saudi Arabia and UAE. Speculative (oil-inventory) shocks impact stock returns in Canada, Russia, Kuwait and the UAE. Flow oil-supply shocks matter for the UK, Kuwait, and UAE. Mexico is the only country where stock returns are unaffected by oil-market shocks. A portfolio that uses the Markov-switching probabilities to switch between equities in the low volatility state and T-bills in the high volatility state outperforms a buy and hold strategy for some countries.