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Volatility Flocking by Cucker–Smale Mechanism in Financial Markets

Author

Listed:
  • Hyeong-Ohk Bae

    (Ajou University)

  • Seung-Yeal Ha

    (Seoul National University)

  • Yongsik Kim

    (Korea Asset Pricing)

  • Hyuncheul Lim

    (Chonnam National University)

  • Jane Yoo

    (Ajou University)

Abstract

We analyze empirical evidence of flocking stock volatilities according to the Cucker–Smale (C–S) mechanism. By using daily realized volatilities of stocks listed on Dow Jones Industrial Average from January, 2007 to December, 2009, we calibrate key parameters such as time-varying coupling strength, communication weight and stochastic noise in coupling of a benchmark C–S model in Bae et al. (Math Models Methods Appl Sci 25:1299–1335, 2015). Our numerical solutions show that the flocking mechanism explains average volatility dynamics better than a stochastic volatility model without the mechanism over the sample period. The model’s empirical implications are found from cyclicality of Volatility Flocking Index (VFI), an aggregate measure of differences between volatilities. Results from Granger causality tests after vector autoregression estimation show that VFI helps us predict the implied volatility index, and weighted average return of S&P500 Index.

Suggested Citation

  • Hyeong-Ohk Bae & Seung-Yeal Ha & Yongsik Kim & Hyuncheul Lim & Jane Yoo, 2020. "Volatility Flocking by Cucker–Smale Mechanism in Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(3), pages 387-414, September.
  • Handle: RePEc:kap:apfinm:v:27:y:2020:i:3:d:10.1007_s10690-019-09299-9
    DOI: 10.1007/s10690-019-09299-9
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    More about this item

    Keywords

    Cucker–Smale model; Communication weight; Flocking; Ridge regression; Volatility-Flocking Index (VFI);
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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