On Tree-Structured Linear and Quantile Regression Based Asset Pricing

51 Pages Posted: 12 Jun 2020

See all articles by John Galakis

John Galakis

ABN AMRO, The Netherlands

Ioannis D. Vrontos

Athens University of Economics and Business

Panos Xidonas

ESSCA École de Management

Date Written: July 1, 2019

Abstract

A tree-structured linear and quantile regression framework is proposed for the analysis and modeling of equity market returns. The approach is based on the idea of a binary tree, where every terminal node parameterizes a local regression model for a specific partition of the data. A Bayesian stochastic method is developed including model selection and estimation of the tree structure parameters. The modeling framework is applied on numerous asset pricing models related to the whole U.S. equity market, using alternative mimicking factor portfolios, frequency of data and widely followed market indices. The findings reveal strong evidence that asset returns exhibit asymmetric effects and nonlinear patterns to different common factors.

Keywords: Asset pricing; Bayesian inference; Markov chain Monte Carlo; Nonlinear dynamics; Tree-structured (linear and quantile) regression models

JEL Classification: G11, G12, C1, C11

Suggested Citation

Galakis, John and Vrontos, Ioannis D. and Xidonas, Panos, On Tree-Structured Linear and Quantile Regression Based Asset Pricing (July 1, 2019). Available at SSRN: https://ssrn.com/abstract=3605008 or http://dx.doi.org/10.2139/ssrn.3605008

John Galakis

ABN AMRO, The Netherlands ( email )

NL-1000 EA Amsterdam
Netherlands

Ioannis D. Vrontos (Contact Author)

Athens University of Economics and Business ( email )

76 Patission Street
Athens, 104 34
Greece

Panos Xidonas

ESSCA École de Management ( email )

55 quai Alphonse Le Gallo
Paris, 92513
France

HOME PAGE: http://xidonas.blogspot.com

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