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CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles
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Cited by:
- Cho, Jin Seo & Kim, Tae-hwan & Shin, Yongcheol, 2015.
"Quantile cointegration in the autoregressive distributed-lag modeling framework,"
Journal of Econometrics, Elsevier, vol. 188(1), pages 281-300.
- Jin Seo Cho & Tae-Hwan Kim & Yongcheol Shin, 2014. "Quantile Cointegration in the Autoregressive Distributed-Lag Modelling Framework," Working papers 2014rwp-69, Yonsei University, Yonsei Economics Research Institute.
- repec:wyi:journl:002112 is not listed on IDEAS
- Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
- Kuan, Chung-Ming & Yeh, Jin-Huei & Hsu, Yu-Chin, 2009. "Assessing value at risk with CARE, the Conditional Autoregressive Expectile models," Journal of Econometrics, Elsevier, vol. 150(2), pages 261-270, June.
- Chan, Ngai Hang & Sit, Tony, 2016. "Artifactual unit root behavior of Value at risk (VaR)," Statistics & Probability Letters, Elsevier, vol. 116(C), pages 88-93.
- James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
- Guo, Yawei & Li, Jianping & Li, Yehua & You, Wanhai, 2021. "The roles of political risk and crude oil in stock market based on quantile cointegration approach: A comparative study in China and US," Energy Economics, Elsevier, vol. 97(C).
- Kingston, Kato Gogo, 2010. "The Dynamics of Gang Criminality and Corruption in Nigeria Universities: A Time Series Analysis," MPRA Paper 28607, University Library of Munich, Germany.
- Jozef Baruník & Matěj Nevrla, 2023.
"Quantile Spectral Beta: A Tale of Tail Risks, Investment Horizons, and Asset Prices,"
Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1590-1646.
- Jozef Barun'ik & Matv{e}j Nevrla, 2018. "Quantile Spectral Beta: A Tale of Tail Risks, Investment Horizons, and Asset Prices," Papers 1806.06148, arXiv.org, revised Dec 2021.
- Ray Chou & Chun-Chou Wu & Nathan Liu, 2009. "Forecasting time-varying covariance with a range-based dynamic conditional correlation model," Review of Quantitative Finance and Accounting, Springer, vol. 33(4), pages 327-345, November.
- Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012.
"Stock return autocorrelations revisited: A quantile regression approach,"
Journal of Empirical Finance, Elsevier, vol. 19(2), pages 254-265.
- Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," University of Tübingen Working Papers in Business and Economics 24, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
- Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022.
"On the volatility of cryptocurrencies,"
Research in International Business and Finance, Elsevier, vol. 62(C).
- Thanasis Stengos & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "On the volatility of cryptocurrencies," Working Papers 2202, University of Guelph, Department of Economics and Finance.
- Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
- Grzegorz Hałaj & Christoffer Kok, 2013.
"Assessing interbank contagion using simulated networks,"
Computational Management Science, Springer, vol. 10(2), pages 157-186, June.
- Kok, Christoffer & Hałaj, Grzegorz, 2013. "Assessing interbank contagion using simulated networks," Working Paper Series 1506, European Central Bank.
- Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
- Cathy W. S. Chen & Takaaki Koike & Wei‐Hsuan Shau, 2024. "Tail risk forecasting with semiparametric regression models by incorporating overnight information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1492-1512, August.
- Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
- Bertrand Candelon & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2011.
"Backtesting Value-at-Risk: A GMM Duration-Based Test,"
Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 314-343, Spring.
- Gilbert COLLETAZ & Christophe HURLIN & Sessi TOKPAVI, 2008. "Backtesting Value-at-Risk: A GMM Duration-Based Test," LEO Working Papers / DR LEO 266, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2008. "Backtesting Value-at-Risk : A GMM Duration-based Test," Post-Print halshs-00363168, HAL.
