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...

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 realized volatility from the returns in the first step and...

Agent-based models are usually claimed to generate complex dynamics; however, the link to such complexity has not been subject to rigorous examination. This paper studies this link between the complexity of financial time series---measured by their multifractal properties---and the design of...