Forecasting Stock Returns using a Copula-GARCH model

Seung-Hwan Lee

ISBN 10: 3659233579 / ISBN 13: 9783659233579

Published by LAP Lambert Academic Publishing Nov 2017, 2017

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 60 pp. Englisch.

Seller Inventory # 9783659233579

Bibliographic Details

• Title: Forecasting Stock Returns using a Copula-GARCH model
• Publisher: LAP Lambert Academic Publishing Nov 2017
• Publication Date: 2017
• Language: English
• ISBN 10: 3659233579
• ISBN 13: 9783659233579
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 107 grams

About this title

Synopsis

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.

About the Author

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