The Bayesian Method in Estimating Polish and German Industry Betas. A Comparative Analysis of the Risk between the Main Economic Sectors from 2001–2020

Authors

DOI:

https://doi.org/10.18778/1508-2008.25.12

Keywords:

industry beta, CAPM, Markov Chain Monte Carlo, Polish Stock Market, German Stock Market

Abstract

This paper examines the long‑term dependence between the Polish and German stock markets in terms of industry beta risk estimates according to the Capital Asset Pricing Model (CAPM). The main objective of this research is to compare the Polish and German beta parameters of five Polish and three German sector indices using the Bayesian methodology in the period 2001–2020. The study has two detailed aims. First, to develop a modified, Bayesian approach (SBETA model) that generates significantly more precise beta than the traditional model. Second, to compare the results of different time‑varying industry betas in the Polish and German economies, giving a simple investment recommendation, i.e., which sector could be classified as aggressive or defensive.

The betas were time‑varying in both markets but less persistent in the German industries, which seems characteristic of an advanced economy. The Banking sector betas were the highest in both markets, implying the aggressive nature of that industry in the last twenty years. For the Polish market industry, the betas of Construction, IT, Food and Drinks, and Telecom were classified as defensive. For the German economy, the Technologies (IT) sector was also classified as aggressive, but Telecom was defensive. The results give a valuable insight into the systematic risk levels in Poland and Germany, reflecting the investors' learning process and indicating that Polish Banking and German technologies outperformed the market in the last twenty years.

Downloads

Download data is not yet available.

References

Berk, J.B., Green, R.C., Naik, V. (1999), Optimal investment, growth options, and security returns, “The Journal of Finance”, 54 (5), pp. 1553–1607, https://doi.org/10.11​11/0022-1082.00161
Google Scholar DOI: https://doi.org/10.1111/0022-1082.00161

Będowska‑Sójka, B. (2017), Evaluating the Accuracy of Time‑varying Beta. The Evidence from Poland, “Dynamic Econometric Models”, 17, pp. 161−176.
Google Scholar

Blume, M.E. (1975), Betas and their regression tendencies, “The Journal of Finance”, 30 (3), pp. 785–795, https://doi.org/10.1111/j.1540-6261.1975.tb01850.x
Google Scholar DOI: https://doi.org/10.1111/j.1540-6261.1975.tb01850.x

Cepeda‑Cuervo, E., Jaimes, D., Marín, M., Rojas, J. (2016), Bayesian beta regression with Bayesianbetareg R‑package, Comput Stat 31, pp. 165–187, https://doi.org/10.10​07/s00180-015-0591-9
Google Scholar DOI: https://doi.org/10.1007/s00180-015-0591-9

Chaveau, T., and Maillet, B. (1998), Flexible Least Squares Betas: The French Market Case, Papers 1998–03/fi, Caisse des Depots et Consignations – Cahiers de recherche.
Google Scholar

Das, A., Ghoshal, T. (2010), Market Risk Beta Estimation using Adaptive Kalman Filter, “International Journal of Engineering Science and Technology”, 2 (6), pp. 1923–1934.
Google Scholar

Dębski, W., Feder‑Sempach, E., Świderski, B. (2015), Are beta parameters stable on the Warsaw Stock Exchange, “Kwartalnik Kolegium Ekonomiczno‑społecznego”, Studia i Prace No. 3 tom. 3 (23), pp. 65–74, https://doi.org/10.33119/KKESSiP​.2015.3.3.5
Google Scholar DOI: https://doi.org/10.33119/KKESSiP.2015.3.3.5

Dębski, W., Feder‑Sempach, E., Świderski, B. (2016), Beta stability over bull and bear market on the Warsaw Stock Exchange, “Folia Oeconomica Statinesia”, 16 (1), pp. 75–92. Wydawnictwo Naukowe Uniwersytetu Szczecińskiego, Szczecin. 2016/1. https://doi.org/10.1515/foli-2016-0006
Google Scholar DOI: https://doi.org/10.1515/foli-2016-0006

Dębski, W., Feder‑Sempach, E., Wójcik, S. (2018), Statistical Properties of Rates of Return on Shares Listed on the German, French, and Polish Markets – a Comparative Study, “Contemporary Economics”, 12 (1), pp. 5–16.
Google Scholar

