Research article Special Issues

Market Value Volatility and the Volume of Traded Stock for U.S. Industrial Corporations

  • Received: 18 July 2017 Accepted: 27 November 2017 Published: 13 December 2017
  • A novel two-phase econometric approach was used to first obtain the variance (volatility) of the firm's market value adjusted for its common stock repurchases and other determinants (the traditional approach). Then, the variance of some 1,077 firms was used to predict the volume of the firm's common stock traded over a given period of time (the novel approach). The hypothesis was that fast traders in the stock market can use the variance of the firm's market value as a source of risk information, when deciding on what stock to purchase. An unbalanced panel of firms covering the quarterly time periods from 1999 (4) to 2017 (1) was analyzed by the longitudinal method to obtain the variances. Then, linear regression was used to relate the volume of stock traded to the variances. The novel method goes beyond the traditional volatility approach. The statistical results were acceptable for both phases, but with some concern over the use of the variance as an independent determinant in the second phase analysis.

    Citation: James P. Gander. Market Value Volatility and the Volume of Traded Stock for U.S. Industrial Corporations[J]. Quantitative Finance and Economics, 2017, 1(4): 403-410. doi: 10.3934/QFE.2017.4.403

    Related Papers:

  • A novel two-phase econometric approach was used to first obtain the variance (volatility) of the firm's market value adjusted for its common stock repurchases and other determinants (the traditional approach). Then, the variance of some 1,077 firms was used to predict the volume of the firm's common stock traded over a given period of time (the novel approach). The hypothesis was that fast traders in the stock market can use the variance of the firm's market value as a source of risk information, when deciding on what stock to purchase. An unbalanced panel of firms covering the quarterly time periods from 1999 (4) to 2017 (1) was analyzed by the longitudinal method to obtain the variances. Then, linear regression was used to relate the volume of stock traded to the variances. The novel method goes beyond the traditional volatility approach. The statistical results were acceptable for both phases, but with some concern over the use of the variance as an independent determinant in the second phase analysis.


    加载中
    [1] Baker HK, Veit ET, Powell GE (2011) Stock repurchases and false signals. J App Buss Res 19: 33–46.
    [2] Baldauf B, Santoni GJ (1991) Stock price volatility: some evidence from an ARCH model. J Fut Mark 11: 191–200.
    [3] Dann, LY (1981) Common stock repurchases: an analysis of returns to bondholders and stockholders. J Fin Econ 9: 113–138. doi: 10.1016/0304-405X(81)90010-6
    [4] Engle RF, Patton AJ (2001) What good is a volatility model? Quant Fin 1: 237–245.
    [5] Fama EF, French KR (2001) Disappearing dividends: changing firm characteristics or lower propensity to pay? J Fin Econ 60: 3–43.
    [6] Haw In-Mu, Ho SSM, Hu B, et al. (2011) The contribution of stock repurchases to the value of the firm and cash holdings around the world. J Corp Fin 17: 152–166.
    [7] Lewis M (2014) Flash boys: a wall street revolt. New York: Norton.
    [8] Sabri NR (2003) Using treasury "repurchase" shares to stabilize stock markets. Intern J Buss 8: 425–450.
    [9] Tsetsekos GP, Kaufman DJ, Gitman LJ (1991) A survey of stock repurchase 10.motivations and practices of major u.s. corporations. J App Buss Res 7: 15–21.
    [10] Woodruff CG, Torabzadeh KM, Ross JB (1995) Ownership structure returns to defensive stock repurchases. J Econ Fin 19: 171–186. doi: 10.1007/BF02920621
  • Reader Comments
  • © 2017 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3699) PDF downloads(832) Cited by(0)

Article outline

Figures and Tables

Tables(2)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog