Forecasting banks return on equity using leading economic indicators
The research examines an approach to forecast return on equity using leading economic indicators for short periods in banks. ROE is one of the most important ratios for performance measurement. Its adequacy is necessary for competitiveness, attract funding in financial markets, accumulate reserve for future turbulences, secure compliance with supervisory requirements and maintain positive signals for the market. There is still a debate in the literature on factors of commercial banks’ profitability forecasting, techniques, and most appropriate models to improve the correctness of predicting and acquiring more accurate signals for communication on targets. The problems are still relevant from both a theoretical perspective and practical implementation. This research aims to prove the necessity to include leading economic indicators for short term ROE forecasting. It conducts investigations for the relevant studies, using regression analysis, necessary tests, ascertains opportunities and limitations of using these indicators and develops a conceptual model and its assessment major Baltic banks. The results show verification of approach to forecast ROE using leading economic indicators for short periods. Such study complements signalling theory with a new approach, how to predict and acquire signal not only using economic indicators as a general group but sub-group them into coinciding, lagging and leading.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Adhikari, N. C. D., Domakonda, N., Chandan, C., Gupta, G., Garg, R., Teja, S., & Misra, A. (2019). An intelligent approach to demand forecasting. In International Conference on Computer Networks and Communication Technologies (pp. 167–183). Springer. https://doi.org/10.1007/978-981-10-8681-6_17
Alalaya, M., & Khattab, S. A. (2015). A case study in business market: banks’ profitability: evidence from Jordanian commercial banks (2002–2015). International Journal of Business Management and Economic Research, 6(4), 204–213.
Ali, M., & Puah, C. H. (2018). The internal determinants of bank profitability and stability. Management Research Review, 42(1), 49–67. https://doi.org/10.1108/MRR-04-2017-0103
Alharbi, A. T. (2017). Determinants of Islamic banks’ profitability: international evidence. International Journal of Islamic and Middle Eastern Finance and Management, 10(3), 331–350. https://doi.org/10.1108/IMEFM-12-2015-0161
Beccalli, E., Bozzolan, S., Menini, A., & Molyneux, P. (2015). Earnings management, forecast guidance and the banking crisis. The European Journal of Finance, 21(3), 242–268. https://doi.org/10.1080/1351847X.2013.809548
Borio, C., Gambacorta, L., & Hofmann, B. (2017). The influence of monetary policy on bank profitability. International Finance, 20(1), 48–63. https://doi.org/10.1111/infi.12104
Buchatskaya, V., Buchatsky, P., & Teploukhov, S. (2015). Forecasting methods classification and its applicability. Indian Journal of Science and Technology, 8(30). https://doi.org/10.17485/ijst/2015/v8i1/84224
Bordeleau, E., & Graham, C. (2010). The impact of liquidity on bank profitability. Financial Stability Department, Bank of Canada. Working Paper 2010-38.
Brezina, I., Pekár, J., Čičková, Z., & Reiff, M. (2016). Herfindahl–Handschman index level of concentration values modification and analysis of the change. Central European Journal of Operations Research, 24(1), 49–72. https://doi.org/10.1007/s10100-014-0350-y
Chambers, J. C., Mullick, S. K., & Smith D. D. (1971). How to choose the right forecasting technique. Harvard Business Review, July.
Chang, T. M., Hsu, M. F., & Lin, S. J. (2018). Integrated news mining technique and AI-based mechanism for corporate performance forecasting. Information Sciences, 424, 273–286. https://doi.org/10.1016/j.ins.2017.10.004
Croitoru, A. (2012). The theory of economic development: An inquiry into profits, capital, credit, interest and the business cycle. Journal of Comparative Research in Anthropology and Sociology, 3(02), 137–148.
Čekanavičius, V., & Murauskas, G. (2015). Statistika and jos taikymai (1rst ed.). Technologijos TEV.
