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文件名:  Gap_Risk_KVA_and_Repo_Pricing:_An_Economic_Capital_Approach_in_the_Black-Scholes.pdf
资料下载链接地址: https://bbs.pinggu.org/a-3677973.html
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英文标题:
《Gap Risk KVA and Repo Pricing: An Economic Capital Approach in the
Black-Scholes-Merton Framework》
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作者:
Wujiang Lou
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最新提交年份:
2016
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英文摘要:
Although not a formal pricing consideration, gap risk or hedging errors are the norm of derivatives businesses. Starting with the gap risk during a margin period of risk of a repurchase agreement (repo), this article extends the Black-Scholes-Merton option pricing framework by introducing a reserve capital approach to the hedging error\'s irreducible variability. An extended partial differential equation is derived with two new terms for expected gap loss and economic capital charge, leading to the gap risk economic value adjustment and capital valuation adjustment (KVA) respectively. Practical repo pricing formulae is obtained showing that the break-even repo rate decomposes into cost of fund and economic capital charge in KVA. At zero haircut, a one-year term repo on main equities could command a capital charge as large as 50 basis points for a \'BBB\' rated borrower.
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中文摘要:
尽管不是正式的定价考虑,缺口风险或对冲错误是衍生品业务的常态。本文从回购协议(repo)风险保证金期内的缺口风险入手,通过引入储备资本方法来解决套期保值误差的不可约可变性,扩展了Black-Scholes-Merton期权定价框架。推导了一个扩展偏微分方程,其中包含了预期缺口损失和经济资本费用的两个新项,分别导致缺口风险经济价值调整和资本估值调整(KVA)。得到了实际回购定价公式,表明盈亏平衡回购利率分解为资金成本和经济资本费用,单位为KVA。在零折减的情况下,对评级为“BBB”的借款人而言,主要股票的一年期回购可能需要高达50个基点的资本支出。
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分类信息:

一级分类:Quantitative Finance 数量金融学
二级分类:Pricing of Securities 证券定价
分类描述:Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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一级分类:Quantitative Finance 数量金融学
二级分类:Mathematical Finance 数学金融学
分类描述:Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法,包括随机、概率和泛函分析、代数、几何和其他方法
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一级分类:Quantitative Finance 数量金融学
二级分类:Risk Management 风险管理
分类描述:Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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