کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
958345 | 1478830 | 2016 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The usefulness of cross-sectional dispersion for forecasting aggregate stock price volatility
ترجمه فارسی عنوان
سودمندی پراکندگی مقطعی برای پیش بینی نرخ نوسان قیمت سهام
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
اقتصاد، اقتصادسنجی و امور مالی
اقتصاد و اقتصادسنجی
چکیده انگلیسی
Does cross-sectional dispersion in the returns of different stocks help forecast volatility of the S&P 500 index? This paper develops a model of stock returns where dispersion in returns across different stocks is modeled jointly with aggregate volatility. Although specifications that allow for feedback from cross-sectional dispersion to aggregate volatility have a better fit in sample, they prove not to be robust for purposes of out-of-sample forecasting. Using a full cross-section of stock returns jointly, however, I find that use of cross-sectional dispersion can help improve parameter estimates of a GARCH process for aggregate volatility to generate better forecasts both in sample and out of sample. Given this evidence, I conclude that cross-sectional information helps predict market volatility indirectly rather than directly entering in the data-generating process.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Empirical Finance - Volume 36, March 2016, Pages 162-180
Journal: Journal of Empirical Finance - Volume 36, March 2016, Pages 162-180
نویسندگان
Sung Je Byun,