Measuring systemic risk using vine-copula A Pourkhanali, JM Kim, L Tafakori, FA Fard Economic modelling 53, 63-74, 2016 | 61 | 2016 |
Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae H Manner, FA Fard, A Pourkhanali, L Tafakori Energy Economics 78, 143-164, 2019 | 40 | 2019 |
Forecasting spikes in electricity return innovations L Tafakori, A Pourkhanali, FA Fard Energy 150, 508-526, 2018 | 18 | 2018 |
Fractional moments of solutions to stochastic recurrence equations T Mikosch, G Samorodnitsky, L Tafakori Journal of Applied Probability 50 (4), 969-982, 2013 | 18 | 2013 |
An estimator of the stable tail dependence function based on the empirical beta copula A Kiriliouk, J Segers, L Tafakori Extremes 21, 581-600, 2018 | 17 | 2018 |
Measuring systemic risk and contagion in the European financial network L Tafakori, A Pourkhanali, R Rastelli Empirical Economics, 1-45, 2022 | 15 | 2022 |
Image denoising using generalised Cauchy filter A Karami, L Tafakori IET Image Processing 11 (9), 767-776, 2017 | 14 | 2017 |
Distance covariance for discretized stochastic processes H Dehling, M Matsui, T Mikosch, G Samorodnitsky, L Tafakori Bernoulli 26 (4), 2758-2789, 2020 | 13 | 2020 |
Estimation of the tail index for lattice-valued sequences M Matsui, T Mikosch, L Tafakori Extremes 16, 429-455, 2013 | 13 | 2013 |
Deep learning based bi-level approach for proactive loan prospecting J Munoz, AA Rezaei, M Jalili, L Tafakori Expert Systems with Applications 185, 115607, 2021 | 8 | 2021 |
Predicting age at onset of type 1 diabetes in children using regression, artificial neural network and Random Forest: A case study in Saudi Arabia A Alazwari, M Abdollahian, L Tafakori, A Johnstone, RA Alshumrani, ... PloS one 17 (2), e0264118, 2022 | 6 | 2022 |
Hierarchical Classification for Account Code Suggestion J Munoz, M Jalili, L Tafakori Knowledge-Based Systems, 2022 | 6 | 2022 |
Predicting the development of T1D and identifying its Key Performance Indicators in children; a case-control study in Saudi Arabia A Alazwari, A Johnstone, L Tafakori, M Abdollahian, AM AlEidan, ... Plos one 18 (3), e0282426, 2023 | 5 | 2023 |
Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect A Pourkhanali, L Tafakori, M Bee International Review of Financial Analysis 89, 102803, 2023 | 3 | 2023 |
A new lifetime model with different types of failure rate L Tafakori, A Pourkhanali, S Nadarajah Communications in Statistics-Theory and Methods 47 (16), 4006-4020, 2018 | 3 | 2018 |
A class of continuous kernels and Cauchy type heavy tail distributions AR Soltani, L Tafakori Statistics & Probability Letters 83 (4), 1018-1027, 2013 | 3 | 2013 |
On Comparison of the Tail Index of Heavy Tail Distributions Using Pitman’s Measure of Closeness AR Nematollahi, L Tafakori Appl. Math. Sci 1 (19), 909-914, 2007 | 3 | 2007 |
The MELBS team winning entry for the EVA2017 competition for spatiotemporal prediction of extreme rainfall using generalized extreme value quantiles AG Stephenson, K Saunders, L Tafakori Extremes 21, 477-484, 2018 | 2 | 2018 |
Some analytical results on bivariate stable distributions with an application in operational risk L Tafakori, M Bee, AR Soltani Quantitative Finance, 2022 | 1 | 2022 |
Supplement to “Distance covariance for discretized stochastic processes.” H Dehling, M Matsui, T Mikosch, G Samorodnitsky, L Tafakori | 1 | 2020 |