Stock Return, Volume and Volatility in the EGARCH model

Yi Jiang

doi:10.23842/jif.2020.31.1.004

Stock Return, Volume and Volatility in the EGARCH model

Journal of Insurance and Finance
2020, 31(1), pp.115-136
DOI : 10.23842/jif.2020.31.1.004
Publisher : Korea Insurance Research Institute
Research Area : Social Science > Business Management
Received : November 29, 2019
Accepted : February 21, 2020
Published : February 29, 2020

Yi Jiang ¹

¹California State University

Accredited

ABSTRACT

I use EGARCH model to study the asymmetric impact of negative and positive shocks on stock return volatility. I find the asymmetric effects exist and the impact on volatility of a negative shock is greater than that of a positive shock. Furthermore, I examine the dynamic relationship between returns, volume and volatility of stock index by introducing trading volume as an exogenous variable into the EGARCH model. The results indicate that trading volume contributes some information to the returns processes of stock indexes. However, the persistence of volatility remains even after incorporating lagged volume effects, which are proxies for information flow. Granger causality tests demonstrate stronger evidence of returns causing volume than volume causing returns.

KEYWORDS

EGARCH models, Volatility Persistence, Trading volume, Information flow

Citation status

* References for papers published after 2023 are currently being built.

[book] Black, F. / 1976 / Business and Economics Statistics Section : 177~181

[journal] Chiang, T. / 2010 / New evidence on the relation between return volatility and trading volume / Journal of Forecasting 29 : 502~515

[journal] Chou, Ray Y. / 1988 / Volatility Persistence and Stock Valuations: Some Empirical Evidence Using GARCH / Journal of Applied Econometrics 3 : 279~294

[journal] Day, T. / 1992 / Stock market volatility and the information content of stock index options / Journal of Econometrics 52 : 267~287

[journal] Dickey, D. / 1979 / Distribution of the Estimators for Autoregressive Time Series with a Unit Root / Journal of American Statistical Association 74 : 427~431

[journal] Gallant, A. / 1992 / Stock prices and volume / Review of Financial Studies 5 : 199~242

[journal] Glosten, L. / 1993 / On the relation between the expected value and the volatility of the nominal excess return on stocks / Journal of Finance 48 : 1779~1801

[journal] Granger, C. / 1969 / Investigating causal relations by econometric models and cross-spectral methods / Econometrica 37 : 424~438

[journal] Harris, L. / 1986 / Cross-security tests of the mixture of distributions hypothesis / Journal of Financial and Quantitative Analysis 21 : 39~46

[journal] Karpoff, J. / 1987 / The Relation Between Price Changes and Trading Volume : A Survey / Journal of Financial and Quantitative Analysis 22 : 109~126

[journal] Lamoureux, C. / 1994 / Endogenous trading volume and momentum in stock-return volatility / Journal of Business and Economic Statistics 12 : 253~260

[journal] Phillips, P. / 1988 / Testing for a Unit Root in Time Series Regression / Biometrika 75 : 335~346

[other] Standard and Poor’s Corporation / 1988 / Standard and Poor’s Statistical Service: Security Price Index Record

[journal] Tauchen, G. / 1983 / The Price Variability-Volume Relationship on Speculative Markets / Econometrica 51 : 485~505

KJCKorea
Journal Central

Journal of Insurance and Finance 2023 KCI Impact Factor : 0.59

Stock Return, Volume and Volatility in the EGARCH model

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of Insurance and Finance 2023 KCI Impact Factor : 0.59

Stock Return, Volume and Volatility in the EGARCH model

ABSTRACT

KEYWORDS

Statistics

Tools

Issue List

Citation status

KCI Citation Counts (0)

REFERENCES (14) * References for papers published after 2023 are currently being built.

Search PDF

Citation

* References for papers published after 2023 are currently being built.