МОДЕЛИРОВАНИЯ ВРЕМЕННЫХ РЯДОВ ЛОКАЛЬНОЙ ВОЛАТИЛЬНОСТИ" В ДЕНЬГАХ"(АТМ) ДЛЯ АКЦИЙ MICROSOFT
V Bondarenko, M Bondarenko - SWorldJournal, 2021 - sworldjournal.com
V Bondarenko, M Bondarenko
SWorldJournal, 2021•sworldjournal.comUntitled Page 1 Page 2 Page 3 SWorldJournal Issue 7 / Part 2 ISSN 2663-5712 www.sworldjournal.com
107 Our term structure corresponds to calibration dates from Table 1 and Table 2. Table 1
Cross validation dataset Calibration Dates 01/03/ 2020 01/10/ 2020 01/24/ 2020 01/31/ 2020
02/07/ 2020 Validation dates (OOS) 01/17/ 2020 02/14/ 2020 02/21/ 2020 Spot MSFT 158.62
00 161.34 00 167.10 00 165.04 00 170.23 00 183.89 00 185.35 00 178.59 00 Calibration
Dates 02/28/ 2020 03/06/ 2020 03/20/ 2020 03/27/ 2020 04/03/ 2020 Validation dates (OOS) …
107 Our term structure corresponds to calibration dates from Table 1 and Table 2. Table 1
Cross validation dataset Calibration Dates 01/03/ 2020 01/10/ 2020 01/24/ 2020 01/31/ 2020
02/07/ 2020 Validation dates (OOS) 01/17/ 2020 02/14/ 2020 02/21/ 2020 Spot MSFT 158.62
00 161.34 00 167.10 00 165.04 00 170.23 00 183.89 00 185.35 00 178.59 00 Calibration
Dates 02/28/ 2020 03/06/ 2020 03/20/ 2020 03/27/ 2020 04/03/ 2020 Validation dates (OOS) …
Abstract
In this work we apply simple linear and polynomial regression to model the time series of at-the-money (ATM) local volatility of Microsoft stocks and predict its out-of-sample values. Multiple researches consider ATM local volatility to be a good measure
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