dEjournals Nyitóoldal
Economica
Nyitólap Aktuális Megjelenés alatti
Archívum Keresés
Regisztráció Bejelentkezés

Economica

Megjelenés előtti cikkek
Folyóiratcikk

The impact of energy crisis on variance- and Gini-optimized portfolio structures – case of Hungary

Megjelent:
2024-11-13
DOI Linkhttps://doi.org/10.47282/economica////14379
Szerzők
Megtekintés
pdf (Angol)
Kulcsszavak
mean-Gini portfolio optimization stock market energy crisis
Hogyan hivatkozzuk
Kiválasztott formátum: APA
Tömöri, G., & Csontos, G. (2024). The impact of energy crisis on variance- and Gini-optimized portfolio structures – case of Hungary. Economica, 1-13. https://doi.org/10.47282/economica////14379
Absztrakt

Crises in the 2020s have shocked global stock markets with unprecedented sud- denness. This has had a particularly strong impact on the Central European countries outside the euro area and exposed to heightened geopolitical conflicts, and within them, Hungary, which has had a particular government response to the crisis. Our research objective was to investigate the impact of the energy crisis on the Hungarian stock market as a consequence of the combination of greening policies, the post-Covid reopening and the EU sanctions policy on Russian energy imports, focusing on the portfolio optimization of the Hungarian blue chips and the stocks of the biggest complex (renewable and non-renewable) energy producer and trader company in the Hungarian market. In this context, our aim is to determine the impact of the turbulent crisis phenomena in the period 2020-2023, with a focus on energy price inflation, on the structure of a portfolio of the 5 stocks mentioned above optimized based on mean-variance and mean-Gini model. Since based on both methods, although differently, significantly increased the portfolio weight of the same energy company stocks in the energy crisis, it can be concluded that the change in the composition of the diversified portfolio reflected the impact of macroeconomic conditions on the stock market.