- Candelon, B. & Colletaz, G. & Hurlin, C. & Tokpavi, S., 2009. "Backtesting value-at-risk : a GMM duration-based test," Research Memorandum 062, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- Gilbert COLLETAZ & Christophe HURLIN & Sessi TOKPAVI, 2009. "Backtesting Value-at-Risk: A GMM Duration-Based Test," LEO Working Papers / DR LEO 265, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2008. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Post-Print halshs-00364793, HAL.
- Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2008. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Post-Print halshs-00364797, HAL.
- Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2008. "Backtesting Value-at-Risk : A GMM Duration-based Test," Post-Print halshs-00363165, HAL.
- Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2008. "Backtesting Value-at-Risk : A GMM Duration-based Test," Post-Print halshs-00363146, HAL.
- Christophe Hurlin & Gilbert Colletaz & Sessi Tokpavi & Bertrand Candelon, 2008. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Working Papers halshs-00329495, HAL.
- Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2008. "Backtesting Value-at-Risk: A GMM Duration-Based-Test," Post-Print halshs-00364796, HAL.
- Clements, Michael P., 2018.
"Are macroeconomic density forecasts informative?,"
International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
- Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
- Jian, Zhihong & Wu, Shuai & Zhu, Zhican, 2018. "Asymmetric extreme risk spillovers between the Chinese stock market and index futures market: An MV-CAViaR based intraday CoVaR approach," Emerging Markets Review, Elsevier, vol. 37(C), pages 98-113.
- Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
- Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.
- Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Charle Augusto Llondono, 2011.
"Regresión del cuantil aplicada al modelo de redes neuronales artificiales. Una aproximación de la estructura CAVIAR para el mercado de valores colombiano,"
Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 29(64), pages 62-109, July.
- Charle Augusto Londoño, 2011. "Regresión del cuantil aplicada al modelo de redes neuronales artificiales," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(64), pages 62-109, July.
- Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012.
"Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests,"
Finance, Presses universitaires de Grenoble, vol. 33(1), pages 79-112.
- Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.
- Elena Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Post-Print hal-01385901, HAL.
- Donggyu Kim & Minseok Shin & Yazhen Wang, 2023.
"Overnight GARCH-Itô Volatility Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1215-1227, October.
- Donggyu Kim & Minseok Shin & Yazhen Wang, 2021. "Overnight GARCH-It\^o Volatility Models," Papers 2102.13467, arXiv.org, revised Jun 2022.
- Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
- Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
- Zagaglia, Paolo, 2008.
"Money-market segmentation in the euro area : what has changed during the turmoil?,"
Research Discussion Papers
23/2008, Bank of Finland.
- Zagaglia, Paolo, 2009. "Money-Market Segmentation in the Euro Area: What has Changed During the Turmoil?," Research Papers in Economics 2009:11, Stockholm University, Department of Economics.
- Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Philipp Ratz, 2022. "Nonparametric Value-at-Risk via Sieve Estimation," Papers 2205.07101, arXiv.org.
- Dean Fantazzini, 2024.
"Adaptive Conformal Inference for Computing Market Risk Measures: An Analysis with Four Thousand Crypto-Assets,"
JRFM, MDPI, vol. 17(6), pages 1-44, June.
- Fantazzini, Dean, 2024. "Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets," MPRA Paper 121214, University Library of Munich, Germany.
- Mateusz Buczyński & Marcin Chlebus, 2017. "Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(," Working Papers 2017-29, Faculty of Economic Sciences, University of Warsaw.
- Lyu, Yongjian & Wang, Peng & Wei, Yu & Ke, Rui, 2017. "Forecasting the VaR of crude oil market: Do alternative distributions help?," Energy Economics, Elsevier, vol. 66(C), pages 523-534.
- Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.
- Beine, Michel & Cosma, Antonio & Vermeulen, Robert, 2010.
"The dark side of global integration: Increasing tail dependence,"
Journal of Banking & Finance, Elsevier, vol. 34(1), pages 184-192, January.
- Michel Beine & Antonio Cosma & Robert Vermeulen, 2008. "The Dark Side of Global Integration: Increasing Tail Dependence," DEM Discussion Paper Series 08-03, Department of Economics at the University of Luxembourg.
