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State space models play a key role in the estimation of time-varying sensitivities in financial markets. The objective of this book is to analyze the relative merits of modern time series techniques, such as Markov regime switching and the Kalman filter, to model structural changes in the...
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We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that...
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The paper develops a tail risk forecasting model that incorporates the wealth of economic and financial information … available to risk managers. The approach can be viewed as a regularized extension of the two-stage GARCH-EVT model of McNeil and … extreme value distribution of risk. We use a rich data set from the US equity market to explore when this additional …
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