Value-at-risk capital requirement regulation, risk taking and asset allocation: a mean–variance analysis

Kaplanski, Guy; Levy, Haim

doi:10.1080/1351847x.2013.802249

Cited by 9 publications

(2 citation statements)

References 61 publications

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“…Similarly, in the work of Leippold et al (2006), VaR constraints lead to changes in inter-temporal hedging behaviour increasing risk exposure. The potential for unintended consequences of regulation appears in the research of Kaplanski and Levy (2015): Using the Mean-Variance, CAPM, framework, they argue that through VaR regulation, the CML is shifted downwards. 4 Theoretically, they show how regulation induces a bank to select a less risky portfolio, relative to the unregulated, optimal risky portfolio.…”

Section: Theoretical Perspectivesmentioning

confidence: 99%

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Regulation and De-Risking: Theoretical and Empirical Insights

Haar

Gregoriou

2023

Risks

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The purpose of the Bank for International Settlements regulatory agenda, as implemented by financial regulators globally, has been to make banks safer and reduce the likelihood of systemic events. Using an original model of bank profit maximisation under a regulatory constraint, we statistically examine how market risk exposure has interacted with financial performance and capital structure, to see if the Basel regulatory agenda concerning the quantity, quality and liquidity of capital, has prompted changes in banking behaviour as measured by exposure to market risk. Breaking new ground, we empirically explore how the regulatory agenda has affected the largest banks. We analyse if the regulatory agenda has succeeded in aligning the cost of capital with their exposure to market risk, measured by Value at Risk; or if regulations have induced changes to banking activities. We find rather than regulation inducing changes to the rate at which unchanged risk exposure is capitalised; it leads to changes in the nature of exposures. Risk has declined along with financial performance while the cost of capital is largely unchanged. A consequence of regulation may be to encourage the migration of riskier activities to organisations where it may be borne more cheaply.

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Section: Theoretical Perspectivesmentioning

confidence: 99%

“…Arguably, Market Risk is the most identifiable with systematic risk, as per the Capital Asset Pricing Model. The work of Kaplanski and Levy (2015) is distinct in positing more than one CML, i.e., one with and without regulatory impositions. While intriguing, we ask, how can there be more than one Capital Market Line?…”

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confidence: 99%

Regulation and De-Risking: Theoretical and Empirical Insights

Haar

Gregoriou

2023

Risks

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Dynamic behavioral assessment model based on Hebb learning rule

Yin

Yuan

Zhang

2016

Neural Comput & Applic

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Behavioral assessment based on computing system is with important value for computer-simulated training and system diagnosis. However, the existing assessment is a static method for ex post evaluation, and the low efficiency and high complexity have been the urgent problems to be solved in the academic field. In this paper, we propose an adaptive dynamic behavioral assessment model based on Hebb learning rule that effectively combines the assessment standard and the weights of factors. The dynamic behavioral assessment considers the relative weights between the assessment indexes, whereas the existing assessment method does not; the dynamic behavioral assessment uses the assessment standard data recursively and can conduct an instant assessment for the objectives. We have built an assessment system for computer-simulated training, and took the pilot behavioral assessment for example to test and verify the dynamic behavioral assessment mode. Experimental results show that the dynamic behavioral assessment model based on Hebb learning rule has more advantage in assessment efficiency and online computing support.

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A robust bank asset allocation model integrating credit-rating migration risk and capital adequacy ratio regulations

2020

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In this paper, we consider a bank asset allocation problem with uncertain migration risk of credit ratings and capital adequacy ratio (CAR) regulations. In the practical scenarios, the future market values of each risky asset are largely affected by outer complex environments. We only observe the information about their first-moment and marginal second-moment of year-ahead market value of each loan asset. Based on these scenarios, we propose a new distributionally robust optimization model with the chance constraint characterized by uncertain capital adequacy ratio. Following the duality theory in infinite-dimensional optimization problem and the theory of conic linear optimization model, we can reformulate the original problem into a tractable linear deterministic semi-definite programming (SDP) model. By using this tractable linear SDP model, we can provide a robust asset allocation policy to bank managers. Further, we conduct a simulation study to illustrate the application of our method under two different economic conditions, a downward condition and an upward condition. Then a series of sensitivity tests is applied to examine the impacts of various factors, including safety probability, target CAR and recovery rate, on the optimal asset allocations. We also compare the performance of our model and the CVaR model. We demonstrate our model provides an efficient way to deal with the trade-off between expected return and CAR.

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Value-at-risk capital requirement regulation, risk taking and asset allocation: a mean–variance analysis

Cited by 9 publications

References 61 publications

Regulation and De-Risking: Theoretical and Empirical Insights

Regulation and De-Risking: Theoretical and Empirical Insights

Dynamic behavioral assessment model based on Hebb learning rule

A robust bank asset allocation model integrating credit-rating migration risk and capital adequacy ratio regulations

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