- Antonio Cosma & antonio.cosma@uni.lu & Michel Beine & Robert Vermeulen, 2009. "The Dark Side of Global Integration: Increasing Tail Dependence," LSF Research Working Paper Series 09-05, Luxembourg School of Finance, University of Luxembourg.
- Adediran, Idris A. & Swaray, Raymond, 2023. "Carbon trading amidst global uncertainty: The role of policy and geopolitical uncertainty," Economic Modelling, Elsevier, vol. 123(C).
- Muhammadriyaj Faniband & Kedar Marulkar, 2020. "Do macroeconomic factors impact corporate debt? Evidence from India," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 10(1), pages 16-23, January.
- Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2011.
"Evaluating Value-at-Risk Models with Desk-Level Data,"
Management Science, INFORMS, vol. 57(12), pages 2213-2227, December.
- Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2005. "Evaluating Value-at-Risk models with desk-level data," Working Paper Series 010, North Carolina State University, Department of Economics, revised Dec 2006.
- Peter Christoffersen & Jeremy Berkowitz & Denis Pelletier, 2008. "Evaluating Value-at-Risk Models with Desk-Level Data," CREATES Research Papers 2009-35, Department of Economics and Business Economics, Aarhus University.
- Martinez-Iriarte, Julian & Montes-Rojas, Gabriel & Sun, Yixiao, 2022.
"Location-Scale and Compensated Effects in Unconditional Quantile Regressions,"
University of California at San Diego, Economics Working Paper Series
qt89z1w74z, Department of Economics, UC San Diego.
- Julián Martínez-Iriarte & Gabriel Montes-Rojas & Yixiao Sun, 2022. "Location-Scale and Compensated Effects in Unconditional Quantile Regressions," Working Papers 127, Red Nacional de Investigadores en Economía (RedNIE).
- Degiannakis, Stavros & Floros, Christos, 2013.
"Modeling CAC40 volatility using ultra-high frequency data,"
Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
- Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 Volatility Using Ultra-high Frequency Data," MPRA Paper 80445, University Library of Munich, Germany.
- Prat, Georges & Uctum, Remzi, 2011.
"Modelling oil price expectations: Evidence from survey data,"
The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 236-247, June.
- Georges Prat & Remzi Uctum, 2009. "Modelling oil price expectations: evidence from survey data," EconomiX Working Papers 2009-28, University of Paris Nanterre, EconomiX.
- Zagaglia, Paolo, 2008. "Money-market segmentation in the euro area: what has changed during the turmoil?," Bank of Finland Research Discussion Papers 23/2008, Bank of Finland.
- Wen, Danyan & Wang, Gang-Jin & Ma, Chaoqun & Wang, Yudong, 2019. "Risk spillovers between oil and stock markets: A VAR for VaR analysis," Energy Economics, Elsevier, vol. 80(C), pages 524-535.
- Timo Dimitriadis & Yannick Hoga, 2023. "Regressions under Adverse Conditions," Papers 2311.13327, arXiv.org, revised Jul 2024.
- Wang, Xinyu & Qi, Zikang & Huang, Jianglu, 2023. "How do monetary shock, financial crisis, and quotation reform affect the long memory of exchange rate volatility? Evidence from major currencies," Economic Modelling, Elsevier, vol. 120(C).
- Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
- Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
- Peter S. Sephton, 2009. "Fractional integration in agricultural futures price volatilities revisited," Agricultural Economics, International Association of Agricultural Economists, vol. 40(1), pages 103-111, January.
- Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
- Yuzhi Cai & Julian Stander, 2020.
"The Threshold GARCH Model: Estimation and Density Forecasting for Financial Returns,"
Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 395-424.
- Yuzhi Cai & Julian Stander, 2018. "The threshold GARCH model: estimation and density forecasting for financial returns," Working Papers 2018-23, Swansea University, School of Management.
