Reading the WSJ May Make You a Better Economist
How can textual analysis of business news, specifically The Wall Street Journal (WSJ), be used to measure the state of the economy?
How can textual analysis of business news, specifically The Wall Street Journal (WSJ), be used to measure the state of the economy?
Trailing twelve-month P/E ratios account for 91% of the variation in analysts’ price targets. We construct a new kind of asset-pricing model around this fact and show that it explains the market response to earnings surprises.
The paper examines key factors that influence the performance and success of private equity investments. Specifically, it focuses on the importance of manager selection, the role of LP sophistication and skill, the relationship between fund size and performance, the potential misalignment of incentives between GPs and LPs, and the benefits and risks associated with co-investment opportunities.
Retail traders are contrarian in stocks and gold, yet the same traders follow a momentum-like strategy in cryptocurrencies. The differences are not explained by individual characteristics, investor composition, inattention, differences in fees, or preference for lottery-like assets. We conjecture that retail investors have a model where cryptocurrency price changes affect the likelihood of future widespread adoption, which leads them to further update their price expectations in the same direction.
This paper provides new evidence on the efficacy of prioritizing transactions so as to focus portfolio turnover on the trades that offer the strongest signals and hence the highest potential performance impact.
An AI analyst trained to digest corporate disclosures, industry trends, and macroeconomic indicators surpasses most analysts in stock return predictions. AI wins when information is transparent but voluminous. Humans provide significant incremental value in “Man + Machine,” which also substantially reduces extreme errors.
The authors effectively argue the case for intrinsic value and DCF based approaches to building Value factor strategies. The traditional value measures, especially the book-to-market ratio, are described as ineffective in today's market environment.
This article provides detailed insights into how high school financial education policies are implemented at the local level.
As a result of the trading required to capture the premiums that drive factor strategies investors may face significant tax liabilities. The challenge for the [...]
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 propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high-dimensional problems.
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.
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