The impact of news from the Moscow and New York stock exchanges on the daily returns and volatilities of Baltic stock market indices is studied. A nonlinear time series model that accounts for asymmetries in conditional mean and variance functions is used for the empirical work. News from New...

The impact of news of the Moscow and New York stock market exchanges on the <p> returns and volatilities of the Baltic state stock market indices is studied using daily <p> return data for the period of 2000-2005. A nonlinear time series model that accounts <p> for asymmetries in the conditional mean and...</p></p></p>

This paper deals with the issues of identification and estimation in the canonical model of contagion advanced in Pesaran and Pick (2007). The model is a two-equation nonlinear simultaneous equations system with endogenous dummy variables; it also represents an extension of univariate threshold...

The price adjustment coefficient model of Amihud and Mendelson (1987) is shown to be suitable for estimation by the Kalman filter. A techique that, under some commonly used conditions, is asymptotically efficient. By Monte Carlo simulations it is shown that both bias and mean squared error are...

Financial markets are typically characterized by high (low) price level and low (high) volatility during boom (bust) periods, suggesting that price and volatility tend to move together with different market conditions/states. By proposing a simple heterogeneous agent model of fundamentalists and...

A new estimator of bid-ask spreads is presented. When the trade direction is known, any estimate of the spread is associated with a unique series of conjectural mid-prices derived by adjusting the observed transaction price by half the estimated spread. It is shown that the covariance of...

We develop a model to account for the long memory property in a bivariate count data framework. We propose a bivariate integer-valued fractional integrated (BINFIMA) model and apply the model to high frequency stock transaction data. The BINFIMA model allows for both positive and negative...

A model to account for the long memory property in a count data framework <p> is proposed and applied to high frequency stock transactions data. <p> The unconditional and conditional first and second order moments are <p> given. The CLS and FGLS estimators are discussed. In its empirical <p> application to...</p></p></p></p>

This thesis comprises four papers concerning modelling of financial count data. Paper [1], [2] <p> and [3] advance the integer-valued moving average model (INMA), a special case of integer-valued <p> autoregressive moving average (INARMA) model class, and apply the models to the number of <p> stock...</p></p></p>

The paper considers conditional duration models in which durations are in continuous time but measured in grouped or discretized form. This feature of recorded durations in combination with a frequently traded stock is expected to negatively influence the performance of conventional estimators....