基于波动率预测的VIX交易:又一个波动率之谜?

IF 3.4 3区 经济学 Q1 ECONOMICS
Stavros Degiannakis, Panagiotis Delis, George Filis, George Giannopoulos
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引用次数: 0

摘要

本研究基于股票市场隐含波动率预测改善短期交易决策过程的能力,评估其经济效用。目前的文献将预测范围与交易决策的频率对齐,以评估不同的预测框架。相比之下,我们的论文的前提是,这些不应该是必然相关的,而是评估应该基于最终用户的实际需求。因此,我们评估多天前股市波动率预测与-à-vis 1天前预测是否可以提高VIX和标普500期货的1天前交易利润。我们的研究结果表明,当交易决策基于长期波动预测时,1天前的交易利润确实显著提高。更具体地说,最高的交易收益是在使用22天的预测时获得的。这一结果适用于VIX指数和标普500指数期货的日内交易。虽然没有理论背景表明预测和交易不应该一致,但从统计和财务的角度来看,我们强烈地激发了这个潜在的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trading VIX on Volatility Forecasts: Another Volatility Puzzle?

This study evaluates the economic usefulness of stock market implied volatility forecasts, based on their ability to improve the short-run trading decision-making process. The current literature aligns the forecast horizon with the frequency of the trading decision in order to evaluate different forecasting frameworks. By contrast, the premise of our paper is that these should not be necessarily related, but rather the evaluation should be based on the actual needs of the end-user. Thus, we evaluate whether the multiple days ahead stock market volatility forecasts vis-à-vis the 1-day ahead forecasts can improve the 1-day ahead trading profits from VIX and the S&P500 futures. Our results suggest that indeed the 1-day ahead trading profits are significantly improved when the trading decisions are based on longer term volatility forecasts. More specifically, the highest trading gains are obtained when using the 22-day ahead forecasts. The results hold true for both VIX and S&P500 futures day-ahead trading. Although there is no theoretical background regarding the fact that forecasting and trading horizons should not be aligned, we strongly motivate this potential issue, both from the statistical and financial points of view.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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