With this study, we aim to determine the effect of Covid-19 pandemic on return volatility DJI, DAX, FTSE100 and CAC40 stock indexes. We take between 1st January 2019 17th July 2020 split it into two separate periods - before outbreak first wave ‘In-Pandemic’ period. Only so-called was chosen avoid influence knowledge possible vaccines antiviral solutions. Data were analysed by using exponential...

A common finding in the empirical literature is that financial volatility exhibits high persistence, or slow mean reversion of the order of months. We present evidence that financial volatility data contains more than a single time scale. After showing that the expectation of the sum of the estimates of the autoregressive coefficients of a GARCH(1,1) model is one when there are unknown paramete...

In this paper we analyze the consequences of considering risk-augmented speci cations of the relationship between spot and forward rates. Previous parametric speci cations such as the GARCH-M provided disappointing results possibly due to the high degree of persistence of the estimated process for conditional volatility. We propose a more exible semiparametric approach where a nonparametric est...

We present a novel GARCH model that accounts for time varying, state dependent, persistence in the volatility dynamics. The proposed model generalizes the component GARCH model of Ding and Granger (1996). The volatility is modelled as a convex combination of unobserved GARCH components where the combination weights are time varying as a function of appropriately chosen state variables. In order...

The estimation of the memory parameter in perturbed long memory series has recently attracted attention motivated especially by the strong persistence of the volatility of many financial and economic time series and the use of Long Memory in Stochastic Volatility (LMSV) processes to model such a behaviour. This paper proposes an extension of the log periodogram regression which explicitly accou...

This paper employs a Generalised Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) model to consider the effect of macroeconomic factors on Australian property returns over the period 1985 to 2002. Three direct (office, retail and industrial property) and two indirect (listed property trust and property stock) returns are included in the analysis, along with market returns, short,...

This paper explores some of the empirical features generated in an agent-based computational stock market with market participants adapting and evolving over time. Investors view differing lengths of past information as being relevant to their investment decision making process. The interaction of these memory lengths in determining market prices creates a kind of market ecology in which it is ...

A distinguishing feature of the intra-day time-varying volatility of financial time series is given by the presence of long-range dependence of periodic type due mainly to time-of-the-day phenomena. In this work we introduce a model able to describe the empirical evidence given by this periodic longmemory behaviour. The model, named PLM-GARCH (Periodic Long Memory GARCH), represents a natural e...

A major issue in nancial economics is the behaviour of stock returns over long horizons. This study provides empirical evidence of the long-range behaviour of various speculative returns. Using di erent techniques such as R=S and modi ed R=S analysis, detrended uctuation analysis (DFA), fractional di erencing test (GPH) and ARFIMA maximum likelihood estimation, we nd little evidence of long mem...

In this paper we examine the characteristics of market opening news and its impact on the estimated coe cients of the conditional volatility models of the GARCH class. We nd that the di erences between the opening price of one day and the closing price of the day before have di erent characteristics when considering various stock market indices on which options are actively traded. The impact o...