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Machine-learning-based semiparametric time series conditional variance : estimation and forecasting

Dang, Justin; Ullah, Aman - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-12

This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares...

Persistent link: https://www.econbiz.de/10012814196

Reconsidering Social Capital : A Latent Class Approach

Owen, Ann L.; Videras, Julio - 2006

Social capital has proven to be a useful concept, but has been ill-defined and not well-measured in the economics literature. We propose a different empirical method for measuring social capital, latent class analysis, based on the idea that social capital is an unobservable multidimensional...

Persistent link: https://www.econbiz.de/10014058732

Determinants of ICT infrastructure : a cross-country statistical analysis

Krüger, Jens; Rhiel, Mathias - 2016

We investigate economic and institutional determinants of ICT infrastructure for a broad cross section ofmore than 100 countries. The ICT variable is constructed from a principal components analysis. The explanatory variables are selected by variants of the Lasso estimator from the machine...

Persistent link: https://www.econbiz.de/10011552991

Double debiased machine learning nonparametric inference with continuous treatments

Colangelo, Kyle; Lee, Ying-Ying - 2019

We propose a nonparametric inference method for causal effects of continuous treatment variables, under unconfoundedness and in the presence of high-dimensional or nonparametric nuisance parameters. Our simple kernel-based double debiased machine learning (DML) estimators for the average...

Persistent link: https://www.econbiz.de/10012111514

Double debiased machine learning nonparametric inference with continuous treatments

Colangelo, Kyle; Lee, Ying-Ying - 2019

Persistent link: https://www.econbiz.de/10012137890

Stripping the discount curve : a robust machine learning approach

Filipović, Damir; Pelger, Markus; Ye, Ye - 2022

We introduce a robust, flexible and easy-to-implement method for estimating the yield curve from Treasury securities. This method is non-parametric and optimally learns basis functions in reproducing Hilbert spaces with an economically motivated smoothness reward. We provide a closed-form...

Persistent link: https://www.econbiz.de/10013169176

Honest Confidence Sets in Nonparametric IV Regression and Other Ill-Posed Models

Babii, Andrii - 2020

nonparametric instrumental regression, various functional regressions, and the density deconvolution. We focus on uniform confidence … of resulting sets have uniform validity over a large class of models, i.e., constructed confidence sets are honest. Monte … Carlo experiments illustrate that introduced confidence sets have reasonable width and coverage properties. Using U.S. data …

Persistent link: https://www.econbiz.de/10012854330

Flexible mixture-amount models for business and industry using Gaussian processes

Ruseckaite, Aiste; Fok, Dennis; Goos, Peter - 2016

Many products and services can be described as mixtures of ingredients whose proportions sum to one. Specialized models have been developed for linking the mixture proportions to outcome variables, such as preference, quality and liking. In many scenarios, only the mixture proportions matter for...

Persistent link: https://www.econbiz.de/10011531150

Permutation tests on returns to scale and common production frontiers in nonparametric models

Rønn-Nielsen, Anders; Kronborg, Dorte; Asmild, Mette - 2022

Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions,...

Persistent link: https://www.econbiz.de/10013338075

Shortcomings of a parametric VaR approach and nonparametric improvements based on a non-stationary return series model

Gürtler, Marc; Rauh, Ronald - 2009 - This Version: 2009-09-09

A non-stationary regression model for financial returns is examined theoretically in this paper. Volatility dynamics are modelled both exogenously and deterministic, captured by a nonparametric curve estimation on equidistant centered returns. We prove consistency and asymptotic normality of a...

Persistent link: https://www.econbiz.de/10009487233