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Comments on: Nonparametric tail risk, stock returns and the macroeconomy
Camponovo, Lorenzo; Scaillet, Olivier; Trojani, Fabio - 2016
Persistent link: https://www.econbiz.de/10011518800
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Volatility modeling and Value-at-Risk (VaR) forecasting of emerging stock markets in the presence of long memory, asymmetry, and skewed heavy tails
Gencer, Hatice Gaye; Demiralay, Sercan - In: Emerging markets finance & trade : a journal of the … 52 (2016) 1/3, pp. 639-657
Persistent link: https://www.econbiz.de/10011562539
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On the statistical differences between binary forecasts and real-world payoffs
Taleb, Nassim Nicholas - In: International journal of forecasting 36 (2020) 4, pp. 1228-1240
Persistent link: https://www.econbiz.de/10012546083
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Assessing asset tail risk with artificial intelligence : the application of artificial neural network
Becker, Ying L.; Guo, Lin; Nurmamatov, Odilbek - In: Advances in Pacific Basin business, economics, and finance 8 (2020), pp. 23-52
Persistent link: https://www.econbiz.de/10012601378
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Forecasting VaR and ES using a joint quantile regression and its implications in portfolio allocation
Merlo, Luca; Petrella, Lea; Raponi, Valentina - In: Journal of banking & finance 133 (2021), pp. 1-18
Persistent link: https://www.econbiz.de/10013256440
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Forecasting gains by using extreme value theory with realised GARCH filter
Paul, Samit; Sharma, Prateek - In: IIMB management review 33 (2021) 1, pp. 64-70
Persistent link: https://www.econbiz.de/10013205188
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Observation-driven models for realized variances and overnight returns applied to value-at-risk and expected shortfall forecasting
Opschoor, Anne; Lucas, André - In: International journal of forecasting 37 (2021) 2, pp. 622-633
Persistent link: https://www.econbiz.de/10012792858
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Conditional value-at-risk forecasts of an optimal foreign currency portfolio
Kim, Dongwhan; Kang, Kyu Ho - In: International journal of forecasting 37 (2021) 2, pp. 838-861
Persistent link: https://www.econbiz.de/10012792873
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Forecasting value-at-risk using high-frequency information
Huang, Huiyu; Lee, Tae-hwy - In: Econometrics : open access journal 1 (2013) 1, pp. 127-140
In the prediction of quantiles of daily Standard&Poor’s 500 (S&P 500) returns we consider how to use high-frequency 5-minute data. We examine methods that incorporate the high frequency information either indirectly, through combining forecasts (using forecasts generated from returns sampled...
Persistent link: https://www.econbiz.de/10009776365
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Predicting loss given default in leasing : a closer look at models and variable selection
Kaposty, Florian; Kriebel, Johannes Maximilian; … - In: International journal of forecasting 36 (2020) 2, pp. 248-266
Persistent link: https://www.econbiz.de/10012414715