The volatility dynamics of foreign exchanges have been the focus of research since Bollerslev’s (1986) seminal work on the generalized autoregressive conditional heteroscedasticity (GARCH) modelling. Several well-established empirical regularities may be highlighted as follows: [a] evidence of volatility clustering is detected in the exchange rates returns; [b] asymmetric effects in exchange ra...

Abstract This paper examined the association between various measures of earnings quality and stock return volatility Johannesburg Stock Exchange (JSE)-listed companies for 10 years from 2009 to 2018. The considered were accrual quality, conservatism, persistence, predictability smoothness. was measured with idiosyncratic volatility. Multilevel linear regression found that persistence are negat...

The two-country monetary model is extended to include a consumption externality with habit persistence. This is set within a limited participation framework. The model is simulated using the artificial economy methodology. The ‘puzzles’ in the forward market are re-examined. The model is able to account for (a) the persistence in the forward discount (b) the random walk in spot exchange rates (...

We propose a new semiparametric estimator of the degree of persistence in volatility for long memory stochastic volatility (LMSV) models. The estimator uses the periodogram of the log squared returns in a local Whittle criterion which explicitly accounts for the noise term in the LMSV model. Finite-sample and asymptotic standard errors for the estimator are provided. An extensive simulation stu...

I use daily futures price data to examine the behavior of natural gas and crude oil price volatility in the U.S. since 1990. I test whether there has been a significant trend in volatility, whether there was a short-term increase in volatility during the time of the Enron collapse, and whether natural gas and crude oil price volatilities are interrelated. I also measure the persistence of shock...

Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model that is able to generate volatility clustering with hyperbolically decaying autocorrelations via traders with multiple trading frequencies, using Bayesian information updates in an incomp...

In this paper we consider tests for the null of (trend-) stationarity against the alternative of a change in persistence at some (known or unknown) point in the observed sample, either from I(0) to I(1) behaviour or vice versa, of, inter alia, Kim (2000). We show that in circumstances where the innovation process displays non-stationary unconditional volatility of a very general form, which inc...

In this paper, we develop and apply Bayesian inference for an extended NelsonSiegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov chain Monte Carlo (MCMC) algorithm to efficiently estimate the SVNS model using simulation-based inference...

We propose behavioral learning equilibria as a plausible explanation of coordination of individual expectations and aggregate phenomena such as excess volatility in stock prices and high persistence in inflation. Boundedly rational agents use a simple univariate linear forecasting rule and correctly forecast the unconditional sample mean and first-order sample autocorrelation. In the long run, ...