Prognozowanie zmienności indeksu WIG20 za pomocą modeli AR-GARCH z dodatkową informacją

• Autorzy: Piotr Płuciennik

Warianty tytułu

Forecasting Volatility of WIG20 Index Using AR-GARCH Models whit Additional Information

• Języki publikacji: PL

Abstrakty

Opisywane w artykule wyniki wskazują, że zastosowanie dziennej zmienności implikowanej z opóźnieniem rzędu 1-6 dni jako dodatkowej zmiennej objaśniającej może poprawić jakość prognoz, która ze względu na duże wahania zmienności zrealizowanej w badanym okresie nie jest zbyt dobra. (fragment tekstu)

EN

Forecasting the daily volatility of financial instruments is very important issue for option pricing, risk management and portfolio management. Since the famous paper of Andersen and Bollerslev [1998], the forecasts of the volatility are usually compared with the daily realized volatility. This trend of development is possible due to the increasing availability of financial market data at intraday frequencies. On the other hand, there are strong attempts to explore the different historical data as an information source for volatility forecasting. Such source of information can be obtained from options or volume. In the paper we model and forecast the daily volatility of the stock index WIG20 using a GARCH model with such additional explanatory variables. The obtained volatility forecasts are compared with the daily realized volatility. (original abstract)

Słowa kluczowe

PL

Model GARCH; Ekonomia matematyczna; Metody ilościowe; Metody ilościowe w ekonomii; Model ARFIMA

EN

GARCH model; Mathematical economics; Quantitative methods; Quantitative methods in economics; Autoregressive fractionally integrated moving average model (ARFIMA)

• Czasopismo: Zeszyty Naukowe / Akademia Ekonomiczna w Poznaniu
• Rocznik: 2007
• Numer: nr 92
• Strony: 231--250

Twórcy

autor

Piotr Płuciennik

• Uniwersytet im. Adama Mickiewicza w Poznaniu

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