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Dependence and extreme correlation among US industry sectors

Sukcharoen, Kunlapath; Leatham, David J. - In: Studies in economics and finance 33 (2016) 1, pp. 26-49

Persistent link: https://www.econbiz.de/10011718723

Quantile graphical models : prediction and conditional independence with applications to systemic risk

Belloni, Alexandre; Chen, Mingli; Chernozhukov, Victor - 2017 - This version December 4, 2017

The understanding of co-movements, dependence, and influence between variables of interest is key in many applications. Broadly speaking such understanding can lead to better predictions and decision making in many settings. We propose Quantile Graphical Models (QGMs) to characterize prediction...

Persistent link: https://www.econbiz.de/10011775380

Tail relation between return and volume in the US stock market : an analysis based on extreme value theory

Longin, François M.; Pagliardi, Giovanni - In: Economics letters 145 (2016), pp. 252-254

Persistent link: https://www.econbiz.de/10011618837

Forecasting comparison of long term component dynamic models for realized covariance matrices

Bauwens, Luc; Braione, Manuela; Storti, Giuseppe - In: Annals of economics and statistics 123/124 (2016), pp. 103-134

Persistent link: https://www.econbiz.de/10011592738

Dynamic linkages between developed and BRICS stock markets : portfolio risk analysis

Mensi, Walid; Hammoudeh, Shawkat; Kang, Sang Hoon - In: Finance research letters 21 (2017), pp. 26-33

Persistent link: https://www.econbiz.de/10011807276

Range-based DCC models for covariance and value-at-risk forecasting

Fiszeder, Piotr; Fałdziński, Marcin; Molnár, Peter - In: Journal of empirical finance 54 (2019), pp. 58-76

Persistent link: https://www.econbiz.de/10012174846

Covariance prediction in large portfolio allocation

Trucíos, Carlos; Zevallos, Mauricio; Hotta, Luiz K.; … - In: Econometrics : open access journal 7 (2019) 2/19, pp. 1-24

Many financial decisions, such as portfolio allocation, risk management, option pricing and hedge strategies, are based on forecasts of the conditional variances, covariances and correlations of financial returns. The paper shows an empirical comparison of several methods to predict...

Persistent link: https://www.econbiz.de/10012025822

Optimizing portfolio risk of cryptocurrencies using data-driven risk measures

Bowala, Sulalitha; Singh, Japjeet - In: Journal of risk and financial management : JRFM 15 (2022) 10, pp. 1-16

recently proposed data-driven volatility forecasting approach with daily data are used to study risk forecasting for …

Persistent link: https://www.econbiz.de/10013471488

The choice of GARCH models to forecast value-at-risk for currencies (euro exchange rates), crypto assets (Bitcoin and Ethereum), gold, silver and crude oil : automated processes, statistical distribution models and the specification of the mean equation

Gohs, Andreas Marcus - 2022

windows. Since the calculated default correlation depends on the VaR forecasts, analyses are performed for different quantiles …Regular or automated processes require reliable software applications that provide accurate volatility and Value … estimates and fails. VaR prognoses are produced for extreme quantiles (up to 99.9%) and three alternative distribution …

Persistent link: https://www.econbiz.de/10013474092

Forecasting Value at Risk and expected shortfall of foreign exchange rate volatility of major African currencies via GARCH and dynamic conditional correlation analysis

Afuecheta, Emmanuel; Okorie, Idika E.; Nadarajah, Saralees - In: Computational economics 63 (2024) 1, pp. 271-304

Persistent link: https://www.econbiz.de/10014472109