Stavros Degiannakis, Panagiotis Delis, George Filis, George Giannopoulos
{"title":"基于波动率预测的VIX交易:又一个波动率之谜?","authors":"Stavros Degiannakis, Panagiotis Delis, George Filis, George Giannopoulos","doi":"10.1002/for.3257","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>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.</p>\n </div>","PeriodicalId":47835,"journal":{"name":"Journal of Forecasting","volume":"44 4","pages":"1602-1618"},"PeriodicalIF":3.4000,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trading VIX on Volatility Forecasts: Another Volatility Puzzle?\",\"authors\":\"Stavros Degiannakis, Panagiotis Delis, George Filis, George Giannopoulos\",\"doi\":\"10.1002/for.3257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>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.</p>\\n </div>\",\"PeriodicalId\":47835,\"journal\":{\"name\":\"Journal of Forecasting\",\"volume\":\"44 4\",\"pages\":\"1602-1618\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forecasting\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/for.3257\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/for.3257","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
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.
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.