Dębski W., Feder‑Sempach E., Szczepocki, P. (2020), Time‑Varying Beta–The Case Study of the Largest Companies from the Polish, Czech, and Hungarian Stock Exchange, “Emerging Markets Finance and Trade”, 2020, https://doi.org/10.1080/154​0496X.2020.1738188
Google Scholar

Ebner, M., Neumann, T. (2005), Time‑Varying Betas of German Stock Returns, “Financial Markets and Portfolio Management”, 19 (1), pp. 29–46, https://doi.org/10.1007​/s11408-005-2296-5
Google Scholar DOI: https://doi.org/10.1007/s11408-005-2296-5

Elshqirat, M., Sharifzadeh, M. (2018), Testing a multi‑factor capital asset pricing model in the Jordanian Stock Market, “International Business Research”, 11 (9), pp. 13–22. https://doi.org/10.5539/ibr.v11n9p13
Google Scholar DOI: https://doi.org/10.5539/ibr.v11n9p13

Engle, R.F. (2002), Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models, “Journal of Business and Economic Statistics”, 20, pp. 339–350, https://doi.org/10.1198/073500102​288618487
Google Scholar DOI: https://doi.org/10.1198/073500102288618487

Engle, R.F., Kroner, K.F. (1995), Multivariate Simultaneous Generalized Arch, “Econometric Theory”, 11 (1), https://doi.org/10.1017/S0266466600009063
Google Scholar DOI: https://doi.org/10.1017/S0266466600009063

Fabozzi, F.J., Francis, J.C. (1978), Betas as a random coefficient, “Journal of Financial and Quantitative Analysis”, 13, pp. 101–115, https://doi.org/10.2307/2330525
Google Scholar DOI: https://doi.org/10.2307/2330525

Faff, R.W., Hillier, D., Hillier, J. (2000), Time varying beta risk: An analysis of alternative modelling techniques, “Journal of Business Finance & Accounting”, 27 (5–6), pp. 523–554, https://doi.org/10.1111/1468-5957.00324
Google Scholar DOI: https://doi.org/10.1111/1468-5957.00324

Fama, E.F., French, K.R., (1993), Common risk factors in the returns on stocks and bonds, “Journal of Financial Economics”, Elsevier, 33 (1), pp. 3–56, https://doi.org/10.1016​/0304-405X(93)90023-5
Google Scholar DOI: https://doi.org/10.1016/0304-405X(93)90023-5

French, J. (2016), Estimating time‑varying beta‑coefficients: An empirical study of US &ASEAN portfolios, “Research in Finance”, 32, pp. 19–34, https://doi.org/10.1108/S0​196-382120160000032002
Google Scholar DOI: https://doi.org/10.1108/S0196-382120160000032002

Gomes, J., Kogan, L., Zhang, L. (2003), Equilibrium cross section of returns, “Journal of Political Economy”, 111 (4), pp. 693–732, https://doi.org/10.1086/375379
Google Scholar DOI: https://doi.org/10.1086/375379

Jostova, G., Philipov, A. (2005), Bayesian analysis of stochastic betas, “Journal of Financial and Quantitative Analysis”, 40 (4), pp. 747–778, https://doi.org/10.1017/S0​022109000001964
Google Scholar DOI: https://doi.org/10.1017/S0022109000001964

Kim, S., Shephard, N., Chib, S. (1998), Stochastic volatility: likelihood inference and comparison with ARCH models, “The Review of Economic Studies”, 65 (3), pp. 361–393, https://doi.org/10.1111/1467-937X.00050
Google Scholar DOI: https://doi.org/10.1111/1467-937X.00050

Kurach, R., Stelmach, J. (2014), Time‑Varying Behavior of Sector Beta Risk – The Case of Poland, “Romanian Journal of Economic Forecasting”, XVII (1), pp. 139–159, https://doi.org/10.2478/cer-2014-0018
Google Scholar DOI: https://doi.org/10.2478/cer-2014-0018

Lewellen, J., Nagel, S. (2006), The Conditional CAPM Does Nol Explain Asset‑Pricing Anomalies, “Journal of Financial Economics”, 82 (2), November 2006, pp. 289–314, https://doi.org/10.1016/j.jfineco.2005.05.012
Google Scholar DOI: https://doi.org/10.1016/j.jfineco.2005.05.012

