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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 of volatility in finance for portfolio allocation,...
Persistent link: https://www.econbiz.de/10011568279
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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
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Optimal Threshold Selection for Realized Volatility Forecasts in the Presence of Jumps
Sun, Yixiao; Fissel, Benjamin - 2010
When estimating and forecasting realized volatility in the presence of jumps, a form of bias-variance tradeoff is present in the selection of the truncation threshold. We propose an optimal method for threshold selection that minimizes the out-of-sample forecasting loss. The use of a forecasting...
Persistent link: https://www.econbiz.de/10014188741
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Scale-, time- and asset-dependence of Hawkes process estimates on high frequency price changes
Wehrli, Alexander; Wheatley, Spencer; Sornette, Didier - 2020
The statistical estimate of the branching ratio η of the Hawkes model, when fitted to windows of mid-price changes, has been reported to approach criticality (η = 1) as the fitting window becomes large. In this study -- using price changes from the EUR/USD currency pair traded on the...
Persistent link: https://www.econbiz.de/10012219363
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A simple test for causality in volatility
Chang, Chia-Lin; McAleer, Michael - 2016
An early development in testing for causality (technically, Granger non-causality) in the conditional variance (or … volatility) associated with financial returns, was the portmanteau statistic for non-causality in variance of Cheng and Ng (1996 …). A subsequent development was the Lagrange Multiplier (LM) test of non-causality in the conditional variance by Hafner …
Persistent link: https://www.econbiz.de/10011556246
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A simple test for causality in volatility
Chang, Chia-ling; McAleer, Michael - In: Econometrics : open access journal 5 (2017) 1, pp. 1-5
An early development in testing for causality (technically, Granger non-causality) in the conditional variance (or … volatility) associated with financial returns was the portmanteau statistic for non-causality in the variance of Cheng and Ng … (1996). A subsequent development was the Lagrange Multiplier (LM) test of non-causality in the conditional variance by …
Persistent link: https://www.econbiz.de/10011654183
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Transformed Polynomials for Nonlinear Autoregressive Models of the Conditional Mean
Blasques, Francisco - 2012
This paper proposes a new set of transformed polynomial functions that provide a flexible setting for nonlinear autoregressive modeling of the conditional mean while at the same time ensuring the strict stationarity, ergodicity, fading memory and existence of moments of the implied stochastic...
Persistent link: https://www.econbiz.de/10013097030
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Modeling Dynamic Heterogeneity using Gaussian Processes
Dew, Ryan - 2019
Marketing research relies on individual-level estimates to understand the rich heterogeneity that exists in consumers, firms, and products. While much of the literature focuses on capturing static cross-sectional heterogeneity, little research has been done on modeling dynamic heterogeneity, or...
Persistent link: https://www.econbiz.de/10012902314
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Modelling Stochastic Volatility with Leverage and Jumps : A Simulated Maximum Likelihood Approach via Particle Filtering
Malik, Sheheryar; Pitt, Michael K. - 2011
In this paper we provide a unified methodology for conducting likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...
Persistent link: https://www.econbiz.de/10014185810
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Nonparametric Estimation and Parametric Calibration of Time-Varying Coefficient Realized Volatility Models
Chen, Xiangjin Bruce - 2013
This paper introduces a new specification for the heterogeneous autoregressive (HAR) model for the realized volatility of S&P500 index returns. In this new model, the coefficients of the HAR are allowed to be time-varying with unknown functional forms. We propose a local linear method for...
Persistent link: https://www.econbiz.de/10013076694