22 datasets found

The paper analyses the impact of persistence and volatility in the discount rate in present-value models on cointegration tests in levels and in logarithms. In simulations we...

Using a fad model with Markov-switching heteroscedasticity in both the fundamental and fad components (UC-MS model), this paper examines the possibility that the 1987 stock...

This paper addresses the problem of testing for the presence of a stochastic bubble in a time series in the case that the bubble is periodically collapsing so that the asset...

In this paper we present an exact maximum likelihood treatment for the estimation of a Stochastic Volatility in Mean (SVM) model based on Monte Carlo simulation methods. The SVM...

Bull and bear markets are a common way of describing cycles in equity prices. To fully describe such cycles one would need to know the data generating process (DGP) for equity...

This paper considers Markov error-correction (MEC) models in which deviations from the long-run equilibrium are characterized by different rates of adjustment. To motivate our...

Using annual data for 1872-1997, this paper re-examines the predictability of real stock prices based on price-dividend and price-earnings ratios. In line with the extant...

We compare 330 ARCH-type models in terms of their ability to describe the conditional variance. The models are compared out-of-sample using DM?$ exchange rate data and IBM...

This study examines the long-run price relationship and the dynamic price transmission among the USA, Germany, and four major Eastern European emerging stock markets, with...

We apply extreme value analysis to US sectoral stock indices in order to assess whether tail risk measures like value-at-risk and extremal linkages were significantly altered by...

Using Bayesian Markov chain Monte Carlo methods, we decompose the log price-dividend ratio into a market fundamentals component and a bubble component. The market fundamentals...

This paper assesses the robustness of the relative performance of spot? and options-based volatility forecasts to the treatment of microstructure noise. Robustness of the...

Recently, Duarte and Young (2009) studied the probability of informed trading (PIN) proposed by Easley et al. (2002) and decomposed it into two parts: the adjusted PIN (APIN) as...

We propose a local adaptive multiplicative error model (MEM) accommodating time-varying parameters. MEM parameters are adaptively estimated based on a sequential testing...

We investigate the relationship between long-term US stock market risks and the macroeconomic environment using a two-component GARCH-MIDAS model. Our results show that...

This paper develops a novel approach to information-based securities trading by characterizing the hidden state of the market, which varies following a Markov process. Extensive...

We investigate the effects of fragmentation in equity markets on the quality of trading outcomes in a panel of FTSE stocks over the period 2008-2011. This period coincided with...

This paper provides a characterisation of the degree of cross-sectional dependence in a two dimensional array, {xit,i = 1,2,...N;t = 1,2,...,T} in terms of the rate at which the...

We analyze the contribution of credit spread, house and stock price shocks to the US economy based on a time-varying parameter vector autoregressive model. We find that the...

We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso-type estimators to reduce the dimensionality...