Estimating the integrated covariance matrix (ICM) from high frequency financial trading data is crucial to reflect the volatilities and covariations of the underlying trading instruments. Such an objective is difficult due to contaminated data with microstructure noises, asynchronous trading...

We consider modeling and forecasting a variety of asset return volatility series by adding a random level shift component to the usual long-memory ARFIMA model. We propose a parametric state space model with an accompanying estimation and forecasting framework that combines long memory and level...

The present paper tests for the existence of multicointegration between real per capita private consumption expenditure and real per capita disposable personal income in the USA. In doing so, we exploit the fact that the flows of disposable income and consumption expenditure on the one hand, and...

The globalisation on financial markets and the development of financial derivatives has increased not only chances but also potential risk within the banking industry. Especially market risk has gained major significance since market price variation of interest rates, stocks or exchange rates...

This thesis consists of four self-contained papers related to banking, credit markets and financial stability. Paper [I] presents a credit market model and finds, using an agent based modeling approach, that credit crunches have a tendency to occur; even when credit markets are almost entirely...

We define risk spillover as the dependence of a given asset variance on the past covariances and variances of other assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an international equity portfolio. According to the risk...

This paper extends previous studies in modeling and estimating energy demand functions for both gasoline and kerosene petroleum products for Nigeria from 1977 to 2008. In contrast to earlier studies on Nigeria and other developing countries, this study specifically tests for the possibility of...

This paper aims to develop new methods for statistical inference in a class of stochastic volatility models for financial data based on non-Gaussian Ornstein-Uhlenbeck (OU) processes. Our approach uses indirect inference methods: First, a quasi-likelihood for the actual data is estimated. This...

This paper extends the ordinary quasi-likelihood estimator for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck (OU) processes to vector processes. Despite the fact that multivariate modeling of asset returns is essential for portfolio optimization and risk management --...

We use a dynamic factor model and a detailed panel data set with quarterly accounts data on all Norwegian banks to study the effects of banks' funding costs on their retail rates. Banks' funds are categorized into two groups: customer deposits and long-term wholesale funding (market funding from...