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...

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...

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 -...

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...

Rationally justifying Bitcoin's immense price fluctuations has remained a persistent challenge for both investors and researchers in this field. A primary reason is our potential weakness toward robustly quantifying unquantifiable risks or ambiguity in Bitcoin returns. This paper introduces a...

We examine the liquidity provision premium in cryptocurrency markets using the returns from the short reversal strategy suggested by Nagel (2012). We show that the VIX index, economic policy uncertainty (EPU) index, crash risk, tail risk, and the innovations of Tether liquidity can predict the...

Earnings forecasts can be useful for investment decisions. Research on earnings forecasts has focused on forecast performance in relation to firm characteristics, on categorizing the analysts into groups with similar behaviour and on the effect of an earnings announcement by thefirm on future...

This paper considers the problem of estimating a linear model between two heavy-tailed variables if the explanatory variable has an extremely low (or high) value. We propose an estimator for the model coefficient by exploiting the tail dependence between the two variables and prove its...