This paper develops a two-step estimation methodology that allows us to apply catastrophe theory to stock market … returns with time-varying volatility and to model stock market crashes. In the first step, we utilize high-frequency data to … estimate daily realized volatility from returns. Then, we use stochastic cusp catastrophe on data normalized by the estimated …

the period stock markets showed marks of bifurcations, in the second half catastrophe theory was not able to confirm this …This paper develops a two-step estimation methodology, which allows us to apply catastrophe theory to stock market … returns with time-varying volatility and model stock market crashes. Utilizing high frequency data, we estimate the daily …

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …

the period stock markets showed marks of bifurcations, in the second half catastrophe theory was not able to confirm this …This paper develops a two-step estimation methodology, which allows us to apply catastrophe theory to stock market … returns with time-varying volatility and model stock market crashes. Utilizing high frequency data, we estimate the daily …

model in several ways, it allows for all the primary stylized facts of financial asset returns, including volatility … volatility, but without the estimation problems associated with the latter, and being applicable in the multivariate setting for …

examines how well exchange rate volatility explains movements in stock market returns. The model-based predictions are …