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Bootstrap inference under cross-sectional dependence
Conley, Timothy G.; Gonçalves, Sílvia; Kim, Min Seong; … - In: Quantitative economics : QE ; journal of the … 14 (2023) 2, pp. 511-569
In this paper, we introduce a method of generating bootstrap samples with unknown patterns of cross …-sectional/spatial dependence, which we call the spatial dependent wild bootstrap. This method is a spatial counterpart to the wild dependent … bootstrap of Shao (2010) and generates data by multiplying a vector of independently and identically distributed external …
Persistent link: https://www.econbiz.de/10014308576
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Global and Asset Class Diversified ETF Portfolio Strategy - A Convex Mean/CVaR Optimization Approach using Dynamic Copulas with Flexible Probabilities
Mantesso F, Flavio; Ahmed, Joe; Flores, Mauro - 2023
One of the most important factors to control for the achievements of investment portfolio returns is risk. If we only think that a 100% positive return is needed to recover a portfolio loss of 50%, we can understand why. With the advent of the exponential growth of technology usage in markets,...
Persistent link: https://www.econbiz.de/10014254526
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Changes in the span of systematic risk exposures
Liao, Yuan; Todorov, Viktor - In: Quantitative economics : QE ; journal of the … 15 (2024) 3, pp. 817-847
the statistic under the null hypothesis and develop an easy-to-implement bootstrap for constructing the critical region of …
Persistent link: https://www.econbiz.de/10015053883
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Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; … - 2014
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...
Persistent link: https://www.econbiz.de/10011346044
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Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; … - 2014
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...
Persistent link: https://www.econbiz.de/10010382148
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Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; … - 2014
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...
Persistent link: https://www.econbiz.de/10010386488
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Do maternal health problems influence child's worrying status? : evidence from British cohort study
Dai, Xianhua; Härdle, Wolfgang; Yu, Keming - 2014
The influence of maternal health problems on child's worrying status is important in practice in terms of the intervention of maternal health problems early for the influence on child's worrying status. Conventional methods apply symmetric prior distributions such as a normal distribution or a...
Persistent link: https://www.econbiz.de/10010253468
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Factorisable sparse tail event curves
Chao, Shih-Kang; Härdle, Wolfgang; Yuan, Ming - 2015
In this paper, we propose a multivariate quantile regression method which enables localized analysis on conditional quantiles and global comovement analysis on conditional ranges for high-dimensional data. The proposed method, hereafter referred to as FActorisable Sparse Tail Event Curves, or...
Persistent link: https://www.econbiz.de/10011296776
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Bayesian Exploratory Factor Analysis
Conti, Gabriella - 2014
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...
Persistent link: https://www.econbiz.de/10013049750
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Wavelet Improvement in Turning Point Detection Using a Hidden Markov Model
Li, Yushu - 2014
The Hidden Markov Model (HMM) has been widely used in regime classification and turning point detection for econometric series after the decisive paper by Hamilton (1989). The present paper will show that when using HMM to detect the turning point in cyclical series, the accuracy of the...
Persistent link: https://www.econbiz.de/10013056423