Hivatkozások
  1. : Acharya VV, Pedersen LH, Philippon T, Richardson M (2017) Measuring systematic risk. The Review of Financial Studies, 30(1): 2–47
  2. : Agouram J, Lakhnati G (2016) Mean-Gini and mean-extended gini portfolio selec- tion: An empirical analysis. Risk Governance and Control: Financial Markets and Institutions, 6(3-1): 59-66. https://doi.org/10.22495/rcgv6i3c1art7
  3. : Anagnostopoulos KP, Mamanis G (2010) A portfolio optimization model with three objectives and discrete variables. Computers and Operations Research, 37(7): 1285-1297. https://doi.org/10.1016/j.cor.2009.09.009
  4. : Bakos P (2020) A COVID-19 hatása a tőkepiacokra, https://www.bet.hu/Rolunk/Sajtoszoba/szakmai-cikkek-es-tanulmanyok/a-covid-19-hatasa-a-tokepiacokra. Accessed 12 October 2023
  5. : Best MJ (2010) Portfolio optimization. CRC Press.
  6. : Brealey RA, Myers SC (2005) Modern corporate finance. Budapest, Panem.
  7. : Brown CE (1998) Coefficient of variation. Applied multivariate statistics in geohydrology and related sciences. Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-80328-4 13
  8. : Brückner G (2023) Háború, energiaválság, különadók: a BUX-index tavaly 13,6 százalékkal gyengült, https://telex.hu/gazdasag/2023/01/01/tozsde-reszveny-valsag-haborukulonadok-bux-index-minusz13-6-szazalek. Accessed 21 October 2023
  9. : Bugár Gy, Uzsoki M (2006) Befektetések kockázatának mérése. Statisztikai Szemle. 84(9): 876-898.
  10. : Bugár G, Uzsoki M (2011) Portfolio optimization strategies: Performance evalua- tion with respect to different objectives. Journal of Transnational Management, 16(3): 135-148. https://doi.org/10.1080/15475778.2011.596773
  11. : Chaweewanchon, A., Chaysiri, R. (2022) Markowitz Mean-Variance Portfolio Opti- mization with Predictive Stock Selection Using Machine Learning. International Journal of Financial Studies, 10(3): 64. https://doi.org/10.3390/ijfs10030064
  12. : Cheung CS, Kwan CC, Miu PC (2007) Mean-Gini portfolio analysis: A pedagogic illustration. Spreadsheets in Education, 2(2): 194-207.
  13. : Douglas Montgomery C, Runger GC (1994): Applied Statistics and Probability for Engineers. New York, Chichester, John Wiley and Sons.
  14. : Goldthau AC, Youngs, R (2023) The EU energy crisis and a new geopolitics of climate transition. Journal of Common Market Studies, 61: 115- https://doi.org/10.1111/jcms.13539
  15. : Gunjan A, Bhattacharyya S (2023) A brief review of portfolio optimization techniques. Artificial Intelligence Review, 56(5): 3847-3886. https://doi.org/10.1007/s10462-022-10273-7
  16. : Hali NA, Yuliati A (2020) Markowitz model investment portfolio optimization: a review theory. International Journal of Research in Community Services, 1(3): 14-18. https://doi.org/10.46336/ijrcs.v1i3.104
  17. : Hoe LW, Jaaman SH, Siew LW (2020) Portfolio optimization of technology companies in Malaysia with Mean-Gini Model. Menemui Matematik (Discovering Mathematics), 42(1): 45-50.
  18. : Hutter C, Weber E (2022) Russia-Ukraine war: Short-run production and labour market effects of the energy crisis, 10. https://doi.org/10.48720/IAB.DP.2210
  19. : Jamal A, Ghizlane L (2015) A Comparative Study of Mean-Variance and Mean Gini Portfolio Selection Using VaR and CVaR. Journal of Financial Risk Management, 4: 72-81. https://doi.org/10.4236/jfrm.2015.42007
  20. : Ji R (2016) Models and Algorithms for Portfolio Optimization Under Uncertainty.
  21. The George Washington University
  22. : Ji R, Lejeune MA, Prasad SY (2018) Interactive portfolio optimization using Mean- Gini criteria. Financial Decision Aid Using Multiple Criteria: Recent Models and Applications, 49-91.
  23. : Mansini R, Ogryczak W, Speranza MG (2015) Linear models for portfolio optimization. Linear and Mixed Integer Programming for Portfolio Optimization, 19-45.
  24. : Markowitz HM (1952) Portfolio Selection. The Journal of Finance. 7(1): 77-91.
  25. : Mba JC, Ababio KA, Agyei SK (2022) Markowitz mean-variance portfolio selection and optimization under a behavioral spectacle: New empirical evidence. International Journal of Financial Studies, 10(2): 28. https://doi.org/10.3390/ijfs10020028
  26. : Mukhopadhyay, D. (2023). Does Green Investing Generate Return Over Conventional Funds? A Comparative Portfolio Analysis with Indian Stock Market. In Economic, Environmental and Health Consequences of Conservation Capital: A Global Perspective (pp. 85-96). Singapore: Springer Nature Singapore.
  27. : Myles EM (2013) A simplified perspective of the Markowitz portfolio theory. Global journal of businnes research, 7(1): 59-70.
  28. : Naccarato A, Pierini A, Ferraro G (2021) Markowitz portfolio optimization through pairs trading cointegrated strategy in long-term investment. Annals of Operations Research, 299 (1-2): 81-99. https://doi.org/10.1007/s10479-019-03225-y
  29. : Ozili PK, Ozen E (2023) Global energy crisis: impact on the global economy. The Impact of Climate Change and Sustainability Standards on the Insurance Market, 439-454. https://doi.org/10.1002/9781394167944.ch29
  30. : Pálos M (2023) Az Oroszországban maradt nagy európai cégek 100 milliárd eurót buktak, https://g7.hu/vallalat/20230808/az-oroszorszagban-maradt-nagy-europai-cegek- 100-milliard-eurot-buktak/. Accessed 12 October 2023
  31. : Pupos T (2013) Pénzügyi ismeretek, Debreceni Egyetem, 56-58.
  32. : Ringuest JL, Graves SB, Case RH (2004) Mean–Gini analysis in RandD portfolio selection. European Journal of Operational Research, 154(1): 157-169. https://doi.org/10.1016/S0377-2217(02)00708-7
  33. : Yang B, Berger J (1994) Estimation of a covariance matrix using the reference prior. The Annals of Statistics, 22(3): 1195-1211.
  34. : Schechtman E, Yitzhaki S, Artsev Y (2006) The similarity between mean-variance and mean-Gini: Testing for equality of Gini correlations. Advances in Investment Analysis and Portfolio Management, 3: 97-122. http://dx.doi.org/10.2139/ssrn.938178
  35. : Shalit H, Yitzhaki S (1984) Mean-Gini, Portfolio Theory, and the Pricing of Risky Assets. The Journal of Finance, 39 (5): 1449-1468. https://doi.org/10.1111/j.1540-6261.1984.tb04917.x
  36. : Shalit H, Yitzhaki S (2005) The mean-Gini efficient portfolio frontier. Journal of Financial Research, 28(1): 59-75. https://doi.org/10.1111/j.1475-6803.2005.00114.x
  37. : Siew LW, Jaaman SH, Hoe LW (2019) Mathematical modelling of risk in portfolio optimization with Mean-Gini approach. In Journal of Physics: Conference Series, 1212(1): 12-31. https://doi.org/10.1088/1742-6596/1212/1/012031
  38. : Trichilli Y, Abbes MB, Masmoudi A (2020) Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis. Research in International Business and Finance, 51: 101071. https://doi.org/10.1016/j.ribaf.2019.1010711
  39. : Tola V, Lillo F, Gallegati M, Mantegna RN (2008) Cluster analysis for portfolio optimization. Journal of Economic Dynamics and Control, 32(1): 235-258.
  40. : Ubukata M, Watanabe T (2014) Market variance risk premiums in Japan for asset predictability. Empirical Economics, 47, 169-198. https://doi.org/10.1007/s00181-013-0741-2
  41. : Zanjirdar M. (2020) Overview of portfolio optimization models. Advances in mathematical finance and applications, 5(4): 419-435. https://doi.org/10.22034/amfa.2020.1897346.1407
Ugyanannak a szerző(k)nek a legtöbbet olvasott cikkei