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Dynamic Autoregressive Liquidity (DArLiQ)

Accepted version
Peer-reviewed

Type

Article

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Abstract

We introduce a new class of semiparametric dynamic autoregressive models for the Amihud illiquidity measure, which captures both the long-run trend in the illiquidity series with a nonparametric component and the short-run dynamics with an autoregressive component. We develop a generalized method of moments (GMM) estimator based on conditional moment restrictions and an efficient semiparametric maximum likelihood (ML) estimator based on an iid assumption. We derive large sample properties for our estimators. Finally, we demonstrate the model fitting performance and its empirical relevance on an application. We investigate how the different components of the illiquidity process obtained from our model relate to the stock market risk premium using data on the S&P 500 stock market index.

Description

Keywords

Kernel, Nonparametric estimation, Semiparametric model

Journal Title

Journal of Business and Economic Statistics

Conference Name

Journal ISSN

0735-0015
1537-2707

Volume Title

ahead-of-print

Publisher

Informa UK Limited