Transaction costs have a first-order effect on the performance of currency portfolios. Proportional costs based on quoted bid–ask spread are relatively small, but when a fund is large, costs due to the trading volume price impact are sizable and quickly erode returns, leaving many popular strategies unprofitable.
We find that a significant share of Canadian Bitcoin owners have low crypto knowledge and low financial literacy. We also find gender differences in crypto literacy among Bitcoin owners, with female owners scoring lower in Bitcoin knowledge than male owners.
How does the perception of the need to hold emergency cash relate to overconfidence in one's degree of financial literacy? The answer is surprising.
What are the primary factors contributing to the steep and persistent decline in U.S. consumption growth during the Great Financial Crisis of 2008-2009?
Trading costs, discontinuous trading, missed trades, and other frictions, along with asset management fees can cause a shortfall between live and paper portfolios. The focus of this paper is to test an effective rebalancing method that prioritizes trades with the strongest signals to capture more of the factor premia while reducing turnover and trading costs.
This paper explores the effectiveness of the BJZZ algorithm, developed by Boehmer, Jones, Zhang, and Zhang (2021), in identifying and signing retail trades executed off exchanges with subpenny price improvements.
Simple models severely understate return predictability compared to “complex” models in which the number of parameters exceeds the number of observations.
This study is important because it provides valuable insights into the current state of financial literacy in Canada, its relationship to retirement planning, and the factors that influence financial literacy outcomes.
The research literature on diversity in asset management, while promising, is limited with respect to the breadth of the evidence produced to date. We don't really understand the broad-based benefits of diversity nor how diversity delivers value in asset management. How does it really work? Is it the university, the college major, gender, race, the work experience? That is where this study comes into play. The authors propose a unifying concept called homophily to analyze the impact of diversity in asset management using hedge funds as their laboratory. Sociology describes homophily as groups of people that share common characteristics such as beliefs, values, education, and so on. In a team setting those characteristics make communication and relationship formation easier. Further, a large body of research in sociology specifically documents the presence of homophily with respect to education, occupation, gender, and race. Luckily, management teams within hedge funds can be characterized by just those dimensions.
This paper explores the applicability of the Bernanke-Blanchard (BB) model across diverse economies, revealing commonalities and differences in inflation dynamics post-pandemic.
Higher volatility is associated with faster, initially stronger reversals, while lower turnover is associated with more persistent, ultimately stronger reversals
How do female appointments to top management teams (TMTs) affect a firm's approach to knowledge-related strategic renewal?
Can AI models improve on the failures in predicting returns strictly from a practical point of view? In this paper, the possibilities are tested with a battery of AI models including linear regression, dimensional reduction methods, regression trees and neural networks. These machine learning models may be better equipped to address the multidimensional nature of stock returns when compared to traditional sorting and cross-sectional regressions used in factor research. The authors hope to overcome the drawbacks and confirm the results of traditional quant methods. As it turns out, those hopes are only weakly fulfilled by the MLM framework.
The implications of wishful thinking and subjective belief choice for endogenous disagreement among investors are substantial and can vary with economic conditions:
The justification for neutralizing sectors in factor strategies is a work in progress. To date, academic researchers haven't had an empirical model to mimic the impact of removing sector "effects" on the measurement and performance of factor strategies. The authors develop and test a two-component model to address the question of, "Is Sector Neutrality in Factor Investing a Mistake?"
Given the significant growth of investment in private markets, there have been increasing demands for greater transparency in the operation and structure of private market funds. This paper aims to address questions such as whether fees are set uniformly within most funds, and if not, by how much do they vary.
While there is literature that describes the "domain" of artificial intelligence, there are very few, if any that analyze the valuation and pricing of AI stocks. The authors attempt to fill the void with a two part methodology.
This study offers valuable information to provide insights into the underlying mechanisms driving investment behavior. For example, recognizing the impact of Neuroticism on belief formation and risk perception can help explain why some investors exhibit greater aversion to stock market volatility. Similarly, understanding how Openness influences risk preferences can shed light on why certain individuals are more willing to take investment risks than others.
Our analysis highlights the importance of short campaigns for understanding the economic impact of activist hedge funds.
This study provides valuable insights into how private equity performs in regions outside North America, reflecting broader trends in global investment.
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