Financial economics is a surprisingly prolific, topic redundant, asocial field, where most papers go largely ignored. Author collaboration improves scientific output, and yet financial economics seems to be one of the least cooperative empirical fields. If these trends continue, financial...

Empirical Finance is in crisis: Our most important discovery tool is historical simulation, and yet, most backtests and time series analyses published in journals are flawed. The problem is well-known to professional organizations of Statisticians and Mathematicians, who have publicly criticized...

With the advent in recent years of large financial data sets, machine learning and high-performance computing, analysts can backtest millions (if not billions) of alternative investment strategies. Backtest optimizers search for combinations of parameters that maximize the simulated historical...

We introduce Kinetic Component Analysis (KCA), a state-space application that extracts the signal from a series of noisy measurements by applying a Kalman Filter on a Taylor expansion of a stochastic process. We show that KCA presents several advantages compared to other popular noise-reduction...

One of the most exciting recent developments in financial research is the availability of new administrative, private sector and micro-level datasets that did not exist a few years ago. The unstructured nature of many of these observations, along with the complexity of the phenomena they...

Many investors rely on market experts and forecasters when making investment decisions, such as when to buy or sell securities. Ranking and grading market forecasters provides investors with metrics on which they may choose forecasters with the best record of accuracy for their particular market...

Full paper is available at: "https://ssrn.com/abstract=3193697" https://ssrn.com/abstract=3193697Most papers in the financial literature control for Type I errors (false positive rate), while ignoring Type II errors (false negative rate). This is a mistake, because a low Type I error can only be...

Most papers in the financial literature estimate the p-value associated with an investment strategy, without reporting the power of the test used to make that discovery. In this paper we provide analytic estimates to Type I and Type II errors for the Sharpe ratios of investments, and derive...

Most investment strategies uncovered by practitioners and academics are false. This partially explains the high rate of failure, especially among quantitative hedge funds (smart beta, factor investing, stat-arb, CTAs, etc.) In this paper we examine why false positives are so prevalent in...