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Forecasting Stock Returns using a Copula-GARCH model

Erschienen am 07.11.2017, 1. Auflage 2017
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Bibliografische Daten
ISBN/EAN: 9783659233579
Sprache: Englisch
Umfang: 60 S.
Format (T/L/B): 0.5 x 22 x 15 cm
Einband: kartoniertes Buch

Beschreibung

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 stocks 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 companys movements in the stock market. The procedures are illustrated in two technology stocks, Apple and Samsung.

Autorenportrait

Seung-Hwan Lee - Associate Professor. Department of Mathematics. Illinois Wesleyan University, Bloomington.