This paper identifies the Multifractal Models of Asset Return (MMARs) from the eight nodal term structure series of US Treasury rates as well as the Fed Funds rate and, after proper synthesis, simulates those MMARs. We show that there is an inverse persistence term structure in the sense that...

In the present paper we suggest to model Realized Volatility, an estimate of daily volatility based on high frequency data, as an Inverse Gaussian distributed variable with time varying mean, and we examine the joint properties of Realized Volatility and asset returns. We derive the appropriate...

This study examines the forecastability of ASEAN-5 stock market returns using linear and non-linear time series models. Time series models with GARCH errors are also considered. Based on formal econometrics tests, this study shows that the behaviour of these returns do not follow random walk...

A prediction model is any statement of a probability distribution for an outcome not yet observed. This study considers the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule. The log score is a concave...

Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative...

This paper presents theoretical models and their empirical results for the return and variance dynamics of German stocks. A factor structure is used in order to allow for a parsimonious modeling of the first two moments of returns. Dynamic factor models with GARCH dynamics (GARCH(1,1)-M,...