We conduct an extensive examination of the profitability of technical analysis in ten emerging foreign exchange markets. Studying 25,988 trading strategies for emerging foreign exchange markets, we find that the best rules can sometimes generate an annual mean excess return of more than 30%....

Reliably detecting insider trading is a major impediment to both research and regulatory practice. Using account-level transaction data, we propose a novel approach. Specifically, after extracting several key empirical features of typical insider trading cases from existing regulatory actions,...

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...

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...

This paper proposes a test for the signal-to-noise ratio applicable to a range of significance tests and model diagnostics in a linear regression. It is particularly useful under a large or massive sample size, where a conventional test frequently rejects an economically negligible deviation...

Computational methods to gauge investor sentiment from commonly used online data sources that rely on machine learning classifiers and lexicons have shown considerable promise, but suffer from measurement and classification errors. In our work, we develop a simple, direct and unambiguous...

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...