根据 CEV 扩散模型为杠杆权证定价

IF 0.7 4区 经济学 Q4 BUSINESS, FINANCE Review of Derivatives Research Pub Date : 2024-01-11 DOI:10.1007/s11147-023-09199-1
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引用次数: 0

摘要

摘要 有關槓桿式(及非槓桿式)權證估值的大部分研究均假設相關狀態變數的波幅是恒定的。本文将有关权证定价的文献扩展至状态变量过程的更一般假设,即所谓的方差弹性恒定(CEV)过程。CEV 模型因能捕捉金融经济学文献中的一些经验观察而闻名,即股票收益与波动率之间的不对称和隐含波动率偏斜。使用 CEV 过程,当波动率成为相关状态变量的函数时,我们就能减少定价偏差。我们对欧式认购权证进行定价,对债务期限没有限制。当权证的到期日与债务的到期日相同时,就有可能得到权证价格的闭式解。当权证的到期日与债务的到期日不同时,可以通过非常有效且简单的估值方法来计算价格。
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Pricing levered warrants under the CEV diffusion model

Abstract

Much of the work on the valuation of levered (and unlevered) warrants assumes that the volatility of the underlying state variable is constant. This paper extends the literature on warrant pricing to a more general assumption for the state variable process, the so-called constant elasticity of variance (CEV) process. The CEV model is well-known for its ability to capture some empirical observations found in the financial economics literature, namely the asymmetry between equity returns and volatility and the implied volatility skew. Using the CEV process, we are able to reduce pricing bias as the volatility becomes a function of the underlying state variable. We price European-style call warrants without restrictions on the debt maturity. When warrants have the same maturity as debt, it is possible to obtain closed-form solutions for warrants prices. When the maturity of warrants is different from the maturity of debt, prices can be computed numerically through very efficient and simple to implement valuation methodologies.

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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
8
期刊介绍: The proliferation of derivative assets during the past two decades is unprecedented. With this growth in derivatives comes the need for financial institutions, institutional investors, and corporations to use sophisticated quantitative techniques to take full advantage of the spectrum of these new financial instruments. Academic research has significantly contributed to our understanding of derivative assets and markets. The growth of derivative asset markets has been accompanied by a commensurate growth in the volume of scientific research. The Review of Derivatives Research provides an international forum for researchers involved in the general areas of derivative assets. The Review publishes high-quality articles dealing with the pricing and hedging of derivative assets on any underlying asset (commodity, interest rate, currency, equity, real estate, traded or non-traded, etc.). Specific topics include but are not limited to: econometric analyses of derivative markets (efficiency, anomalies, performance, etc.) analysis of swap markets market microstructure and volatility issues regulatory and taxation issues credit risk new areas of applications such as corporate finance (capital budgeting, debt innovations), international trade (tariffs and quotas), banking and insurance (embedded options, asset-liability management) risk-sharing issues and the design of optimal derivative securities risk management, management and control valuation and analysis of the options embedded in capital projects valuation and hedging of exotic options new areas for further development (i.e. natural resources, environmental economics. The Review has a double-blind refereeing process. In contrast to the delays in the decision making and publication processes of many current journals, the Review will provide authors with an initial decision within nine weeks of receipt of the manuscript and a goal of publication within six months after acceptance. Finally, a section of the journal is available for rapid publication on `hot'' issues in the market, small technical pieces, and timely essays related to pending legislation and policy. Officially cited as: Rev Deriv Res
期刊最新文献
The interaction between equity-based compensation and debt in managerial risk choices An affine model for short rates when monetary policy is path dependent A two-factor structural model for valuing corporate securities Martingale defects in the volatility surface and bubble conditions in the underlying Pricing levered warrants under the CEV diffusion model
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