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Intraday volatility forecasting from implied volatility

机译:从隐含波动率预测日内波动率

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Purpose - The purpose of this paper is to examine whether the superiority of the implied volatility from a stochastic volatility model over the implied volatility from the Black and Scholes model on the forecasting performance of future realized volatility still holds when intraday data are analyzed. Design/methodology/approach - Two implied volatilities and a realized volatility on KOSPI200 index options are estimated every hour. The grander causality tests between an implied volatility and a realized volatility is carried out for checking the forecasting performance. A dummy variable is added to the grander causality test to examine the change of the forecasting performance when a specific environment is chosen. A trading simulation is conducted to check the economic value of the forecasting performance. Findings - Contrary to the previous studies, the implied volatility from a stochastic volatility model is not superior to that from the Black and Scholes model for the intraday volatility forecasting even if both implied volatilities are informative on one hour ahead future volatility. The forecasting performances of both implied volatilities are improved under high volatile market or low return market. Practical implications - The trading strategy using the forecasting power of an implied volatility earns positively, in particular, more positively under high volatile market or low return market. However, it looks risky to follow the trading strategy because the performance is too volatile. Between two implied volatilities, it is hardly to say that one implied volatility beats another in terms of the economic value. Originality/value - This is the first study which shows the forecasting performances of implied volatilities on the intraday future volatility.
机译:目的-本文的目的是检验当分析当日数据时,随机波动率模型的隐含波动率与布莱克和斯科尔斯模型的隐含波动率在未来实现波动率的预测性能上的优势是否仍然存在。设计/方法/方法-每小时估计KOSPI200指数期权的两个隐含波动率和已实现波动率。在隐含波动率和实际波动率之间进行了较大的因果关系检验,以检查预测性能。在选择特定环境时,将虚拟变量添加到更广泛的因果关系检验中,以检查预测性能的变化。进行交易模拟以检查预测绩效的经济价值。研究结果-与以前的研究相反,对于日内波动率预测,随机波动率模型的隐含波动率并不优于Black and Scholes模型的隐含波动率,即使这两种隐含波动率在未来一小时内都具有参考价值。在高波动市场或低收益市场下,两种隐含波动率的预测性能均得到改善。实际意义-使用隐含波动率的预测能力的交易策略可带来积极的收益,尤其是在高波动性市场或低回报市场下,收益更为可观。但是,由于性能波动太大,因此遵循交易策略似乎很冒险。在两个隐含波动率之间,很难说一个隐含波动率在经济价值方面胜过另一个隐含波动率。独创性/价值-这是第一项研究,显示了隐含波动率对日内未来波动率的预测表现。

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