The performance of bank portfolio optimization
Catarina Coelho
Department of Mathematics, University of Coimbra, Coimbra, Portugal
Search for more papers by this authorJosé Luis Santos
CMUC, Department of Mathematics, University of Coimbra, Apartado 3008, Coimbra, Portugal
Search for more papers by this authorCorresponding Author
Pedro Júdice
ISCTE Business Research Unit, Avenida das Forças Armadas, Lisboa, Portugal
Corresponding author.
Search for more papers by this authorCatarina Coelho
Department of Mathematics, University of Coimbra, Coimbra, Portugal
Search for more papers by this authorJosé Luis Santos
CMUC, Department of Mathematics, University of Coimbra, Apartado 3008, Coimbra, Portugal
Search for more papers by this authorCorresponding Author
Pedro Júdice
ISCTE Business Research Unit, Avenida das Forças Armadas, Lisboa, Portugal
Corresponding author.
Search for more papers by this authorAbstract
Given a liability structure, the bank portfolio optimization determines an asset allocation that maximizes profit, subject to restrictions on Basel III ratios and credit, liquidity, and market risks. Bank allocation models have not been tested using historical data. Using an optimization model based on turnover constraints, we develop such tests, which document the superior performance of optimization strategies compared to heuristic rules, resulting in an average annual out-of-sample outperformance of 15.1% in terms of return on equity using our data set. This outperformance is remarkable and contrasts with the reported underperformance of several portfolio optimization methods in the case of investment management.
References
- Aas, K., 2005. The Basel II IRB approach for credit portfolios: A survey. https://www.semanticscholar.org/paper/The-Basel-II-IRB-approach-for-credit-portfolios-%3A-A-Aas/70ebdb2769006a99f88f10f757072c59e0a46506 (accessed 1 June 2023).
- Bai, X., Scheinberg, K., Tutuncu, R., 2016. Least-squares approach to risk parity in portfolio selection. Quantitative Finance 16, 3, 357–376.
- Bandyopadhyay, A., Singh, P., 2007. Estimating recovery rates on bank's historical loan loss data. https://mpra.ub.uni-muenchen.de/9525/1/MPRA/_paper/_9525.pdf (accessed 1 June 2023).
- Basel Committee on Banking Supervision, 2010. Basel III: A global regulatory framework for more resilient banks and banking systems. https://www.bis.org/publ/bcbs189.pdf (accessed 1 June 2023).
- Basel Committee on Banking Supervision, 2005. An explanatory note on the Basel II IRB risk weight functions. https://www.bis.org/bcbs/irbriskweight.htm (accessed 1 June 2023).
- Birge, J.R., Júdice, P., 2013. Long-term bank balance sheet management: Estimation and simulation of risk-factors. Journal of Banking & Finance 37, 12, 4711–4720.
- Bridgewater Associates, 2009. The all-weather strategy, https://www.bridgewater.com/research-and-insights/the-all-weather-strategy (accessed 1 June 2023).
- Brito, R.P., Júdice, P., 2023. Efficient credit portfolios under IFRS 9. International Transactions in Operational Research 30, 2453–2484.
- Chaves, D., Hsu, J., Li, F., Shakernia, O., 2011. Risk parity portfolio vs. other asset allocation heuristic portfolios. The Journal of Investing 20, 1, 108–118.
10.3905/joi.2011.20.1.108 Google Scholar
- Cornuejols, G., Tütüncü, R., 2006. Optimization Methods in Finance. Mathematics, Finance and Risk, Cambridge University Press, New York.
10.1017/CBO9780511753886 Google Scholar
- DeMiguel, V., Garlappi, L., Uppal, R., 2009. Optimal versus naive diversification: How inefficient is the 1/n portfolio strategy? The Review of Financial Studies 22, 5, 1915–1953.
- European Banking Authority, 2013. Risk-weighted exposure amounts for retail exposures (article 154). https://www.eba.europa.eu/regulation-and-policy/single-rulebook/interactive-single-rulebook/-/interactive-single-rulebook/article-id/5006 (accessed 1 June 2023).
- European Banking Authority, 2022. Risk dashboard.https://www.eba.europa.eu/risk-analysis-and-data/risk-dashboard (accessed 1 June 2023).
- Federal Reserve Bank of St. Louis, 2023. 10-year treasury constant maturity rate. https://fred.stlouisfed.org/series/WGS10YR (accessed 1 June 2023).
- Federal Reserve Bank of St. Louis, 2023. 30-year fixed rate mortgage average in the United States. https://fred.stlouisfed.org/series/MORTGAGE30US (accessed 1 June 2023).
- Federal Reserve Bank of St. Louis, 2023. Charge-off rate on consumer loans, all commercial banks. https://fred.stlouisfed.org/series/CORCACBS (accessed 1 June 2023).
- Federal Reserve Bank of St. Louis, 2023. Charge-off rate on loans secured by real estate, all commercial banks. https://fred.stlouisfed.org/series/CORSREACBS (accessed 1 June 2023).
