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Monday, May 18, 2020 | History

2 edition of dynamic structural model for stock return volatility and trading volume found in the catalog.

dynamic structural model for stock return volatility and trading volume

William A. Brock

dynamic structural model for stock return volatility and trading volume

by William A. Brock

  • 201 Want to read
  • 11 Currently reading

Published by National Bureau of Economic Research in Cambridge, MA .
Written in English

    Subjects:
  • Stocks -- Econometric models.,
  • Stochastic processes.,
  • Time-series analysis.

  • Edition Notes

    StatementWilliam A. Brock, Blake D. LeBaron.
    SeriesNBER working paper series -- working paper no. 4988, Working paper series (National Bureau of Economic Research) -- working paper no. 4988.
    ContributionsLeBaron, Blake Dean, 1961-, National Bureau of Economic Research.
    The Physical Object
    Pagination46 p. :
    Number of Pages46
    ID Numbers
    Open LibraryOL22420439M

    effects, especially in terms of long-horizon forecasting of stock return volatility. Keywords: Stock return volatility, structural breaks, in-sample tests, out-of-sample tests, GARCH . The relationship between returns and trading volume has interested financial economists and analysts for a number of years. In general, previous empirical studies have noted strong positive correlations between trading volume and price volatility/ absolute returns File Size: KB.

    First, to measure the dynamic relationship between price volatility, trading volume and market depth. For such measurement and analysis daily settlement prices, trading volume and open interest series were used by adopting the base model . Modelling stock return volatility dynamics in selected African markets Daniel King and Ferdi Botha ERSA working paper a reliable statistical model of stock return 1An alternative way of accounting for structural .

      Scaling and criticality in a stochastic multi-agent model of a financial market structural model for stock return volatility and trading volume. Rev. in a stochastic multi-agent model Cited by: An Empirical Investigation of the Relationship between Stock Return and Trading Volume: Evidence from the Jordanian Banking Sector Mohamed Khaled Al-Jafari1 and Ahmad Tliti2 Abstract This study investigates the dynamic relationship between stock return and trading volume in the banking sector of Amman Stock .


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Dynamic structural model for stock return volatility and trading volume by William A. Brock Download PDF EPUB FB2

Why Volatility is Important For Investors. A DYNAMIC STRUCTURAL MODEL FOR STOCK RETURN VOLATILITY AND TRADING VOLUME William A.

Brock and Blake D. LeBaron* Abstract-This paper presents an adaptive beliefs model which is able to roughly reproduce the following features seen in the data: (i) The autocorrelation functions of the volatility of returns and trading volume.

This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process itself. Returns and volume data argue, in the context of our model, that persistent volatility is caused by traders Cited by:   This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process itself.

A Dynamic Structural Model for Stock Return Volatility and Trading Volume Cited by: We examine the dynamic relation between returns, volume, and volatility of stock indexes. The data come from nine national markets and cover the period from to The results show.

The dynamic models show a directional causality between trading volume, change in trading volume and returns on ASE index from trading volume and change in trading volume to returns. show nonlinear dynamics exist between stock returns and trading volume in the stock market. Moreover, trading volume plays an important role for the cyclical movements in the stock market.

Key words: Nonlinear dynamics, Cyclical behavior, Stock market returns, Trading volume, STAR models JEL Classification. returns and trading volume. In the model [24] the stock market is composed of the two typical groups of traders: the fundamentalists who believe that the stock price will be equal to the Author: Taisei Kaizoji.

In our work, we take a dynamic, model-based perspective and assume that at time twe observe the vector (r t;x t;Z t) where: r tis a p-dimensional vector of stock returns; Z tis a p kmatrix of rm speci c information; and x tis the market return (or some equivalent measure). We represent Index Models as de ned by the dynamic factor model.

stock market implied volatility and policy uncertainty based on a newly introduced uncertainty index by Baker et al. We nd that the dynamic correlations of policy uncertainty and stock market returns. (ii) The autocorrelation function of a measure of trading activity such as volume or turnover is positive with a slowly decaying tail.

(iii) The cross correlation function of a measure of volatility such as squared returns is about zero for squared returns with past and future volumes and is positive for squared returns with current : William A. Brock and Blake D.

LeBaron. Carnegie Mellon University, Pittsburgh, PAUSA Abstract This paper uses dynamic impulse response analysis to investigate the interrelationships among stock price volatility, trading volume Cited by: Stock Market Volatility Dynamics: a Volume Filtered-GARCH Model Abstract We present a two-factor volatility model to study the impact of news arrival and trading volume on stock returns variance.

The model can explicitly account for the association between volatility and volume Author: Maxime Bonelli.

A Dynamic Structural Model for Stock Return Volatility and Trading Volume This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process.

We would like to show you a description here but the site won’t allow more. The dynamic relationship between trading volume, return and volatility of CNX Nifty Index Future in result shows that the relationship between trading volume and return irrespetive of.

mational reasons. I use the model to study the behavior of stock trading volume and its relation with returns. It is shown that different heterogeneity among investors gives rise to different volume behavior and return-volume dynamics.

This implies that trading volume. Abstract: This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the Cited by: The relationship among trading volume, prices, returns, etc., A dynamic structural model for stock return volatility and trading volume.

The Review of Economics and Statistics – Time series properties of an artificial stock market. Journal of Economic Dynamics Author: José Antonio Pascual, Javier Pajares.

This paper examines the causal and dynamic relationships among stock returns, return volatility and trading volume for five emerging markets in South-East Asia—Indonesia, Cited by:. dynamical models come from the technical trading rules. Another central concept in modern finance is volatility the standard deviation of the returns.

The importance of volatility stems from two facts: (i) compared with the wilderness of returns, the volatility Cited by: Using the dynamic conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) model, we empirically examine the dynamic relationship Cited by: 8.Get this from a library!

A dynamic structural model for stock return volatility and trading volume. [William A Brock; Blake Dean LeBaron; National Bureau of Economic Research.].