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Katleho Makatjane and Tshepiso Tsoku
This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping and backtest density forecasts, which a...
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Ramzi Nekhili and Jahangir Sultan
This paper aims at identifying a validated risk model for the cryptocurrency market. We propose a stochastic volatility model with co-jumps in return and volatility (SVCJ) to highlight the role of jumps in returns and volatility in affecting Value-at-Ris...
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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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Jaime Enrique Lincovil,Chang Chiann
Pág. 56 - 76
Evaluating forecasts of risk measures, such as value?at?risk (VaR) and expected shortfall (ES), is an important process for financial institutions. Backtesting procedures were introduced to assess the efficiency of these forecasts. In this paper, we comp...
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Luis Mª Abadie and José M. Chamorro
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Nikola Radivojevic, Milena Cvjetkovic, Sa?a Stepanov
Pág. pp. 29 - 52
In this paper the authors introduce a new hybrid approach based on the Extreme Value Theory (EVT) to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. The approach is suitable for measuring ma...
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Knowledge Chinhamu, Chun-Kai Huang, Chun-Sung Huang, Delson Chikobvu
Extreme value theory (EVT) has been widely applied in fields such as hydrology and insurance. It is a tool used to reflect on probabilities associated with extreme, and thus rare, events. EVT is useful in modeling the impact of crashes or situations of e...
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Alex Sandro Monteiro De Moraes,Antonio Carlos Figueiredo Pinto,Marcelo Cabus Klotzle
Pág. 394?437
This paper compares the performance of long-memory models (FIGARCH) with short-memory models (GARCH) in forecasting volatility for calculating value-at-risk (VaR) and expected shortfall (ES) for multiple periods ahead for six emerging markets stock indic...
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John Muteba Mwamba, Donovan Beytell
This paper uses closing prices of the BRICS (Brazil, Russia, India, China, and South Africa) financial markets to implement a risk model that generates point estimates of both Value at Risk (VaR); and Expected Shortfall (ES). The risk model is thereafter...
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