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首页> 外文期刊>The North American journal of economics and finance >Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options
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Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options

机译：使用马尔可夫切换多分形模型预测波动率：来自标普100指数和股票期权的证据

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摘要

In this paper, we evaluate the performance of the ability of Markov-switching multifractal (MSM), implied, GARCH, and historical volatilities to predict realized volatility for both the S&P 100 index and equity options. Some important findings are as follows. First, we find that the ability of MSM and GARCH volatilities to predict realized volatility is better than that of implied and historical volatilities for both the index and equity options. Second, equity option volatility is more difficult to be forecast than index option volatility. Third, both index and equity option volatilities can be better forecast during non-global financial crisis periods than during global financial crisis periods. Fourth, equity option volatility exhibits distinct patterns conditional on various equity and option characteristics and its predictability by MSM and implied volatilities depends on these characteristics. And finally, we find that MSM volatility outperforms implied volatility in predicting equity option volatility conditional on various equity and option characteristics.
机译：在本文中，我们评估了马尔可夫转换多重分形（MSM），隐含，GARCH和历史波动率预测标准普尔100指数和股票期权的实际波动率的能力。一些重要的发现如下。首先，我们发现对于指数期权和股票期权，MSM和GARCH波动率预测已实现波动率的能力优于隐含波动率和历史波动率。其次，股票期权的波动性比指数期权的波动性更难预测。第三，与全球金融危机时期相比，在非全球金融危机时期可以更好地预测指数波动率和股票期权波动率。第四，股票期权的波动性表现出不同的模式，其条件取决于各种股票和期权的特征，MSM和隐含波动率的可预测性取决于这些特征。最后，我们发现MSM的波动率在隐含的波动率方面要优于隐含的波动率，这些波动率是在预测各种股权和期权特征的情况下进行的。

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