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Value at Risk (VaR) models : a comparative analysis of parametric and non parametric approaches

Ajassa, Giovanni (contributor); … - 1998

Persistent link: https://www.econbiz.de/10001435254

Forecasting value at risk and expected shortfall using high-frequency data of domestic and international stock markets

Wang, Man; Cheng, Yihan - In: Journal of forecasting 41 (2022) 8, pp. 1595-1607

Persistent link: https://www.econbiz.de/10013465725

Volatility Prediction and Risk Management : An SVR-GARCH

Karasan, Abdullah; Gaygısız, Esma - 2022

This study aims first at improving volatility prediction using a machine learning model called support vector …

Persistent link: https://www.econbiz.de/10014235847

Empirical testing of models of autoregressive conditional heteroscedasticity used for prediction of the volatility of Bulgarian investment funds

Petrova, Mariana; Todorov, Teodor - In: Risks : open access journal 11 (2023) 11, pp. 1-30

forecasting the daily volatility of Bulgarian investment funds, which will support the investment community in making adequate ….1) are adapted to predict the volatility of investment funds. The current development focuses on forecasting the risk … group. The object of the study includes quantitative analysis, estimation and forecasting of daily volatility through the …

Persistent link: https://www.econbiz.de/10014436423

Risk spillovers in international equity portfolios

Bonato, Matteo; Caporin, Massimiliano; Ranaldo, Angelo - In: Journal of empirical finance 24 (2013), pp. 121-137

Persistent link: https://www.econbiz.de/10010371985

Risk spillovers in international equity portfolios

Bonato, Matteo; Caporin, Massimiliano; Ranaldo, Angelo - 2012

assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an …

Persistent link: https://www.econbiz.de/10010407672

Evaluating an EGARCH model with fat tails, skewness and leverage in forecasting VaR

Benito Muela, Sonia - In: Journal of contemporary management : JMC 4 (2015) 3, pp. 67-80

Persistent link: https://www.econbiz.de/10011392904

Assessing coherent value-at-risk and expected shortfall with extreme expectiles

Daouia, Abdelaati; Girard, Stéphane; Stupfler, Gilles - 2015

Persistent link: https://www.econbiz.de/10011302290

Volatility forecast by volatility index and its use as a risk management tool under a value-at-risk approach

Siu, Yam Wing - In: Review of Pacific Basin financial markets and policies 21 (2018) 2, pp. 1-48

Persistent link: https://www.econbiz.de/10011865598

Comparison of semi-parametric and benchmark value-at-risk models in several time periods with different volatility levels

Buczyński, Mateusz; Chlebus, Marcin - In: E-Finanse : finansowy kwartalnik internetowy 14 (2018) 2, pp. 67-82

-GARCH(1,1), CAViaR and historical simulation models in periods with contrasting volatility trends (increasing, constantly high … volatility trend. However, GARCH-st (1,1) and QML-GARCH(1,1) were found to be the most robust models in the different volatility … periods. The results show as well that the CAViaR model forecasts were less appropriate in the increasing volatility period …

Persistent link: https://www.econbiz.de/10011967246