laleh tafakori

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Armin PourkhanaliLecturer of Finance at RMIT UniversityVerified email at rmit.edu.au
mikoschUniversity of CopenhagenVerified email at math.ku.dk
Gennady SamorodnitskyCornell UniversityVerified email at cornell.edu
Jong-Min KimFull Professor of Statistics, University of Minnesota at MorrisVerified email at morris.umn.edu
Hans MannerUniversity of GrazVerified email at uni-graz.at
Alireza NematollahiShiraz UniversityVerified email at shirazu.ac.ir
Justin MunozRMIT UniversityVerified email at rmit.edu.au
Mahdi JaliliProfessor at RMIT University, Melbourne, AustraliaVerified email at rmit.edu.au
Mali AbdollahianAssociate Professor RMIT UniversityVerified email at rmit.edu.au
Johan SegersISBA, LIDAM, Université catholique de LouvainVerified email at uclouvain.be
Anna KirilioukUniversité de NamurVerified email at unamur.be
Riccardo RastelliAssistant Professor, University College DublinVerified email at ucd.ie
Azam KaramiPostdoctoral ResearcherVerified email at purdue.edu
Marco BeeProfessore di statistica economica, Università di TrentoVerified email at unitn.it
Ahmad Asgharian RezaeiRoyal Melbourne Institue of Technology (RMIT)Verified email at unimelb.edu.au
Saralees NadarajahDepartment of Mathematics, University of ManchesterVerified email at manchester.ac.uk
Kate SaundersMonash UniversityVerified email at monash.edu
Alec StephensonCSIROVerified email at csiro.au
Rasool RoozegarStatistician | Lecturer | Researcher | Data ScientistVerified email at unsw.edu.au
Philip Keith PollettProfessor of Mathematics, The University of QueenslandVerified email at maths.uq.edu.au

laleh tafakori

RMIT University

Verified email at rmit.edu.au - Homepage

Mathematical statistics Applied probability Extreme value theory Dependence modelling via copulas Time series


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Measuring systemic risk using vine-copula A Pourkhanali, JM Kim, L Tafakori, FA Fard Economic modelling 53, 63-74, 2016	60	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	39	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	5	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	4	2023
Hierarchical Classification for Account Code Suggestion J Munoz, M Jalili, L Tafakori Knowledge-Based Systems, 2022	3	2022
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
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	2	2023
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

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