Lintner, J. (1965), Security Prices, Risk, And Maximal Gains From Diversification, “Journal of Finance”, American Finance Association, 20 (4), pp. 587–615, https://doi.org​/10.1111/j.1540-6261.1965.tb02930.x
Google Scholar DOI: https://doi.org/10.1111/j.1540-6261.1965.tb02930.x

Mergner, S., Bulla, J. (2008), Time‑varying beta risk of Pan‑European industry portfolios: A comparison of alternative modeling techniques, “The European Journal of Finance”, 14 (8) pp. 771–802, https://doi.org/10.1080/13518470802173396
Google Scholar DOI: https://doi.org/10.1080/13518470802173396

Mossin, J. (1966), Equilibrium in a Capital Asset Market, “Econometrica”, 34 (4), pp. 768–783, https://doi.org/10.2307/1910098
Google Scholar DOI: https://doi.org/10.2307/1910098

Petkova, R., Zhang, L. (2005), Is value riskier than growth?, “Journal of Financial Economics”, 78 (1), pp. 187–202, https://doi.org/10.1016/j.jfineco.2004.12.001
Google Scholar DOI: https://doi.org/10.1016/j.jfineco.2004.12.001

Sharpe, W. (1964), Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk, “Journal of Finance”, 19 (3), pp. 425–442, https://doi.org/10.1111/j.15​40-6261.1964.tb02865.x
Google Scholar DOI: https://doi.org/10.1111/j.1540-6261.1964.tb02865.x

Stan Development Team (2020), RStan: the R interface to Stan. R package version 2.21.2, http://mc‑stan.org/
Google Scholar

Le Tan Phuoc, Chinh Duc Pham (2020), The systematic risk estimation models: A different perspective, “Heliyon”, 6 (2), https://doi.org/10.1016/j.heliyon.2020.e03371
Google Scholar DOI: https://doi.org/10.1016/j.heliyon.2020.e03371

Tsuji, C. (2017), An exploration of the time‑varying beta of the international capital asset pricing model: The case of the Japanese and the other Asia‑Pacific Stock Markets, “Accounting and Finance Research”, pp. 86–93, https://doi.org/10.5430/afr.v6n2p86
Google Scholar DOI: https://doi.org/10.5430/afr.v6n2p86

Wells, C. (1994), Variable betas on the Stockholm exchange 1971–1989, “Applied Economics”, 4, pp. 75–92, https://doi.org/10.1080/758522128
Google Scholar DOI: https://doi.org/10.1080/758522128

Wdowiński, P. (2004), Determinants of country beta risk in Poland, CESifo Working Paper Series 1120. CESifo Group Munich, https://papers.ssrn.com/sol3/papers.cfm​?abstract_id=510962 (accessed: 16.04.2018).
Google Scholar

Yao, J., Gao, J. (2004), Computer‑Intensive Time‑Varying Model Approach to the Systematic Risk of Australian Industrial Stock Returns, “Australian Journal of Management”, Australian School of Business, 29 (1), pp. 121–145, https://doi.org/10.11​77/031289620402900113
Google Scholar DOI: https://doi.org/10.1177/031289620402900113

Yu, J. (2005), On leverage in a stochastic volatility model, “Journal of Econometrics”, 127 (2), pp. 165–178, https://doi.org/10.1016/j.jeconom.2004.08.002
Google Scholar DOI: https://doi.org/10.1016/j.jeconom.2004.08.002

Zhang, L. (2005), The value premium, “The Journal of Finance”, 60 (1), pp. 67–103, https://doi.org/10.1111/j.1540-6261.2005.00725.x
Google Scholar DOI: https://doi.org/10.1111/j.1540-6261.2005.00725.x

Downloads

Published

2022-06-20

How to Cite

Feder‑Sempach, E., & Szczepocki, P. (2022). The Bayesian Method in Estimating Polish and German Industry Betas. A Comparative Analysis of the Risk between the Main Economic Sectors from 2001–2020. Comparative Economic Research. Central and Eastern Europe, 25(2), 45–60. https://doi.org/10.18778/1508-2008.25.12

Issue

Section

Articles