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Jump variation estimation with noisy high frequency financial data via wavelets

Zhang, Xin; Kim, Donggyu; Wang, Yazhen - In: Econometrics : open access journal 4 (2016) 3, pp. 1-26

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence … of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component …-step procedure with detection and estimation. In Step 1, we detect the jump locations by performing wavelet transformation on the …

Persistent link: https://www.econbiz.de/10011568279

Nonparametric Estimation and Testing for Instability of Discount Rate and Cash Flow Channels of Stock Returns

Yu, Deshui; Xu, Xiu; Chen, Li; Li, Luyang - 2023

According to the log-linear return approximation, the ability of a predictor to predict future stock returns may arise from its ability to predict either the cash flows or the discount rates, or both. This paper introduces novel nonparametric approaches for estimating and testing the time...

Persistent link: https://www.econbiz.de/10014351244

Volatility Estimation and Forecasts Based on Price Durations

Hong, Seok Young - 2020

duration estimators can be used for the estimation and forecasting of the integrated variance of an underlying semi …

Persistent link: https://www.econbiz.de/10012855793

Inference of Local Regression in the Presence of Nuisance Parameters

Xu, Ke-Li - 2017

Laplace-type plug-in estimation. The former is natural, and the latter does not require optimization and can be …

Persistent link: https://www.econbiz.de/10012953542

Self-Normalization Inference for Linear Trends in Cointegrating Regressions

Cho, Cheol-Keun - 2022

constructed using integrated and modified ordinary least squares (IMOLS, Vogelsang and Wagner (2014)) estimation results, this …

Persistent link: https://www.econbiz.de/10014078083

New Robust Inference for Predictive Regressions

Ibragimov, Rustam; Kim, Jihyun; Skrobotov, Anton - 2021

We propose two robust methods for testing hypotheses on unknown parameters of predictive regression models under heterogeneous and persistent volatility as well as endogenous, persistent and/or fat-tailed regressors and errors. The proposed robust testing approaches are applicable both in the...

Persistent link: https://www.econbiz.de/10013322853

Exact inference in long-horizon predictive quantile regressions with an application to stock returns

Gungor, Sermin; Luger, Richard - In: Journal of financial econometrics 19 (2021) 4, pp. 746-788

Persistent link: https://www.econbiz.de/10012654991

Variable selection and forecasting in high dimensional linear regressions with structural breaks

Chudik, Alexander; Pesaran, M. Hashem; Sharifvaghefi, Mahrad - 2020

This paper is concerned with problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows or exponential down-weighting. However, these studies...

Persistent link: https://www.econbiz.de/10012258549

Stock returns and risk : evidence from quantile

Chiang, Thomas C.; Li, Jiandong - In: Journal of risk and financial management : JRFM 5 (2012) 1, pp. 20-58

This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four major stock indexes in the US market and finds some evidence in favor of a positive relation between the mean of the excess returns and expected risk. However, by using...

Persistent link: https://www.econbiz.de/10011555867

Estimation and inference for varying-coeffcient models with nonstationary regressors using penalized splines

Chen, Haiqiang; Fang, Ying; Li, Yingxing - 2013

This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose … a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel …

Persistent link: https://www.econbiz.de/10009767261