Tests for Abnormal Returns in the Presence of an Event-Induced Increase in the Cross Sectional Correlation

Niklas Ahlgren; Jan Antell

Tests for Abnormal Returns in the Presence of an Event-Induced Increase in the Cross Sectional Correlation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific

Abstract

Standard tests for abnormal returns are invalid if the abnormal returns are cross sectionally correlated. We model the cross sectional correlation in the abnormal returns by a spatial autoregressive (SAR) model. The SAR model estimates the cross sectional correlation in the abnormal returns from the event day, or event period. Tests which are robust to an event-induced increase in the volatility and cross sectional correlation of the abnormal returns are proposed. Empirical applications to US stock returns around Bear Stearns' collapse and Lehman Brothers' bankruptcy in 2008 are provided as illustrations.

Original language	English
Title of host publication	68th European Meeting of the Econometric Society
Number of pages	38
Publisher	EEA-ESEM - European Economic Association & Econometric Society
Publication date	25.08.2014
Publication status	Published - 25.08.2014
MoE publication type	B3 Article in conference proceedings
Event	68th European Meeting of the Econometric Society (ESEM) - Toulouse, Toulouse, France Duration: 25.08.2014 → 29.08.2014 Conference number: 68

Keywords

511 Economics
Abnormal return
Cross sectional correlation
Event study
Spatial autoregressive model
KOTA2014

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title = "Tests for Abnormal Returns in the Presence of an Event-Induced Increase in the Cross Sectional Correlation",

abstract = "Standard tests for abnormal returns are invalid if the abnormal returns are cross sectionally correlated. We model the cross sectional correlation in the abnormal returns by a spatial autoregressive (SAR) model. The SAR model estimates the cross sectional correlation in the abnormal returns from the event day, or event period. Tests which are robust to an event-induced increase in the volatility and cross sectional correlation of the abnormal returns are proposed. Empirical applications to US stock returns around Bear Stearns' collapse and Lehman Brothers' bankruptcy in 2008 are provided as illustrations. ",

keywords = "511 Economics, Abnormal return, Cross sectional correlation, Event study, Spatial autoregressive model, KOTA2014",

author = "Niklas Ahlgren and Jan Antell",

note = " Volume: Proceeding volume: ; 68th European Meeting of the Econometric Society (ESEM) , ESEM ; Conference date: 25-08-2014 Through 29-08-2014",

year = "2014",

month = aug,

day = "25",

language = "English",

booktitle = "68th European Meeting of the Econometric Society",

publisher = "EEA-ESEM - European Economic Association & Econometric Society",

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Ahlgren, N & Antell, J 2014, Tests for Abnormal Returns in the Presence of an Event-Induced Increase in the Cross Sectional Correlation. in 68th European Meeting of the Econometric Society. EEA-ESEM - European Economic Association & Econometric Society, 68th European Meeting of the Econometric Society (ESEM) , Toulouse, France, 25.08.2014. <http://www.eea-esem.com/EEA-ESEM/2014/prog/viewpaper.asp?pid=2231>

TY - GEN

T1 - Tests for Abnormal Returns in the Presence of an Event-Induced Increase in the Cross Sectional Correlation

AU - Ahlgren, Niklas

AU - Antell, Jan

N1 - Conference code: 68

PY - 2014/8/25

Y1 - 2014/8/25

N2 - Standard tests for abnormal returns are invalid if the abnormal returns are cross sectionally correlated. We model the cross sectional correlation in the abnormal returns by a spatial autoregressive (SAR) model. The SAR model estimates the cross sectional correlation in the abnormal returns from the event day, or event period. Tests which are robust to an event-induced increase in the volatility and cross sectional correlation of the abnormal returns are proposed. Empirical applications to US stock returns around Bear Stearns' collapse and Lehman Brothers' bankruptcy in 2008 are provided as illustrations.

AB - Standard tests for abnormal returns are invalid if the abnormal returns are cross sectionally correlated. We model the cross sectional correlation in the abnormal returns by a spatial autoregressive (SAR) model. The SAR model estimates the cross sectional correlation in the abnormal returns from the event day, or event period. Tests which are robust to an event-induced increase in the volatility and cross sectional correlation of the abnormal returns are proposed. Empirical applications to US stock returns around Bear Stearns' collapse and Lehman Brothers' bankruptcy in 2008 are provided as illustrations.

KW - 511 Economics

KW - Abnormal return

KW - Cross sectional correlation

KW - Event study

KW - Spatial autoregressive model

KW - KOTA2014

M3 - Conference contribution

BT - 68th European Meeting of the Econometric Society

PB - EEA-ESEM - European Economic Association & Econometric Society

T2 - 68th European Meeting of the Econometric Society (ESEM)

Y2 - 25 August 2014 through 29 August 2014

ER -

Tests for Abnormal Returns in the Presence of an Event-Induced Increase in the Cross Sectional Correlation

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Keywords

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