Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Habibnia, Ali"'
Autor:
Habibnia, Ali, Soltanzadeh, Mahdi
This study presents a Reinforcement Learning (RL)-based portfolio management model tailored for high-risk environments, addressing the limitations of traditional RL models and exploiting market opportunities through two-sided transactions and lending
Externí odkaz:
http://arxiv.org/abs/2408.05382
We propose a nonparametric and time-varying directed information graph (TV-DIG) framework to estimate the evolving causal structure in time series networks, thereby addressing the limitations of traditional econometric models in capturing high-dimens
Externí odkaz:
http://arxiv.org/abs/2312.16707
Autor:
Habibnia, Ali, Maasoumi, Esfandiar
This paper considers improved forecasting in possibly nonlinear dynamic settings, with high-dimension predictors ("big data" environments). To overcome the curse of dimensionality and manage data and model complexity, we examine shrinkage estimation
Externí odkaz:
http://arxiv.org/abs/1904.11145
Autor:
Habibnia, Ali
In this thesis, I study high-dimensional nonlinear time series analysis, and its applications in financial forecasting and identifying risk in highly interconnected financial networks. The first chapter is devoted to the testing for nonlinearity in f
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.706172
Akademický článek
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Financial instability and its destructive effects on the economy can lead to financial crises due to its contagion or spillover effects to other parts of the economy. Having an accurate measure of systemic risk gives central banks and policy makers t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______206::1f3cce849e87994004b905663f78113d
http://eprints.lse.ac.uk/70769/
http://eprints.lse.ac.uk/70769/
Autor:
Habibnia, Ali, Maasoumi, Esfandiar
Publikováno v:
Journal of Quantitative Economics; 20210101, Issue: Preprints p1-19, 19p