De Waal, T., Pannekoek, J., & Scholtus, S. (2011). Handbook of statistical data editing and imputation (Vol. 563). John Wiley and Sons. https://doi.org/10.1002/9780470904848
Demandgüç-Kunt, A., & Huizinga, A. (1998). Determinants of commercial bank interest margins and profitability: some international evidence. World Bank Economic Review, 13, 379–408. https://doi.org/10.1093/wber/13.2.379
Delechat, C., Arbelaez, C. H., Muthoora, M. P. S., & Vtyurina, S. (2012). The determinants of banks’ liquidity buffers in Central America (No. 12-301). International Monetary Fund. https://doi.org/10.5089/9781616356675.001
Dietrich, A., & Wanzenried, G. (2011). Determinants of bank profitability before and during the crisis: Evidence from Switzerland. Journal of International Financial Markets, Institutions and Money, 21(3), 307–327. https://doi.org/10.1016/j.intfin.2010.11.002
Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428. https://doi.org/10.1093/biomet/37.3-4.409
Eurostat – Statistical office of the European Union. (2019). Thematic glossaries by statistical themes. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Thematic_glossaries
ECB. (2015). Financial stability review. European Central bank. ISSN 1830-2025.
ECB. (2011). Beyond ROE – How to measure bank performance: Appendix to the report on EU banking structures. Frankfurt am Main European Central bank. https://www.ecb.europa.eu/pub/pdf/other/beyondroehowtomeasurebankperformance201009en.pdf
Forti, C., & Schiozer, R. F. (2015). Bank dividends and signaling to information-sensitive depositors. Journal of Banking & Finance, 56, 1–11. https://doi.org/10.1016/j.jbankfin.2015.02.011
Fritsche, U., & Stephan, S. (2002). Do leading indicators help to predict business cycle turning points in Germany? German Institute for Economic Research. ISSN 1619-4535.
García-Meca, E., & García-Sánchez, I. (2017). Does managerial ability influence the quality of financial reporting? European Management Journal, 36(4), 544–557. https://doi.org/10.1016/j.emj.2017.07.010
Gaspar, J. V. S. C. (2015). The impact of real estate market in financial stability: commercial banks exposure. Dissertação de Mestrado em Economia apresentada à Faculdade de Economia da Universidade de Coimbra para obtenção do grau de Mestre.
García-Herrero, A., Gavilá, S., & Santabárbara, D. (2009). What explains the low profitability of Chinese banks? Journal of Banking and Finance, 33(11), 2080–2092. https://doi.org/10.1016/j.jbankfin.2009.05.005
Gruber, M., Kavan, S., & Stockert, P. (2017). What drives Austrian banking subsidiaries’ return on equity in CESEE and how does it compare to their cost of equity? Financial Stability Report, (33), 78–87.
Horváth, R., Seidler, J., & Weill, L. (2014). Bank capital and liquidity creation: Granger-causality evidence. Journal of Financial Services Research, 45(3), 341–361. https://doi.org/10.1007/s10693-013-0164-4
Hyndman, R. J., & Athanasopoulos, G. (2014). Forecasting: principles and practice (2nd ed.). OTexts: Melbourne, Australia. OTexts.com/fpp2
Horton, R., Searls, P., & Stone, K. (2014). Integrated performance management. Plan. Budget. Forecast. The Creative Studio at Deloitte, London, 33624A, 28.
Hoffmann, P. S. (2011). Determinants of the profitability of the US banking industry. International Journal of Business and Social Science, 2(22).
Jurevičienė, D., & Rauličkis, D. (2016). Identification of indicators’ applicability to settle borrowers’ probability of default. Economic and Culture, 13(1), 53–64. https://doi.org/10.1515/jec-2016-0007
Kim, K., Pandit, S., & Wasley, C. E. (2015). Macroeconomic uncertainty and management earnings forecasts. Accounting Horizons, 30(1), 157–172. https://doi.org/10.2308/acch-51311
Keynes, J. M. (2018). The general theory of employment, interest, and money. Springer. https://doi.org/10.1007/978-3-319-70344-2
Knight, F. (1921). Risk, uncertainty and profit. Hart Schaffner, and Marx. New York.
