I use a time-varying parameter model in order to study the predictability of monthly real stock returns in Germany over the period 1880?1913. I find that the extent to which returns were predictable underwent significant changes over time. Specifically, predictability of returns, as measured by...

We examine the performance of volatility models that incorporate features such as long (short) memory, regime-switching and multifractality along with two competing distributional assumptions of the error component, i.e. Normal vs Student-t. Our precise contribution is twofold. First, we...

Modelling and forecasting the covariance of financial return series has always been a challenge due to the so-called curse of dimensionality. This paper proposes a methodology that is applicable in large dimensional cases and is based on a time series of realized covariance matrices. Some...

This paper examines the degree of persistence in the volatility of financial time series using a Long Memory Stochastic Volatility (LMSV) model. Specifically, it employs a Gaussian semiparametric (or local Whittle) estimator of the memory parameter, based on the frequency domain, proposed by...

This paper focuses on nominal exchange rates, specifically the US dollar rate vis-à-vis the Euro and the Japanese Yen at a daily frequency. We model both absolute values of returns and squared returns using long-memory techniques, being particularly interested in volatility modelling and...

Realized volatility is a nonparametric ex-post estimate of the return variation. The most obvious realized volatility measure is the sum of finely-sampled squared return realizations over a fixed time interval. In a frictionless market, the estimate achieves consistency for the underlying...

I examine whether or not returns on stock markets are a leading indicator for real macroeconomic developments in Austria, Japan and the USA. Further I deal with the concept of stock market efficiency, the question whether or not information from real and financial sectors of the economy is...

Simulations of agent-based models have shown that the stylized facts (unit-root, fat tails and volatility clustering) of financial markets have a possible explanation in the interactions among agents. However, the complexity, originating from the presence of non-linearity and interactions, often...

Simulations of agent-based models have shown that the stylized facts (unit-root, fat tails and volatility clustering) of financial markets have a possible explanation in the interactions among agents. However, the complexity, originating from the presence of non-linearity and interactions, often...

Multi-fractal processes have been proposed as a new formalism for modeling the time series of returns in finance. The major attraction of these processes is their ability to generate various degrees of long memory in different powers of returns - a feature that has been found to characterize...