- Xu, Yan & Wang, Xinyu & Liu, Hening, 2021. "Quantile-based GARCH-MIDAS: Estimating value-at-risk using mixed-frequency information," Finance Research Letters, Elsevier, vol. 43(C).
- Antonio Díaz & Carlos Esparcia, 2021.
"Dynamic optimal portfolio choice under time-varying risk aversion,"
International Economics, CEPII research center, issue 166, pages 1-22.
- Díaz, Antonio & Esparcia, Carlos, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, Elsevier, vol. 166(C), pages 1-22.
- Hagfors, Lars Ivar & Bunn, Derek & Kristoffersen, Eline & Staver, Tiril Toftdahl & Westgaard, Sjur, 2016. "Modeling the UK electricity price distributions using quantile regression," Energy, Elsevier, vol. 102(C), pages 231-243.
- Nowotarski, Jakub & Weron, Rafał, 2018.
"Recent advances in electricity price forecasting: A review of probabilistic forecasting,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
- Jakub Nowotarski & Rafal Weron, 2016. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," HSC Research Reports HSC/16/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Charles, Amélie & Darné, Olivier, 2014.
"Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013,"
Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
- Amélie Charles & Olivier Darné, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Post-Print hal-01122507, HAL.
- Nicholas Apergis, 2015. "Money Demand Sensitivity to Interest Rates: The Case of Japans Zero-Interest Rate Policy," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 5(9), pages 1043-1049, September.
- Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2022.
"Oil tail risks and the forecastability of the realized variance of oil-price: Evidence from over 150 years of data,"
Finance Research Letters, Elsevier, vol. 46(PB).
- Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Oil Tail Risks and the Forecastability of the Realized Variance of Oil-Price: Evidence from Over 150 Years of Data," Working Papers 202146, University of Pretoria, Department of Economics.
- Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016.
"Quantile Regression for Long Memory Testing: A Case of Realized Volatility,"
Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
- Paulo M.M. Rodrigues & Uwe Hassler, 2012. "Quantile regression for long memory testing: A case of realized volatility," Working Papers w201207, Banco de Portugal, Economics and Research Department.
- Wang, Guochang & Zhu, Ke & Li, Guodong & Li, Wai Keung, 2022. "Hybrid quantile estimation for asymmetric power GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 264-284.
- Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
- Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021.
"Factorisable Multitask Quantile Regression,"
Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
- Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2016. "Factorisable multi-task quantile regression," SFB 649 Discussion Papers 2016-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Hartz, Christoph & Mittnik, Stefan & Paolella, Marc, 2006. "Accurate value-at-risk forecasting based on the normal-GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2295-2312, December.
- Gian Piero Aielli, 2011. "Dynamic Conditional Correlation: On properties and estimation," "Marco Fanno" Working Papers 0142, Dipartimento di Scienze Economiche "Marco Fanno".
- Okhrin, Ostap & Ristig, Alexander & Sheen, Jeffrey R. & Trück, Stefan, 2015. "Conditional systemic risk with penalized copula," SFB 649 Discussion Papers 2015-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Stavros Degiannakis & Pamela Dent & Christos Floros, 2014.
"A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification,"
Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
- Degiannakis, Stavros & Dent, Pamela & Floros, Christos, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," MPRA Paper 80431, University Library of Munich, Germany.
- Mittnik, Stefan, 2014.
"VaR-implied tail-correlation matrices,"
Economics Letters, Elsevier, vol. 122(1), pages 69-73.
- Mittnik, Stefan, 2013. "VaR-implied tail-correlation matrices," CFS Working Paper Series 2013/05, Center for Financial Studies (CFS).
- Henry, Jérôme & Zimmermann, Maik & Leber, Miha & Kolb, Markus & Grodzicki, Maciej & Amzallag, Adrien & Vouldis, Angelos & Hałaj, Grzegorz & Pancaro, Cosimo & Gross, Marco & Baudino, Patrizia & Sydow, , 2013. "A macro stress testing framework for assessing systemic risks in the banking sector," Occasional Paper Series 152, European Central Bank.
