The efficient market hypothesis implies that asset prices cannot be cointegrated. On the other hand, arbitrage processes prevent prices of fundamentally related assets from drifting far away. An attractive model that reconciles these two conflicting facts is the nonlinear error correction...

This paper considers the introduction of stock options in an (dynamically) incomplete securities market made up of a riskless bond and the stock. The stock price follows a geometric Brownian motion with constant drift. However, there is incomplete information about the unknown stochastic...

Although stock splits seem to be a purely cosmetic event, there exists ample empirical evidence from the United States that stock splits are associated with abnormal returns on both the announcement and the execution day, and additionally with an increase in variance following the ex-day. This...

The so-called 'Monday effect ' has been found for various stock markets of the world. The empirical finding that Monday returns are significantly smaller than returns measured for the remaining days of the week calls the efficiency hypothesis for pricing processes operating on stock markets into...

A major application of rescaled adjusted range analysis (RS analysis) is the study of price fluctuations in financial markets. There, the value of the Hurst constant, H, in a time series may be interpreted as an indicator of the irregularity of the price of a commodity, currency or similar...

We consider a financial market model with interacting agents and study the long run behaviour of both aggregate behaviour and equilibrium prices. Investors are heterogeneous in their price expectations and they get stochastic signals about the "mood" of the market described by the empirical...

We consider a financial market model with a large number of interacting agents. Investors are heterogeneous in their expectations about the future evolution of an asset price process. Their current expectation is based on the previous states of their "neighbors" and on a random signal about the...

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods. --...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...