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Time varying quantile Lasso
Zbonakova, Lenka; Härdle, Wolfgang; Wang, Weining - 2016
operator (Lasso) method proposed by Tibshirani (1996) and extended into quantile regression context by Li and Zhu (2008). The …
Persistent link: https://www.econbiz.de/10011557306
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Central limit theorems and bootstrap in high dimensions
Chernozhukov, Victor; Chetverikov, Denis; Kato, Kengo - 2014 - This version: December 11, 2014
In this paper, we derive central limit and bootstrap theorems for probabilities that centered high-dimensional vector sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the probabilities that a root-n rescaled sample average of Xi is...
Persistent link: https://www.econbiz.de/10010459841
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Central limit theorems and bootstrap in high dimensions
Chernozhukov, Victor; Chetverikov, Denis; Kato, Kengo - 2016 - This version: May 31, 2016
In this paper, we derive central limit and bootstrap theorems for probabilities that centered high-dimensional vector sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the probabilities that a root-n rescaled sample average of Xi is...
Persistent link: https://www.econbiz.de/10011525777
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Estimation risk and shrinkage in vast-dimensional fundamental factor models
Vlodrop, Andries C. van; Lucas, André - 2018
We investigate covariance matrix estimation in vast-dimensional spaces of 1,500 up to 2,000 stocks using fundamental factor models (FFMs). FFMs are the typical benchmark in the asset management industry and depart from the usual statistical factor models and the factor models with observed...
Persistent link: https://www.econbiz.de/10011949129
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Testing endogeneity with high dimensional covariates
Guo, Zijian; Kang, Hyunseung; Cai, T. Tony; Small, Dylan S. - In: Journal of econometrics 207 (2018) 1, pp. 175-187
Persistent link: https://www.econbiz.de/10012116193
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High-dimensional censored regression via the penalized Tobit likelihood
Jacobson, Tate; Zou, Hui - In: Journal of business & economic statistics : JBES ; a … 42 (2024) 1, pp. 286-297
Persistent link: https://www.econbiz.de/10014449928
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A pricing problem with unknown arrival rate and price sensitivity
Avramidis, Athanassios N. - In: Mathematical methods of operations research : ZOR 92 (2020) 1, pp. 77-106
Persistent link: https://www.econbiz.de/10012301647
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CVaR regression based on the relation between CVaR and mixed-quantile quadrangles
Golodnikov, Alex; Kuzmenko, Viktor; Uryasev, Stan - In: Journal of risk and financial management : JRFM 12 (2019) 3/107, pp. 1-22
A popular risk measure, conditional value-at-risk (CVaR), is called expected shortfall (ES) in financial applications. The research presented involved developing algorithms for the implementation of linear regression for estimating CVaR as a function of some factors. Such regression is called...
Persistent link: https://www.econbiz.de/10012025262
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Whence LASSO? A Rational Interpretation
Chen, Wen; Hu, Bo; Yang, Liyan - 2023
This paper rationalizes the LASSO algorithm based on uncertain fat-tail priors and max-min robust optimization. Our … rationalization excludes heuristic learning or restrictive prior assumptions in the original interpretation of LASSO (Tibshirani (1996 … reasonable range of ambiguous signals but respond linearly to almost unambiguous signals. With this LASSO equivalent strategy …
Persistent link: https://www.econbiz.de/10014235781
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Cost-restricted feature selection for data acquisition
Liu, Xiaoping; Li, Xiao-Bai; Sarkar, Sumit - In: Management science : journal of the Institute for … 69 (2023) 7, pp. 3976-3992
Persistent link: https://www.econbiz.de/10014338318