We examine the impact of tail risk on the return dynamics of size, book-to-market ratio, momentum, and idiosyncratic volatility sorted portfolios. Our time-series analyses document significant portfolio return exposures to aggregate tail risk. In particular, portfolios that contain small, value,...

Investment decisions may be evaluated via several different metrics/criteria, which are functions of a vector of value drivers. The economic significance and the reliability of a metric depend on its compatibility with the Net Present Value (NPV). Traditionally, a metric is said to be...

In the paper, we research on the presence of long-range dependence in returns and volatility of BUX, PX and WIG between years 1997 and 2009 with use of classical and modified rescaled range. Moving block bootstrap with pre-whitening and postblackening is used for the construction of confidence...

Over the last three decades, the world economy has been facing stock market crashes, currency crisis, the dot-com and real estate bubble burst, credit crunch and banking panics. As a response, extreme value theory (EVT) provides a set of ready-made approaches to risk management analysis....

In this paper, the author uses geometrical and topological aspects of Exploratory Data Analysis (EDA) to examine Standard and Poor's (S&P), MSCI's and Thomson Reuters' (TRI) ways of determining which stocks are growth and which are value. The results of the analysis are that two of the firms -...

Following seminal works of Knight (1921) and Ellsberg (1961), we distinguish uncertainty from risk and examine the impact of aggregate uncertainty on return dynamics of size and book-to-market ratio sorted portfolios. Using VVIX as a proxy for aggregate uncertainty and controlling for market...

This paper proposes a novel standardized test for abnormal returns in long-horizon event studies that takes into account cross-sectional correlation, autocorrelation, and hetersoskedasticity of stock returns. Extensive simulation analyses demonstrate improved size and power of testing relative...

Taking advantage of granular data we measure the change in bank capital requirement resulting from the implementation of AI techniques to predict corporate defaults. For each of the largest banks operating in France we design an algorithm to build pseudo-internal models of credit risk management...

Taking advantage of granular data we measure the change in bank capital requirement resulting from the implementation of AI techniques to predict corporate defaults. For each of the largest banks operating in France we design an algorithm to build pseudo-internal models of credit risk management...

This paper introduces a new trading strategy in investment: to include the asset (Asset A) with the highest mean, the asset (Asset B) that stochastically dominates many other assets, and the asset (Asset C) with the smallest standard deviation in their portfolio to form the portfolio in the...