Abstract

This paper first proposes a European option pricing method for deposit insurance based on triangular intuitionistic fuzzy numbers. In the proposed method, we take into account the randomness and fuzziness of bank asset value simultaneously, and hence, the method can adequately reflect the high uncertainty of bank asset value. This method fuzzifies the value of bank asset, resubmits it into the original deposit insurance option pricing model as a fuzzy random variable, and then gives an analytic formula of deposit insurance rates using a risk-neutral method. After this, we have also conducted a numerical analysis. In specific, we have obtained the premium interval and presented the static analysis of key parameters. Finally, seven small- and middle-sized banks in Hunan Province in China are used as examples to validate the proposed interval pricing model. The Black-Scholes option pricing model and Yoshida’s triangular fuzzy model are also employed for comparison. The research results show that the interval rates obtained from the proposed European option pricing method for deposit insurance can better reflect the uncertainty of bank asset evaluation than the fixed rates obtained from the Black-Scholes option pricing model. Moreover, the model proposed in this paper is also superior to Yoshida’s model in practice.

Highlights

  • In May 2015, the Deposit Insurance Regulations came into effect in China, which marked the start of the official establishment of China’s deposit insurance system. e deposit insurance system, the macroprudential supervisory authority, and the final lender function of the central bank constitute the national financial safety net together

  • A large amount of literature on deposit insurance pricing can be found. e most significant milestone is in 1977; Merton [1] found that there is an isomorphic relationship between deposit insurance and common stock put options, so he priced deposit insurance based on the European option pricing method developed by Black and Scholes [2] and Merton [3]

  • To validate the applicability of the proposed European option pricing method for deposit insurance based on triangular intuitionistic fuzzy numbers to the banks in China from a practical perspective, this paper selects the semiannual data of seven small- and medium-sized banks in Hunan Province from June 2015 to the end of 2018. e asset volatility and the ratio of savings to assets of each bank are obtained by calculation

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Summary

Introduction

In May 2015, the Deposit Insurance Regulations came into effect in China, which marked the start of the official establishment of China’s deposit insurance system. e deposit insurance system, the macroprudential supervisory authority, and the final lender function of the central bank constitute the national financial safety net together. According to Merton’s deposit insurance pricing model, certain deposit premium value can be calculated, which depends on the input parameter value, such as the asset value of the bank. Changes in the level of economic and financial development, deposit structure, and the cumulative level of deposit insurance funds will affect the decision-making of the regulatory authorities, further increasing the difficulty for them to accurately set insurance premium rates. Erefore, in the environment with increasing external economic uncertainty, the deposit insurance system should play a better role in the financial safety net, safeguard the interests of depositors, stabilize public confidence, and guard against major risks caused by bank runs. The regulatory authorities should fully consider the current economic level, deposit structure, and the accumulated level of premium fund and make flexible adjustments according to the operation conditions and risk level of each commercial bank. If the regulatory authorities can replace the original fixed premium with a reasonable premium range, the deposit insurance system can fully protect the rights and interests of depositors and enable the insured institutions to allocate funds efficiently and maintain the effective and efficient operation of the financial system

Methodology and Modeling
Model Application and Comparison
Conclusions
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