Nguyen, T. H. (2020). Impact of bank capital adequacy on bank profitability under BASEL II accord: evidence from Vietnam. Journal of Economic Development, 45(1).
Nippala, E., & Julin, P. (2012, 26–29 June). Leading indicators for forecasting civil engineering market development. CIB Conference. Montreal, Canada, Management of Construction: Research to Practice. http://www.vtt.fi/files/sites/infra2030/2_leading_indicators_for_forecasting_civil_engineering_market_development.pdf
Organization for Economic Co-operation and Development. (2019). OECD Composite Leading Indicators. https://www.oecd.org/sdd/leading-indicators/CLI-components-and-turning-points.pdf
Ommeren, S. V. (2011). An examination of the determinants of banks’ profitability in the European banking sector. Erasmus University. Rotterdam.
Ou, T.-Y., Cheng, C.-Y., Chen, P.-J., & Perng, C. (2016). Dynamic cost forecasting model based on extreme learning machine – A case study in steel plant. Computers and Industrial Engineering, 101, 544–553. https://doi.org/10.1016/j.cie.2016.09.012
Park, S. Y., & Yoo, K. H. (2016). CEO career concerns and voluntary disclosure. Journal of Applied Business Research, 32(6), 1603. https://doi.org/10.19030/jabr.v32i6.9811
Pasiouras, F., & Kosmidou, K. (2007). Factors influencing the profitability of domestic and foreign commercial banks in the European Union. Research in International Business and Finance, 21(2), 222–237. https://doi.org/10.1016/j.ribaf.2006.03.007
Petria, N., Capraru, B., & Ihnatov, I. (2015). Determinants of banks’ profitability: evidence from EU 27 banking systems. Procedia Economics and Finance, 20, 518–524. https://doi.org/10.1016/S2212-5671(15)00104-5
Quaedvlieg, R. (2019). Multi-horizon forecast comparison. Journal of Business and Economic Statistics, 1–34. https://doi.org/10.1080/07350015.2019.1620074
Qingbin, C. (2005). A dynamic model for profitability analysis of construction fandoms: towards complexity, learning and uncertainty. A dissertation submitted to the faculty of Purdue University.
Regehr, K., & Sengupta, R. (2016). has the relationship between bank size and profitability changed? Economic Review-Federal Reserve Bank of Kansas City, 101(2), 1.
Sayari, K., & Shamki, D. (2016). Commercial banks profitability and stock market developments. Journal of Applied Finance and Banking, 6(4), 43.
Sharma, P., & Gounder, N. (2012). Profitability determinants of deposit institutions in small, underdeveloped financial systems: the case of Fiji. Griffith Business School Discussion Papers Finance, No. 2012-06. https://doi.org/10.2139/ssrn.2187251
Shcherbakov, M. V., Brebels, A., Shcherbakova, N. L., Tyukov, A. P., Janovsky, T. A., & Kamaev, V. A. (2014). A survey of forecast error measures. World Applied Sciences Journal, Information and Technologies in Modern Industry, Education and Society, 24, 171–176. ISSN 1818-4952.
Stockert, P., Kavan, S., & Gruber, M. (2016). What drives Austrian banking subsidiaries’ ROE in CESEE and how does it compare to their cost of equity? OeNB, Financial Stability Report, 33, 78–88.
Spence, M. (2002). Signalling in retrospect and the informational structure of markets. American Economic Review, 92, 434–459. https://doi.org/10.1257/00028280260136200
Trujillo-Ponce, A. (2012). What determines the profitability of banks? Evidence from Spain. Accounting and Finance, 53, 561–586. https://ssrn.com/abstract=2072216
Valverde, S., & Fernández, F. (2007). The determinants of bank margins in European banking. Journal of Banking and Finance, 31(7), 2043–2063. https://doi.org/10.1016/j.jbankfin.2006.06.017
Vašíček, B., Žigraiová, D., Hoeberichts, M., Vermeulen, R., Šmídková, K., & de Haan, J. (2017). Leading indicators of financial stress: New evidence. Journal of Financial Stability, 28, 240–257. https://doi.org/10.1016/j.jfs.2016.05.005