- Federal Reserve Bank of St. Louis, 2023. Effective federal funds rate. https://fred.stlouisfed.org/series/FEDFUNDS (accessed 1 June 2023).
- Federal Reserve Bank of St. Louis, 2023. Finance rate on personal loans at commercial banks, 24 month loan. https://fred.stlouisfed.org/series/TERMCBPER24NS (accessed 1 June 2023).
- Federal Reserve Bank of St. Louis, 2023. Moody's seasoned BAA corporate bond yield. https://fred.stlouisfed.org/series/BAA (accessed 1 June 2023).
- Gordy, M., 2003. A risk-factor model foundation for ratings-based bank capital rules. Journal of Financial Intermediation 12, 3, 199–232.
- Hahm, J., Shin, H.S., Shin, K., 2013. Noncore bank liabilities and financial vulnerability. Journal of Money, Credit and Banking 45, 3–36.
- Halaj, G., 2013. Optimal asset structure of a bank - bank reactions to stressful market conditions. Working Paper Series 1533, European Central Bank, Frankfurt.
- Hałaj, G., 2016. Dynamic balance sheet model with liquidity risk. International Journal of Theoretical and Applied Finance 19, 7, 1650052.
10.1142/S0219024916500527 Google Scholar
- Hooshmand, F., Anoushirvani, Z., MirHassani, S., 2023. Model and efficient algorithm for the portfolio selection problem with real-world constraints under value-at-risk measure. International Transactions in Operational Research 30, 2665–2690.
- Júdice, P., Zhu, Q.J., 2021. Bank balance sheet risk allocation. Journal of Banking & Finance 133, 106257.
- Juszczuk, P., Kaliszewski, I., Miroforidis, J., Podkopaev, D., 2022. Expected mean return–standard deviation efficient frontier approximation with low-cardinality portfolios in the presence of the risk-free asset. International Transactions in Operational Research 30, 2395–2414.
- Kosmidou, K., Zopounidis, C., 2008. Asset liability management techniques. In C. Zopounidis, M. Doumpos, P.M. Pardalos, (eds), Handbook of Financial Engineering, Vol. 18. Springer Optimization and Its Applications, chapter 10, Springer, New York, pp. 281–300.
10.1007/978-0-387-76682-9_10 Google Scholar
- Kusy, M.I., Ziemba, W.T., 1986. A bank asset and liability management model. Operations Research 34, 3, 356–376.
- Lubinska, B., 2018. Contemporary challenges in the asset liability management. In K. Jajuga, H. Locarek-Junge, L.T. Orlowski, (eds) Contemporary Trends and Challenges in Finance. Springer International Publishing, Cham, pp. 159–166.
10.1007/978-3-319-76228-9_15 Google Scholar
- Merrill, C.B., Nadauld, T.D., Stulz, R.M., Sherlund, S.M., et al., 2012. Why did financial institutions sell RMBS at fire sale prices during the financial crisis? Wharton Initiative on Financial Policy and Regulation.
- Moody's Investors Service, 2023. . Annual default study: corporate default rate will rise in 2023 and peak in early 2024. https://www.moodys.com/ (accessed 1 June 2023).
- Mousavi, A., Shen, J., 2023. A penalty decomposition algorithm with greedy improvement for mean-reverting portfolios with sparsity and volatility constraints. International Transactions in Operational Research 30, 2415–2435.
- Roncalli, T., 2013. Introduction to Risk Parity and Budgeting. CRC Press, Boca Raton, FL.
- Roncalli, T., Weisang, G., 2016. Risk parity portfolios with risk factors. Quantitative Finance 16, 3, 377–388.
- Salas-Molina, F., Pla-Santamaria D., Vercher-Ferrandiz, M.L., Garcia-Bernabeu, A., 2023. Geometric compromise programming: application in portfolio selection. International Transactions in Operational Research 30, 2571–2594.
- Schmaltz, C., Pokutta, S., Heidorn, T., Andrae, S., 2014. How to make regulators and shareholders happy under Basel III. Journal of Banking & Finance 46, 311–325.
- Sirignano, J.A., Tsoukalas, G., Giesecke, K., 2016. Large-scale loan portfolio selection. Operations Research 64, 6, 1239–1255.
- The European Parliament and the Council of the European Union, 2013. Corrigendum to Regulation (EU) no 575/2013 of the European Parliament and of the Council of 26 June 2013 on prudential requirements for credit institutions and investment firms and amending regulation (EU) no 648/2012. Official Journal of the European Union 575. L 321/342.
- Tung, J., 2006. Measuring loss-given-default for structured finance securities: an update. https://www.moodys.com/sites/products/DefaultResearch/2006200000430444.pdf (accessed 1 June 2023).
- Uryasev, S., Theiler, U.A., Serraino, G., 2010. Risk-return optimization with different risk-aggregation strategies. The Journal of Risk Finance 11, 2, 129–146.
10.1108/15265941011025161 Google Scholar
- Yan, D., Zhang, X., Wang, M., 2021. A robust bank asset allocation model integrating credit-rating migration risk and capital adequacy ratio regulations. Annals of Operations Research 299, 1, 659–710.