| Super (a, d)-H-antimagic total labelings for shackles of a connected graph H. N Inayah, R Simanjuntak, ANM Salman, KIA Syuhada Australas. J Comb. 57, 127-138, 2013 | 98 | 2013 |
| Comparing gold’s and Bitcoin’s safe-haven roles against energy commodities during the COVID-19 outbreak: A vine copula approach K Syuhada, D Suprijanto, A Hakim Finance Research Letters 46, 102471, 2022 | 40 | 2022 |
| Covid-19 risk data during lockdown-like policy in Indonesia K Syuhada, A Wibisono, A Hakim, F Addini Data in Brief 35, 106801, 2021 | 39 | 2021 |
| Improved Prediction Limits For AR(p) and ARCH(p) Processes P Kabaila, K Syuhada Journal of Time Series Analysis 29 (2), 213-223, 2008 | 33 | 2008 |
| The expected-based value-at-risk and expected shortfall using quantile and expectile with application to electricity market data K Syuhada, A Hakim, R Nur’aini Communications in Statistics-Simulation and Computation 52 (7), 3104-3121, 2023 | 15 | 2023 |
| The asymptotic efficiency of improved prediction intervals P Kabaila, K Syuhada Statistics & probability letters 80 (17-18), 1348-1353, 2010 | 15 | 2010 |
| Modeling risk dependence and portfolio VaR forecast through vine copula for cryptocurrencies K Syuhada, A Hakim PLoS One 15 (12), e0242102, 2020 | 14 | 2020 |
| Is Tether a safe haven of safe haven amid COVID-19? An assessment against Bitcoin and oil using improved measures of risk K Syuhada, A Hakim, D Suprijanto, I Muchtadi-Alamsyah, L Arbi Resources Policy 79, 103111, 2022 | 12 | 2022 |
| The improved Value-at-Risk for heteroscedastic processes and their coverage probability K Syuhada Journal of Probability and Statistics 2020, 1-5, 2020 | 10 | 2020 |
| Dependent conditional value-at-risk for aggregate risk models BP Josaphat, K Syuhada Heliyon 7 (7), 2021 | 9 | 2021 |
| Value-at-risk and expected shortfall relationship AA Rohmawati, K Syuhada International Journal of Applied Mathematics and Statistics 53 (5), 211-215, 2015 | 8 | 2015 |
| The relative efficiency of prediction intervals P Kabaila, K Syuhada Communications in Statistics—Theory and Methods 36 (15), 2673-2686, 2007 | 8 | 2007 |
| Estimating copula-based extension of tail value-at-risk and its application in insurance claim K Syuhada, O Neswan, BP Josaphat Risks 10 (6), 113, 2022 | 6 | 2022 |
| Quantile-based estimative VaR forecast and dependence measure: A simulation approach K Syuhada, R Nur’aini, Mahfudhotin Journal of applied mathematics 2020, 1-14, 2020 | 5 | 2020 |
| Dependent metaverse risk forecasts with heteroskedastic models and ensemble learning K Syuhada, V Tjahjono, A Hakim Risks 11 (2), 32, 2023 | 4 | 2023 |
| Modifying (M) CoVaR and constructing tail risk networks through analytic higher-order moments: Evidence from the global forex markets A Hakim, ANM Salman, Y Ashari, K Syuhada Plos one 17 (11), e0277756, 2022 | 4 | 2022 |
| Bounds of Adj-TVaR Prediction for Aggregate Risk K Syuhada InPrime: Indonesian Journal of Pure and Applied Mathematics 1 (1), 1-7, 2019 | 4 | 2019 |
| Bivariate control chart with copula T Lestari, K Syuhada, U Mukhaiyar AIP Conference Proceedings 1692 (1), 2015 | 4 | 2015 |
| Assessing systemic risk and connectedness among dirty and clean energy markets from the quantile and expectile perspectives K Syuhada, A Hakim, D Suprijanto Energy Economics 129, 107261, 2024 | 3 | 2024 |
| Formulating MCoVaR to Quantify Joint Transmissions of Systemic Risk across Crypto and Non-Crypto Markets: A Multivariate Copula Approach A Hakim, K Syuhada Risks 11 (2), 35, 2023 | 3 | 2023 |
