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Publication search results
found 45 matches
- 2023
- Simon Rudkin, Wanling Qiu, Pawel Dlotko:
Uncertainty, volatility and the persistence norms of financial time series. Expert Syst. Appl. 223: 119894 (2023) - Lei Liu, Zheng Pei, Peng Chen, Hang Luo, Zhisheng Gao, Kang Feng, Zhihao Gan:
An Efficient GAN-Based Multi-classification Approach for Financial Time Series Volatility Trend Prediction. Int. J. Comput. Intell. Syst. 16(1): 40 (2023) - Pranay Pasula:
Real World Time Series Benchmark Datasets with Distribution Shifts: Global Crude Oil Price and Volatility. CoRR abs/2308.10846 (2023) - Leonard Mushunje, David Allen, Shelton Peiris:
Volatility and irregularity Capturing in stock price indices using time series Generative adversarial networks (TimeGAN). CoRR abs/2311.12987 (2023) - 2022
- Furkan Kayim:
Volatilite aktivasyon fonksiyonu ile zaman serisi tahmini (Time series forecasting with volatility activation function). Beykent University, Turkey, 2022 - Furkan Kayim, Atinç Yilmaz:
Time Series Forecasting With Volatility Activation Function. IEEE Access 10: 104000-104010 (2022) - Fengqian Ding, Chao Luo:
Interpretable cognitive learning with spatial attention for high-volatility time series prediction. Appl. Soft Comput. 117: 108447 (2022) - Muhammad Sheraz, Silvia Dedu, Vasile Preda:
Volatility Dynamics of Non-Linear Volatile Time Series and Analysis of Information Flow: Evidence from Cryptocurrency Data. Entropy 24(10): 1410 (2022) - Yuan Yang, Xu Ma:
Support Vector Machine and Granular Computing Based Time Series Volatility Prediction. J. Robotics 2022: 4163992:1-4163992:12 (2022) - Georgy Urumov, Panagiotis Chountas:
Essay on Volatility Clusters and Time Series Prediction. IS 2022: 1-7 - Ananda Chatterjee, Hrisav Bhowmick, Jaydip Sen:
Stock Volatility Prediction using Time Series and Deep Learning Approach. CoRR abs/2210.02126 (2022) - 2021
- Rohit Kaushik, Shikhar Jain, Siddhant Jain, Tirtharaj Dash:
Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility. CAAI Trans. Intell. Technol. 6(3): 265-280 (2021) - 2020
- Kyungwon Kim, Jae Wook Song:
Analyses on Volatility Clustering in Financial Time-Series Using Clustering Indices, Asymmetry, and Visibility Graph. IEEE Access 8: 208779-208795 (2020) - Nicole Barthel, Claudia Czado, Yarema Okhrin:
A partial correlation vine based approach for modeling and forecasting multivariate volatility time-series. Comput. Stat. Data Anal. 142 (2020) - Sangyeol Lee, Chang Kyeom Kim, Dongwuk Kim:
Monitoring Volatility Change for Time Series Based on Support Vector Regression. Entropy 22(11): 1312 (2020) - 2019
- Sheikh Mohammad Idrees, Mohd. Afshar Alam, Parul Agarwal:
A Prediction Approach for Stock Market Volatility Based on Time Series Data. IEEE Access 7: 17287-17298 (2019) - Han Lin Shang, Yang Yang, Fearghal Kearney:
Intraday forecasts of a volatility index: functional time series methods with dynamic updating. Ann. Oper. Res. 282(1-2): 331-354 (2019) - Giuseppina Albano, Michele La Rocca, Cira Perna:
Volatility Modelling for Air Pollution Time Series. EUROCAST (1) 2019: 176-184 - Ryotaro Miura, Lukás Pichl, Taisei Kaizoji:
Artificial Neural Networks for Realized Volatility Prediction in Cryptocurrency Time Series. ISNN (1) 2019: 165-172 - Shikhar Jain, Rohit Kaushik, Siddhant Jain, Tirtharaj Dash:
Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility. CoRR abs/1911.06704 (2019) - 2018
- Siyao Liu, Xiangyun Gao, Wei Fang, Qingru Sun, Sida Feng, Xueyong Liu, Sui Guo:
Modeling the Complex Network of Multidimensional Information Time Series to Characterize the Volatility Pattern Evolution. IEEE Access 6: 29088-29097 (2018) - Xin-Jiang He, Song-Ping Zhu:
A series-form solution for pricing variance and volatility swaps with stochastic volatility and stochastic interest rate. Comput. Math. Appl. 76(9): 2223-2234 (2018) - Qiang Zhang, Rui Luo, Yaodong Yang, Yuanyuan Liu:
Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series. CoRR abs/1811.03711 (2018) - 2017
- Dadabada Pradeepkumar, Vadlamani Ravi:
Forecasting financial time series volatility using Particle Swarm Optimization trained Quantile Regression Neural Network. Appl. Soft Comput. 58: 35-52 (2017) - Olena Liashenko, Tetyana Kravets, Kateryna Krytsun:
Econometric Modeling of Financial Time Series Volatility Using Software Packages. ICTERI 2017: 56-71 - 2016
- Jianan Han, Xiao-Ping Zhang, Fang Wang:
Gaussian Process Regression Stochastic Volatility Model for Financial Time Series. IEEE J. Sel. Top. Signal Process. 10(6): 1015-1028 (2016) - Matthew J. Lorig, Ronnie Sircar:
Portfolio Optimization under Local-Stochastic Volatility: Coefficient Taylor Series Approximations and Implied Sharpe Ratio. SIAM J. Financial Math. 7(1): 418-447 (2016) - 2015
- Madalena D. Costa, Ary L. Goldberger:
Generalized Multiscale Entropy Analysis: Application to Quantifying the Complex Volatility of Human Heartbeat Time Series. Entropy 17(3): 1197-1203 (2015) - Ranjeeta Bisoi, Pradipta Kishore Dash:
Prediction of financial time series and its volatility using a hybrid dynamic neural network trained by sliding mode algorithm and differential evolution. Int. J. Inf. Decis. Sci. 7(2): 166-191 (2015) - Jianan Han, Xiao-Ping Zhang:
Financial time series volatility analysis using Gaussian process state-space models. GlobalSIP 2015: 358-362
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