- Yongmiao Hong, 2013. "Serial Correlation and Serial Dependence," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
- Ben Rejeb, Aymen & Arfaoui, Mongi, 2016.
"Financial market interdependencies: A quantile regression analysis of volatility spillover,"
Research in International Business and Finance, Elsevier, vol. 36(C), pages 140-157.
- Ben Rejeb, Aymen & Arfaoui, Mongi, 2014. "Financial market interdependencies: a quantile regression analysis of volatility spillover," MPRA Paper 61516, University Library of Munich, Germany.
- Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
- James W. Taylor, 2005. "Generating Volatility Forecasts from Value at Risk Estimates," Management Science, INFORMS, vol. 51(5), pages 712-725, May.
- Catania, Leopoldo & Luati, Alessandra, 2023. "Semiparametric modeling of multiple quantiles," Journal of Econometrics, Elsevier, vol. 237(2).
- George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
- Ben Ameur, H. & Prigent, J.-L., 2018.
"Risk management of time varying floors for dynamic portfolio insurance,"
European Journal of Operational Research, Elsevier, vol. 269(1), pages 363-381.
- H. Ben Ameur & Jean-Luc Prigent, 2018. "Risk management of time varying floors for dynamic portfolio insurance," Post-Print hal-03679408, HAL.
- Lin, Weidong & Taamouti, Abderrahim, 2024.
"Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach,"
International Journal of Forecasting, Elsevier, vol. 40(3), pages 1179-1188.
- Weidong Lin & Abderrahim Taamouti, 2023. "Portfolio Selection Under Non-Gaussianity And Systemic Risk: A Machine Learning Based Forecasting Approach," Working Papers 202310, University of Liverpool, Department of Economics.
- Cai, Zongwu & Xu, Xiaoping, 2009.
"Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models,"
Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 371-383.
- Cai, Zongwu & Xu, Xiaoping, 2008. "Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1595-1608.
- Xiaoping Xu & Zongwu Cai, 2013. "Nonparametric Quantile Estimations For Dynamic Smooth Coefficient Models," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
- Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
- Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
- repec:zbw:bofrdp:2008_023 is not listed on IDEAS
- Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2009.
"Copula-based nonlinear quantile autoregression,"
Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 50-67, January.
- Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2008. "Copula-Based Nonlinear Quantile Autoregression," Cowles Foundation Discussion Papers 1679, Cowles Foundation for Research in Economics, Yale University.
- Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2008. "Copula-Based Nonlinear Quantile Autoregression," Boston College Working Papers in Economics 691, Boston College Department of Economics.
- Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2008. "Copula-based nonlinear quantile autoregression," CeMMAP working papers CWP27/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ilias Chronopoulos & Aristeidis Raftapostolos & George Kapetanios, 2024.
"Forecasting Value-at-Risk Using Deep Neural Network Quantile Regression,"
Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 636-669.
- Chronopoulos, Ilias & Raftapostolos, Aristeidis & Kapetanios, George, 2023. "Forecasting Value-at-Risk using deep neural network quantile regression," Essex Finance Centre Working Papers 34837, University of Essex, Essex Business School.
- Linton, Oliver & Whang, Yoon-Jae, 2003.
"A quantilogram approach to evaluating directional predictability,"
LSE Research Online Documents on Economics
2112, London School of Economics and Political Science, LSE Library.
- Oliver Linton & Yoon-Jae Whang, 2003. "A Quantilogram Approach to Evaluating Directional Predictability," STICERD - Econometrics Paper Series 463, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Oliver Linton & Yoon-Jae Whang, 2004. "A Quantilogram Approach to Evaluating Directional Predictability," Cowles Foundation Discussion Papers 1454, Cowles Foundation for Research in Economics, Yale University.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
- repec:wyi:journl:002087 is not listed on IDEAS
- Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
- Giacomini, Raffaella & Komunjer, Ivana, 2005.
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