Asset pricing asks the field’s central question — why do some assets earn higher returns than others — and factor investing is its practical export. This hub collects the cross-sectional literature: momentum, value, carry, quality, low-volatility, the factor-zoo debates, and machine-learning approaches to the cross-section of expected returns.
The elephant in this literature is replication decay. Documented anomalies shrink dramatically after publication, and a large fraction fail replication once you correct for data mining across hundreds of tested signals. That makes publication date and multiple-testing correction the two most informative fields in any factor paper: work that applies higher t-statistic thresholds, or tests on post-publication and international samples, deserves far more weight than a fresh anomaly with a 1990-2015 US backtest. The rigor ranking below tends to surface exactly those papers.
Related hubs: Portfolio Optimization, Machine Learning for Forecasting, Fixed Income & Rates.
Spanish Abstract: Las recomendaciones sobre la Prima de Riesgo del Mercado de los 100 libros sobre valoración y finanzas analizados (publicados entre 197
The COVID-19 pandemic has resulted in dramatic economic effects, characterized by excessive stock price volatility and a market crash. Some of the phenomena in
The battle between proponents of the Efficient Markets Hypothesis and champions of behavioral finance has never been more pitched, and there is little consensus
The paper reviews historical finance theory (MPT, CAPM, Fama-French) with minimal advanced math, focusing on conceptual discussion rather than new derivations or models. It lacks any backtests, datasets, or implementation details, serving primarily as a theoretical critique and framework proposal wi
Big data revolutionizes accounting and auditing, offering deep insights but also introducing challenges like data privacy and security. With data from IoT, social media, and transactions, traditional practices are evolving. Professionals must adapt to these changes, utilizing AI and machine learning
Behavioral finance argues that some financial phenomena can plausibly be understood using models in which some agents are not fully rational. The field has two
This is the second in a series of articles that examines the practical applications of economic thought. Its focus is on the most fundamental aspects of finance
I review 150 textbooks on corporate finance and valuation published between 1979 and 2009 by authors such as Brealey, Myers, Copeland, Damodaran, Merton, Ross,
The efficient market hypothesis is a special case in finance. It explains only tiny fractions of observed phenomena. Perhaps its major contribution is a forma
We study a two-sided singular stochastic control problem in which changes in consumption carry utility costs and the risk premium follows the mean-reverting Kim-Omberg model. Optimal consumption is reflected between two moving barriers given by thresholds that depend on the current risk premium. The
\textit{Il significato soggettivo della probabilità} (1931) by B. de Finetti \cite{deF} is unanimously considered the rise of `subjectivism’, a notion which strongly influenced both Probability and Decision Theory. What is less acknowledge is that \cite{deF} posed the foundations of modern arbitrage
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