This paper deals with the economics of Bitcoins in two ways. First, it broadens the discussion on how to capture Bitcoins using economic terms. Center stage in this analysis take the discussion of some unique characteristics of this market as well as the comparison of Bitcoins and gold. Second,...

This paper builds a model of high-frequency equity returns by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in ordinary clock time and in...

In this paper, we review econometric methodology that is used to test for jumps and to decompose realized volatility into continuous and jump components. In order to illustrate how to implement the methods discussed, we also present the results of an empirical analysis in which we separate...

In order to examine non-linear predictability of the US and Japanese dividend-yield ratio, smooth transition regression model analysis is applied to an extended time period of data. The theoretical basis for investigating non-linear behaviour in stock returns can be based on the interaction...

This paper investigates changes in persistence caused by the COVID-19 pandemic in the US and EA yield curves. We extract the long-term, short-term and medium-term factors and proxy the persistence by estimating the autoregressive coefficient of each factor. To examine the time-varying effects,...

This study evaluates whether exchange traded funds (ETFs) threaten fnancial market stability by testing two hypotheses relating the growing importance of ETFs to increased market volatility and rising equity valuations. We estimate quantile cointegration models using Standard & Poor's 500 Index...

We make use of the extant testing methodology of Barndorff-Nielsen and Shephard (2006) and Aït-Sahalia and Jacod (2009a,b,c) to examine the importance of jumps, and in particular large and small jumps, using high frequency price returns on 25 stocks in the DOW 30 and S&P futures index. In...

Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML) estimation with variance targeting, which reduces the degree of parameterization and facilitates estimation. We compare the two approaches and investigate, via simulations, how non-normality features of the...

In this paper we introduce new Dynamic Conditional Score (DCS) models for the Skew-Gen-t (Skewed Generalized t) and NIG (Normal-Inverse Gaussian) distributions as alternatives to the recent DCS models for the Student’s-t and EGB2 (Exponential Generalized Beta of the second kind) distributions,...

This paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multivariate GARCH models using volatility impulse response analysis. The data set features ten years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index from the London...