Forecasting Stock Returns using a Copula-GARCH model - Eun-Joo Lee,Jonathan Vlk,Seung-Hwan Lee
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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 volatilit ... Full description
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Description
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.
More Information
| Author | Eun-Joo Lee, Jonathan Vlk, Seung-Hwan Lee |
|---|---|
| Publisher | LAP Lambert Academic Publishing |
| Release year | 2017 |
| Cover type | Softcover |
| EAN | 9783659233579 |