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Forecasting financial volatility of the Athens stock exchange daily returns : an application of the asymmetric normal mixture GARCH model

Drakos, Anastassios A.; Kouretas, Georgios P.; … - In: International journal of finance & economics : IJFE 15 (2010) 4, pp. 331-350

Persistent link: https://www.econbiz.de/10008811307

Asset allocation in the Athens stock exchange : a variance sensitivity analysis

Diamandis, Panayotis F.; Drakos, Anastassios A.; … - In: International journal of finance & economics : IJFE 17 (2012) 2, pp. 167-181

Persistent link: https://www.econbiz.de/10009615696

Testing the long-memory features in return and volatility of NSE index

Ahamed, Naseem; Kalita, Mamoni; Tiwari, Aviral Kumar - In: Theoretical economics letters 5 (2015) 3, pp. 431-440

Persistent link: https://www.econbiz.de/10011396558

Long memory analysis : an empirical investigation

Nazarian, Rafik; Naderi, Esmaeil; Gandali Alikhani, Nadiya - In: International journal of economics and financial issues … 4 (2014) 1, pp. 16-26

Persistent link: https://www.econbiz.de/10010519739

Effects of asset frequency components on value-at-risk in emerging and developed markets : analyses with MODWT and CWT wavelets

Biage, Milton; Nelcide, Pierre Joseph - In: Brazilian review of econometrics : BRE ; the review of … 40 (2020) 1, pp. 145-207

Persistent link: https://www.econbiz.de/10012271374

Stochastic volatility in the Peruvian stock market and exchange rate returns : a Bayesian approximation

Alanya, Willy; Rodriguez, Gabriel - In: Journal of emerging market finance 17 (2018) 3, pp. 354-385

Persistent link: https://www.econbiz.de/10011964842

Predicting stock market volatility using MODWT with HyFIS and FS.HGD models

Alenezy, Abdullah H.; Mohd Tahir Ismail; Sadam Al-Wadi; … - In: Risks : open access journal 11 (2023) 7, pp. 1-16

We enhance the precision of predicting daily stock market price volatility using the maximum overlapping discrete wavelet transform (MODWT) spectral model and two learning approaches: the heuristic gradient descent (FS.HGD) and hybrid neural fuzzy inference system (HyFIS). The FS.HGD approach...

Persistent link: https://www.econbiz.de/10014335933