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Unspanned stochastic volatility from an empirical and practical perspective

机译:从经验和实践角度来看未扫描的随机波动

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I conduct a simulation study to address concerns raised in the empirical literature on unspanned stochastic volatility (USV, i.e., interest-rate-volatility risk that cannot be hedged with bonds or swaps). Regressions have been the popular method of identifying and measuring USV, and have led to a consensus that is in favour of USV models. Despite plausible challenges to this approach, my simulations show that regressions are able to correctly identify the presence and absence of USV. This relies on a number of methodological considerations which are inconsistent in the literature. Regression results from empirical data, from several modern interest-rate markets, resemble results from data simulated from USV models. I then assess the economic significance of USV. By comparing hedged and unhedged returns of market interest-rate options, I develop quantitative guidelines around how unspanned volatility risk compares to interest-rate risk. (C) 2020 Elsevier B.V. All rights reserved.
机译:我进行了模拟研究,以解决在未扫描随机波动率的经验文献中提出的担忧(USV,即股息 - 波动性风险,不能与债券或换回保持联系)。回归是识别和测量USV的流行方法,并导致支持USV型号的共识。尽管对这种方法具有合理的挑战,我的模拟表明回归能够正确识别USV的存在和缺失。这依赖于文献中不一致的一些方法论考虑因素。来自经验数据的回归结果来自几个现代利率市场,类似于由USV模型模拟的数据的结果。然后我评估USV的经济意义。通过比较对冲和未联合的市场利率选项的回报,我围绕悬念风险与利率风险相比,开发定量指南。 (c)2020 Elsevier B.v.保留所有权利。

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