Partially informed investors: hedging in an incomplete market with default

Tardelli, Paola

doi:10.1239/jap/1445543842

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…Yang and Zhao applied it to the special type of forward and backward stochastic differential equations (FB-SDE) that appeared in finance and stochastic control and provided convergence analysis for the recently proposed multistep scheme [4], but this method is more difficult to solve. Tardelli uses reverse stochastic differential equations (BSDE) and filtering techniques to study stochastic control problems [5], but this method has certain limitations; it requires a sequence of functions that converge to a value function. Wang et al use the method and Monte Carlo method to study the optimal investment problem of DC pension under inflation and loss avoidance [6], but this method has a large amount of calculation and slower improvement in accuracy.…”

Section: Proposed Methodsmentioning

confidence: 99%

[Retracted] Dynamic Index Optimal Investment Strategy Based on Stochastic Differential Equations in Financial Market Options

Zhang

2021

Wireless Communications and Mobile Computing

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With the gradual development and improvement of the financial market, financial derivatives such as futures and options have also become the objects of competition in the financial market. Therefore, how to make the most favorable and optimized investment and consumption when options are included? It has become a problem facing investors. Aiming at the optimal investment problem of investors, this paper studies the calculation of an optimal investment strategy in stochastic differential equations in financial market options on the basis of fuzzy theory. Now, stochastic calculus has become an important branch of stochastic analysis, finance, control, and other fields. The study of introducing stochastic differential equations is mainly to solve the stochastic control problem, which is the principle of the stochastic maximum. In finance, some hedging or pricing problems of contingent rights can eventually be transformed into a series of stochastic differential equations. Based on the historical data of five aspects of bank deposits, bonds, funds, stocks, and real estate of four listed insurance companies, the paper analyzes the optimization strategy of the capital investment of listed insurance companies based on the investment yield of the domestic investment market. According to the final results, the historical proportion of bank deposits of the superior company is 27%, and the optimal proportion given by the model is 25%; the total proportion of funds and stocks is 15%, and the optimal proportion of funds analyzed in the model is 20% and the optimal proportion of stocks is 10%. Therefore, the final results show that the investment efficiency of listed insurance companies can actually increase investment in stocks and funds and reduce the proportion of bank deposits to obtain greater investment returns.

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Section: Proposed Methodsmentioning

confidence: 99%

[Retracted] Dynamic Index Optimal Investment Strategy Based on Stochastic Differential Equations in Financial Market Options

Zhang

2021

Wireless Communications and Mobile Computing

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“…Pricing and hedging problems for contingent claims under incomplete information using filtering techniques have been studied in credit risk context, in Frey and Runggaldier [25], Frey and Schmidt [26], Tardelli [45] and in the insurance framework in Ceci et al [17] under the hypothesis of independence between the financial and the insurance markets.…”

Section: Introductionmentioning

confidence: 99%

Unit-linked life insurance policies: Optimal hedging in partially observable market models

Ceci

Colaneri

Cretarola

2017

Insurance: Mathematics and Economics

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Abstract. In this paper we investigate the hedging problem of a unit-linked life insurance contract via the local risk-minimization approach, when the insurer has a restricted information on the market. In particular, we consider an endowment insurance contract, that is a combination of a term insurance policy and a pure endowment, whose final value depends on the trend of a stock market where the premia the policyholder pays are invested. We assume that the stock price process dynamics depends on an exogenous unobservable stochastic factor that also influences the mortality rate of the policyholder. To allow for mutual dependence between the financial and the insurance markets, we use the progressive enlargement of filtration approach.We characterize the optimal hedging strategy in terms of the integrand in the Galtchouk-Kunita-Watanabe decomposition of the insurance claim with respect to the minimal martingale measure and the available information flow. We provide an explicit formula by means of predictable projection of the corresponding hedging strategy under full information with respect to the natural filtration of the risky asset price and the minimal martingale measure. Finally, we discuss applications in a Markovian setting via filtering.

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Structural credit risk models with stochastic default barriers and jump clustering using Hawkes jump-diffusion processes

Pasricha,

Selvamuthu,

Tardelli

2024

OPSEARCH

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This paper derives a closed-form expression for the default probability and the default correlation of firms under a structural model of credit risk. Specifically, the underlying firms are assumed to have the value process driven by a Hawkes jump-diffusion model with the continuous parts of the trajectories being driven by correlated Brownian motions, while the jumps being driven by Hawkes processes having general structure of the exciting functions. The proposed framework takes into account the numerically observed facts about the default, i.e., clustering and unexpectedness. Furthermore, the default barriers are assumed to be stochastic in nature and modeled as stochastic processes, affected by common factors reflecting the systematic risk. A sensitivity analysis of default probability and correlation is conducted to investigate the impact of jump risk, clustering, and stochastic default barriers. These numerical studies demonstrate that jump clustering increases the default probability but reduces the correlation of defaults.

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Partially informed investors: hedging in an incomplete market with default

Cited by 3 publications

References 20 publications

[Retracted] Dynamic Index Optimal Investment Strategy Based on Stochastic Differential Equations in Financial Market Options

[Retracted] Dynamic Index Optimal Investment Strategy Based on Stochastic Differential Equations in Financial Market Options

Unit-linked life insurance policies: Optimal hedging in partially observable market models

Structural credit risk models with stochastic default barriers and jump clustering using Hawkes jump-diffusion processes

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