Forbearance is important and we argue that performance evaluation should be multifaceted, akin to a Bayesian decision-maker who conducts continued due diligence and updates beliefs about returns with process information.
The implications of the competitive landscape for ETFs are mixed. On one hand, they have truly democratized investing. Investors now have access to the benefits of financial markets in one instrument that provides diversification at very low fees. Recently advertised fees on broad-based bond funds have fallen to 3bps. On the other hand, ETF providers have been able to satisfy investor demand for increasingly specialized products even though the evidence suggests they underperform. Are investors becoming worse off due to the effectiveness of the marketing strategies by providers of specialized ETFs?
Cryptocurrency and the various forms of infrastructure are currently in a stage of rapid innovation. If the manipulation embedded in PADs is widespread then the confidence in and integrity of the crypto market will suffer.
Trend follower nerd alert: This study is important because it offers a comprehensive analysis of TS momentum strategies, its unifying framework that links performance to underlying variables, and its practical implications for investors seeking to enhance their understanding of momentum investing and improve their portfolio performance.
The correlation between stocks and bonds should be a critical component of any asset allocation decision, as it impacts not only the overall risk of a diversified multi-asset class portfolio but also the risk premia one should expect to receive for taking risk in different asset classes. The problem for investors is that the correlation between stocks and bonds fluctuates extensively across time and economic regimes.
Short term return anomalies are generally dismissed in the academic literature "because they seemingly do not survive after accounting for market frictions.” In this research, short term “factors” are taken seriously and the authors argue the standard parameters may not apply for short horizons.
The findings from this Hidden Markov Model analysis provide policymakers with valuable insights into the nature and behavior of inflation regimes. This information can inform the design and implementation of monetary, fiscal, and regulatory policies to effectively manage inflation, stabilize the economy, and promote sustainable economic growth.
This article provides insights into the behavior of depositors and the role of large banks during a banking crisis, offering valuable implications for policymakers, regulators, and researchers in the field of banking and finance.
The traditional financial theory attributes security returns to market- or factor-based risk, with no role ascribed to other influences. In this research, the authors argue for including investor demand as an additional variable in explaining returns. Can changes in investor demand generate systematic changes in security returns?
The article aims to examine the role of social media in venture capital financing, its impact on disparities faced by underrepresented groups, and the mechanisms through which social media usage can facilitate venture capital funding.
The results of this research extend the literature in a number of areas including: the analyst forecast literature; the literature on behavioral accounting and finance with respect to corporate decision-making all in the context of gender; and the dominant role of the CEO on information transparency.
This study explores the degree to which fund concentration (high tracking error) affects the magnitude of excess returns and whether or not the likelihood of outperformance or underperformance are distributed similarly.
The article aims to explore the relationship between multitasking and performance for mutual fund managers, investigate the potential mechanisms and factors influencing this relationship, and provide insights for fund companies and investors regarding the implications of multitasking on fund performance.
The article aims to provide insights into the gender gaps in executive employment and compensation, explore the role of corporate culture and temporal flexibility in these gaps, and understand the factors influencing gender differences in entry, exit, and pay among top business executives.
BloombergGPT is a large language model (LLM) developed specifically for financial tasks. The authors trained the LLM on a large body of financial textual data, evaluated it on several financial language processing tasks and found it performed at a significantly higher level than several other state-of-the-art LLMs.
The article aims to explore the possibility that changes in fundamentals play a role in the attenuation of stock market anomalies, offering an alternative explanation to the prevailing arbitrage-based explanation