Meta-regression models are increasingly utilized to integrate empirical results across studies while controlling for the potential threats of data-mining and publication bias. We propose extended meta-regression models and evaluate their performance in identifying genuine empirical effects by...

The goal of this paper is to assist the trader in answering two questions: 1) "What is a reasonable performance estimate of the long-run edge of the trading system?" and, 2) "What worst-case contingencies must be tolerated in short-run performance in order to achieve the long-run expectation?"...

This paper applies the model confidence sets (MCS) procedure to a set of volatility models. A MSC is analogous to a confidence interval of parameter in the sense that the former contains the best forecasting model with a certain probability. The key to the MCS is that it acknowledges the...

Accounting fraud is a global concern representing a significant threat to the financial system stability due to the resulting diminishing of the market confidence and trust of regulatory authorities. Several tricks can be used to commit accounting fraud, hence the need for non-static regulatory...

We study overreaction and the cumulative effect of the consecutive local overreaction patterns in financial markets. The 'overreaction diamond' pattern [1] is one of the key components of a financial market bubble. The cumulative effect of the consecutive short term overreactions arising from...

The academic literature literally contains hundreds of variables that seem to predict the cross-section of expected returns. This so-called ‘anomaly zoo' has caused many to question whether researchers are using the right tests of statistical significance. But, here's the thing: even if...

The academic literature literally contains hundreds of variables that seem to predict the cross-section of expected returns. This so-called ‘anomaly zoo' has caused many to question whether researchers are using the right tests of statistical significance. But, here's the thing: even if...

Before condemning data mining one should distinguish between objective and biased data mining. The former is commendable. Even biased data mining is appropriate when used to illustrate and not to test hypotheses. In the context of testing, the problem with biased data mining arises not from the...

In a novel model mining experiment, we data mine hundreds of randomly constructed three-factor models and find that many outperform well-known models from the literature, including those with four and five factors. The results provide compelling evidence that the threshold of factor model...