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Information Flow Interpretation of Heteroskedasticity for Capital Asset Pricing: An Expectation-based View of Risk

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  • Senarathne, Chamil W
  • Jayasinghe, Prabhath

Abstract

The Heteroskedastic Mixture Model (HMM) of Lamoureux, and Lastrapes (1990) is extended, relaxing the restriction imposed on the mean i.e. μt-1=0 . Instead, an exogenous variable rm, along with its vector βm, that predicts return rt is introduced to examine the hypothesis that the volume is a measure of speed of evolution in the price change process in capital asset pricing. The empirical findings are documented for the hypothesis that ARCH is a manifestation of time dependence in the rate of information arrival, in line with the observations of Lamoureux, and Lastrapes (1990). The linkage between this time dependence and the expectations of market participants is investigated and the symmetric behavioural response is documented. Accordingly, the tendency of revision of expectation in the presence of new information flow whose frequency as measured by ‘volume clock’ is observed. In the absence of new information arrival at the market, investors tend to follow the market on average. When new information is available, the expectations of investors are revised in the same direction as a symmetric response to the flow of new information arrival at the market.

Suggested Citation

  • Senarathne, Chamil W & Jayasinghe, Prabhath, 2017. "Information Flow Interpretation of Heteroskedasticity for Capital Asset Pricing: An Expectation-based View of Risk," MPRA Paper 78771, University Library of Munich, Germany, revised 04 Apr 2017.
  • Handle: RePEc:pra:mprapa:78771
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    References listed on IDEAS

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    Cited by:

    1. Chamil W SENARATHNE & Wei JIANGUO, 2020. "Testing for Heteroskedastic Mixture of Ordinary Least Squares Errors," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 73-91, July.
    2. SENARATHNE W Chamil & JIANGUO Wei, 2018. "Do Investors Mimic Trading Strategies Of Foreign Investors Or The Market: Implications For Capital Asset Pricing," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 13(3), pages 171-205, December.
    3. Senarathne Chamil W. & Šoja Tijana, 2019. "Heteroskedasticity in Excess Bitcoin Return Data: Google Trend vs. Garch Effects," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(3), pages 35-45, September.
    4. Senarathne Chamil W. & Long Wei, 2019. "Industry Competition and Common Stock Returns," Management Sciences. Nauki o Zarządzaniu, Sciendo, vol. 24(3), pages 24-35, September.
    5. Senarathne, Chamil W., . "The Information Flow Interpretation of Margin Debt Value Data: Evidence from New York Stock Exchange," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 26(1).
    6. Senarathne Chamil W., 2018. "The Impact of Corporate Cultural Behaviour on Common Stock Return: Some Implications for Corporate Governance," Management of Organizations: Systematic Research, Sciendo, vol. 80(1), pages 115-130, December.
    7. Senarathne Chamil W., 2019. "Possible Impact of Facebook’s Libra on Volatility of Bitcoin: Evidence from Initial Coin Offer Funding Data," Management of Organizations: Systematic Research, Sciendo, vol. 81(1), pages 87-100, June.

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    More about this item

    Keywords

    Mixture of Distribution Hypothesis; Information Flow; Stock Volume; Systematic Risk; Capital Asset Pricing; ARCH; GARCH;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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