The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia,...

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and...

The integer-valued moving average model is advanced to model the number of transactions in intra-day data of stocks. The conditional mean and variance properties are discussed and model extensions to include, e.g., explanatory variables are offered. Least squares and generalized method of moment...

This paper introduces a new class of long memory model for volatility of stock returns, and applies the model on squared returns for BRICS (Brazil, Russia, India, China, and South Africa) countries. The conditional first- and second-order moments are provided. The CLS, FGLS and QML estimators...

The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia,...

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and...

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>

This thesis comprises two papers concerning modelling of financial count data. The papers advance the integer-valued moving average model (INMA), a special case of integer-valued autoregressive moving average (INARMA) model class, and apply the models to the number of stock transactions in...