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首页> 外文期刊>Journal of Emerging Market Finance >On the Relationship of Ex-ante and Ex-post Volatility: A Sub-period Analysis of S&P CNX Nifty Index Options
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On the Relationship of Ex-ante and Ex-post Volatility: A Sub-period Analysis of S&P CNX Nifty Index Options

机译:事前与事后波动之间的关系:标准普尔CNX漂亮指数期权的亚周期分析

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摘要

In this article, the information content of implied volatility is studied at sub-periods (i.e., pre- and post-crises of 2007-09). The main objective is to judge the predictive power of implied volatility in the pre- and post-crises period, using at-the-money (ATM) non-overlapping monthly implied volatilities of Nifty Index options. A simple ordinary least squares (OLS) estimation is used to analyse the information content of implied volatility in sub-periods. An autoregressive-moving average (ARMA) structure is analysed for the assessment of times series property of ex-ante and ex-post volatility. An autoregressive distributed lag (ARDL) model is adopted to choose the most advantageous forecasting model for predicting the future volatility. The OLS estimation shows that implied volatility is more biased in the pre-crises period. The two-stage least squares (2SLS) estimation clearly explains that implied volatility is an unbiased estimate of the future realised volatility. An ARMA (1,1) and ARDL (1,0) is the best model of future volatility estimation. This study explains that for Indian derivative market, volatility estimates based on options are useful for the pricing of derivative instruments and portfolio risk management.
机译:在本文中,隐含波动率的信息内容在以下子时段(即2007-09年危机前后)进行了研究。主要目的是使用Nifty Index期权的现价(ATM)非重叠每月隐含波动率来判断危机前后隐含波动率的预测能力。一个简单的普通最小二乘(OLS)估计用于分析子周期内隐含波动率的信息内容。分析了自回归移动平均值(ARMA)结构,以评估事前和事后波动率的时间序列特性。采用自回归分布滞后(ARDL)模型来选择最有利的预测模型来预测未来的波动率。 OLS估计表明,隐含波动率在危机前时期更为偏向。两阶段最小二乘(2SLS)估计清楚地说明了隐含波动率是对未来实现波动率的无偏估计。 ARMA(1,1)和ARDL(1,0)是未来波动率估计的最佳模型。这项研究解释说,对于印度衍生品市场,基于期权的波动率估计对于衍生工具的定价和投资组合风险管理很有用。

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