2020 (17), №1

The Speculative Nature of Public Companies Capitalization Factors

For citation: 

Busygin, E. G. (2020). The Speculative Nature of Public Companies Capitalization Factors. Zhurnal Economicheskoj Teorii [Russian Journal of Economic Theory], 17 (1), 144-155

Abstract:

To date, many concepts have been developed, within which researchers are trying to consider the investors decision making process in the face of uncertainty. Nevertheless, it is worth noting that work in this direction is based on one simple condition that characterizes behavioral finance as a direction — the absence of a rational beginning in decisions made by investors, which is further explained in terms of psychological characteristics of individuals, the presence of errors in analysis information, etc.
In this paper, author tried to make an attempt to draw a bridge between the theory of efficient markets and behavioral finance. It should be taken into account that investors, when making decisions, rely primarily on the capitalization of companies. In other words, the emphasis shifts from the personification of investors as subjects to their perception of certain events that they can interpret both rationally and irrationally.
The study assumes that the investor’s rationality and irrationality do not refer to the investor as a subject, but to the analysis of incoming information flows. The rationality is set by default in the framework of the efficient markets theory. The irrationality is the root of the behavioral finance concepts. An investor can rationally evaluate some factors, while irrationally analyzing the influence of other factors.
The paper presents data on for 8 of the largest public vertically integrated companies (BP, Chevron, ExxonMobil, Royal Dutch Shell, Total, Equinor, OMV, Imperial Oil) for the period from Q1 2006 to Q4 2017, and two dependent variables are also taken: capitalization and ROWA for the regression analysis.
The goal of the work was achieved: within the framework of the work, it was possible to identify non-speculative factors: the level of oil production by OPEC countries, the world uncertainty index, return on sales in the upstream segment and return on equity. In other words, information could be divided into groups from the point of view of rational perception by investors.
The findings of the work should be used by private investors, financial analysts and other stock market participants to optimize investment decision-making models.

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Evgeniy Georgievich Busygin — Postgraduate, Higher School of Economics (Moscow, Russian Federation; e-mail: egbusygin@edu.hse.ru).

Goretskaya, V. A. (2014). Povedencheskie finansy: primenenie teorii perspektiv v upravlenii finansami [Behavioral finance: application of the theory of prospects in financial management]. Finansy i kredit [Finance and Credit], 4 (580), 28–35. (In Russ.)

Evstigneev, V. R. (2014). Kak uchastniki valyutnogo rynka stroyat sub’ektivnuyu kartinu budushchego [How participants in the foreign exchange market build a subjective picture of the future]. Voprosy ekonomiki [Issues of Economics], 5, 66–83. (In Russ.)

Evstigneev, V. R. (2014). Modelirovanie investitsionnykh ozhidaniy na valyutnom rynke na osnove raspredeleniya s funktsional’nym parametrom [Modeling of investment expectations in the foreign exchange market based on distribution with a functional parameter]. Nauchno-issledovatel’skiy finansovyy institut. Finansovyy zhurnal [Research Financial Institute. Financial magazine], 1, 25–34. (In Russ.)

Kovalenko, E. A. (2012). Teoriya povedencheskikh finansov i ee primenenie k prognozirovaniyu dokhodnosti finansovykh aktivov [The theory of behavioral finance and its application to forecasting the return on financial assets]. Inform. sistemy i mat. metody v ekonomike [Inform. Systems and mat. Methods in economics], 5. (In Russ.)

Morgunov, A.V. (2016). Modelirovanie veroyatnosti defolta investitsionnykh proektov [Modeling the probability of default of investment projects]. Korporativnye finansy [Corporate Finance], 1 (37), 23–45. (In Russ.)

Redkin, N. M. (2019). Optimizatsiya investitsionnogo portfelya na rossiĭskom fondovom rynke v kontekste povedencheskoĭ teorii [Optimization of the investment portfolio in the Russian stock market in the context of behavioral theory]. Finansy: teoriya i praktika [Finance: Theory and Practice], 23 (4), 99–116. (In Russ.)

Barber, B. M., Heath, C., & Odean, T. (2003). Good reasons sell: Reason-based choice among group and individual investors in the stock market. Management Science, 49 (12), 1636–1652.

Bernheim, B. D., DellaVigna, S., & Laibson, D. (2019). Handbook of Behavioral Economics-Foundations and Applications 2, Elsevier, 503.

Burnstein, E., & Vinokur, A. (1977). Persuasive argumentation and social comparison as determinants of attitude polarization. Journal of experimental social psychology, 13 (4), 315–332.

Chang, C. L., McAleer, M., & Tansuchat, R. (2009). Volatility spillovers between returns on crude oil futures and oil company stocks, available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1406983.

Diaz, E. M., & de Gracia, F. P. (2017). Oil price shocks and stock returns of oil and gas corporations. Finance Research Letters, 20, 75–80.

Ewing, B. T., & Thompson, M. A. (2016).The role of reserves and production in the market capitalization of oil and gas companies. Energy Policy, 98, 576–581.

Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417.

Gabaix, X., & Laibson, D. (2018). Shrouded attributes, consumer myopia and information suppression in competitive markets. Handbook of Behavioral Industrial Organization. Edward Elgar Publishing.

Hartley, P. R., & Medlock, III K. B. (2013). Changes in the operational efficiency of national oil companies. The Energy Journal, 27–57.

Hirshleifer, D. (2015). Behavioral finance. Annual Review of Financial Economics, 7, 133–159.

Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. The stata journal, 7 (3), 281–312.

Howard, A. W., & Harp, Jr A. B. (2009). Oil and gas company valuations. Business Valuation Review, 28 (1), 30–35.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–292.

Kaiser, M. J. (2013). Oil and Gas Company Production, Reserves, and Valuation. Journal of Sustainable Energy Engineering, 1 (3), 220–235.

Kang, W., de Gracia, F. P., & Ratti, R. A. (2017.). Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations. Journal of International Money and Finance, 70, 344–359.

Koller, T. et al. (2010). Valuation: measuring and managing the value of companies. Wiley, 820.

Kumar, Bhaskaran R., & K. Sukumaran, S. (2016). An empirical study on the valuation of oil companies. OPEC Energy Review, 40 (1), 91–108.

Lakonishok, J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. The journal of finance, 49, (5), 1541–1578.

Lanza, A. et al. (2005). Long-run models of oil stock prices. Environmental Modelling & Software, 20, (11), 1423–1430.

Lerner, J. S., & Tetlock, P. E. (1999). Accounting for the effects of accountability. Psychological bulletin, 125 (2).

MacDiarmid, J., Tholana, T., & Musingwini, C. (2018). Analysis of key value drivers for major mining companies for the period 2006–2015. Resources Policy, 56, 16–30.

Osmundsen, P. et al. (2006). Valuation of international oil companies. The Energy Journal, 27, 49–64.

Samuelson, P. A. et al. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6(2), 41–49.

Sanusi, M. S., & Ahmad, F. (2016). Modelling oil and gas stock returns using multi factor asset pricing model including oil price exposure. Finance research letters, 18, 89–99.

Shafir, E., Simonson, I., & Tversky, A. (1993). Reason-based choice. Cognition, 49 (1–2), 11–36. Shleifer, A. (2000). Inefficient markets: An introduction to behavioral finance. OUP Oxford, 216.

Tetlock, P. E. (1992). The impact of accountability on judgment and choice: Toward a social contingency model. Advances in experimental social psychology. Academic Press, 25, 331–376.