I examine 468 estimates on the relationship between trading volume and stock returns reported in 44 studies. I deploy recent nonlinear techniques for detecting publication bias together with Bayesian and frequentist model averaging to evaluate the heterogeneity in the estimates. The results...

Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major...

This paper proposes computational framework for empirical estimation of Financial Agent-Based Models (FABMs) that does not rely upon restrictive theoretical assumptions. We customise a recent methodology of the Non-Parametric Simulated Maximum Likelihood Estimator (NPSMLE) based on kernel...

We study the impact of news embedded in scheduled macroeconomic announcements on the government bond market in Poland and the Czech Republic. We conduct an event study on intraday data and time-series regressions using daily data over an eight-year period, distinguishing between effects under...

We examine time-varying explanatory power of realized moments on subsequent bond futures excess returns using more than 12 years of high-frequency data from U.S. and German sovereign bond markets. We detect realized volatility and realized kurtosis to carry valuable information for next-day...

We develop a four-factor model intended to capture size, value, and credit rating transition patterns in excess returns for a panel of predominantly mid- and large-cap entities. Using credit transition matrices and rating histories from 48 US issuers, we provide evidence to support a...

We examine how extreme market risks are priced in the cross-section of asset returns at various horizons. Based on the frequency decomposition of covariance between indicator functions, we define the quantile cross-spectral beta of an asset capturing tail-specific as well as horizon-, or...

We study the role of the choice of a fundamental database on the portfolio returns of a set of 74 fundamental anomalies. We benchmark Compustat by comparing it to Datastream in the US and find systematic differences in the raw financial statements across the databases. These differences only...

Measuring risk in the stock market context is one of the key challenges of modern finance. Despite of the substantial significance of the topic to investors and market regulators, there is a controversy over what risk factors should be used to price the assets or to determine the cost of...

Using daily return data from the four major Central and Eastern European stock markets including fourteen highly liquid stocks and ATX (Vienna), PX (Prague), BUX (Budapest), and WIG20 (Warsaw) market indices, we model the value-at-risk using a set of univariate GARCH-type models. Our results...