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Więcej informacji o Forecasting Stock Returns using a Copula-GARCH model

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Opis

Investigating dependence structures of stocks that are related to one another should be an important consideration in managing a stock portfolio, among other investment strategies. To capture various dependence features, we employ copula. Financial time series data is typically characterized by volatility clustering of returns that influences an estimate of a stock's future price. To deal with the volatility and dependence of stock returns, this book provides procedures of combining a copula with a GARCH model. Using the copula-GARCH approach that describes the tail dependences of stock returns, we carry out Monte Carlo simulations to predict a company's movements in the stock market. The procedures are illustrated in two technology stocks, Apple and Samsung.

Szczegóły książki

• Pełny tytuł: Forecasting Stock Returns using a Copula-GARCH model
• Autor: Seung-Hwan Lee, Jonathan Vlk, Eun-Joo Lee
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 60
• EAN: 9783659233579
• ID: 18624999
• Wydawca: LAP Lambert Academic Publishing
• Waga: 107 g
• Wymiary: 220 × 150 × 5 mm
• Rok wydania: 2017

Ulubione w innej kategorii

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