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

Karell, V., Luukka, P., Pätäri, E. and Yeomans, J.S. (2018). "Comparison of the Multicriteria Decision-Making Methods for Equity Portfolio Selection: The U.S. Evidence", European Journal of Operational Research, 265(2), 655-672.

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Abstract This paper compares the efficacy of four multicriteria decision-making (MCDM) methods in identifying the future best-performing stocks in two comprehensive samples of U.S. stocks. This is the first time that median-scaling (MS), the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), the Analytic Hierarchy Process (AHP), and the additive Data Envelopment Analysis (add.DEA) have been used to combine value and momentum indicators into a single efficiency score. The results show that the MCDM methods examined can successfully be applied to equity portfolio selection. As a robustness check, we repeat all the main sample tests for the sample of the largest-cap stocks included in the two biggest size quintiles (i.e., stocks above 40% NYSE market-cap breakpoint) and find that the overall results are surprisingly robust to size effect. However, the best-performing portfolios formed on the basis of different MCDM methods have remarkably different exposures to the style factors that are commonly used to explain the abnormal returns of active equity portfolios. As a practical implication of this study, investors following certain investing styles could take these different style exposures into account when choosing the MCDM criteria that best fit their portfolio-selection purposes.

Karell, V. and Yeomans, J.S. (2018). "Anomaly Interactions and the Cross-Section of Stock Returns", Fuzzy Economic Review, 23(1), 33-61.

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Abstract This study provides new evidence on anomaly interactions, as well as on the cross-section of returns in all-but-microcap universe of U.S. stocks over the 42-year sample period from 1971 to 2013. The five anomalies being examined are size, value, profitability, investment/asset growth, and momentum. We form 5x5 conditional double-sort portfolios for each pair of anomaly variables, resulting in 20 different 5x5 sorts when using each variable in the first-stage sorting and the remaining four in the second-stage sorting. The interrelation between each pair of anomaly variables is evaluated on the basis of the monotonic relation (MR) test of Patton and Timmermann (2010) for portfolio raw returns, and in addition, by means of the Sharpe ratio comparisons. Moreover, we run Fama-MacBeth (1973) cross-sectional regressions to compare the relative explanatory power of each variable in the presence of the others. The results show that investment/asset growth and momentum dimensions capture the cross-sectional return patterns better than size, value, or profitability. The relative efficacy of momentum is higher in all-but-microcap universe than previously documented for the corresponding unlimited market-cap samples of U.S. stocks.