This paper applies six recently developed nonparametric tests of serial independence to monthly US stock returns. Findings of previous studies based on the BDS test are sup-ported since most of the new tests also reject the random walk hypothesis. Furthermore, power properties of the new tests...

It is well documented in the literature that long-run asset prices do not follow the random walk, and their returns are not independent and identically-distributed (i.i.d.) over time. But how can this notion – long-run returns and volatilities being horizon dependent - be incorporated into...

Aim/purpose - The aim of this paper is to verify whether extremely high values of market value ratios are the symptoms of informational inefficiency of the market in a weak form. The authors intend to examine whether these phenomena co-occur with each other. Design/methodology/approach -...

We empirically investigate the short-run impact of anticipated and unanticipated unemployment rates on stock prices. We particularly examine the nonlinearity in stock market’s reaction to unemployment rate and study the effect at each individual point (quantile) of stock return distribution....

We empirically investigate the short-run impact of anticipated and unanticipated unemployment rates on stock prices. We particularly examine the nonlinearity in stock market's reaction to unemployment rate and study the effect at each individual point (quantile) of stock return distribution....

How often do jumps or price discontinuities occur on energy markets? What is the dynamics of the energy market sentiment (based on media coverage of economic fundamentals and other news events) that influence market behavior? How does the market sentiment affect the commodity returns? This study...

This paper proposes a new nonparametric test for conditional independence, which is based on the comparison of Bernstein copula densities using the Hellinger distance. The test is easy to implement because it does not involve a weighting function in the test statistic, and it can be applied in...

This paper proposes a new nonparametric test for conditional independence, which is based on the comparison of Bernstein copula densities using the Hellinger distance. The test is easy to implement because it does not involve a weighting function in the test statistic, and it can be applied in...

This paper proposes a new nonparametric test for conditional independence, which is based on the comparison of Bernstein copula densities using the Hellinger distance. The test is easy to implement because it does not involve a weighting function in the test statistic, and it can be applied in...