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Dimitrios Kartsonakis Mademlis,Nikolaos Dritsakis
Pág. 49 - 60
In several financial applications, it is extremely useful to predict volatility with the highest precision. Neural Networks alongside GARCH-type models have been extensively employed in the last decades for estimating volatility of financial indices. The...
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Douglas E. Johnston
In this paper, we provide a novel Bayesian solution to forecasting extreme quantile thresholds that are dynamic in nature. This is an important problem in many fields of study including climatology, structural engineering, and finance. We utilize results...
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Sam Bock Park, Sung-Kyoo Kim and Sangryul Lee
Studies on the characteristics of insolvent firms? earnings management are critical, as the ripple effects of a firm?s opportunistic accounting and insolvency on society can be widespread and significant. This study divides a dataset of unlisted firms in...
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Rama Krishna Yelamanchili
Pág. 109 - 114
This paper aims to study predictive ability of consumer sentiment of individual stocks. We consider two proxies for sentiment. One is explicit (Index of Consumer Sentiment, ICS), second is implicit (Broad Market Indicator, S&PBSE500) and we pick 50 stock...
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Raúl de Jesús-Gutiérrez,Roberto J. Santillán-Salgado
Pág. 127 - 141
The purpose of this work is to extend McNeil and Frey´s (2000) methodology by combining two component GARCH models and extreme value theory to evaluate the performance of the Value at Risk (VaR) and Expected Shortfall (ES) measures in the Latin American ...
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