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Are stock returns predictable?

An Empirical Investigation of the German Stock Market

Titre: Are stock returns predictable?

Thèse de Master , 2015 , 73 Pages , Note: 1,7

Autor:in: Marc Seibert (Auteur)

Gestion d'entreprise - Banque, Bourse, Assurance
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Résumé Résumé des informations

Can stock returns be predicted? This master's thesis investigates the question empirically for the German stock market. Using monthly price data for all DAX constituents from 1983 to 2013, it develops and tests its own forecasting models: a multivariate regression based on micro- and macroeconomic variables (P/E ratio, EPS, credit spread, oil price, GDP and others), an ARMA time-series model and a naive benchmark. The complete methodology is demonstrated using the BASF share, with forecasting quality assessed through in-sample and out-of-sample tests via RMSE, MAE and MAPE.

The study first provides a solid grounding in the theoretical foundations — capital market efficiency, portfolio management, technical and fundamental analysis — together with a comprehensive literature review. The findings are as honest as they are insightful: over the long run, returns can be approximately explained by a few economic factors, while in the short run the market remains largely unpredictable. Essential reading for economics and finance students, analysts and anyone interested in quantitative equity valuation.

Résumé des informations

Titre
Are stock returns predictable?
Sous-titre
An Empirical Investigation of the German Stock Market
Université
Justus-Liebig-University Giessen  (Uni)
Cours
Thesis
Note
1,7
Auteur
Marc Seibert (Auteur)
Année de publication
2015
Pages
73
N° de catalogue
V1737281
ISBN (PDF)
9783389196311
ISBN (Livre)
9783389196328
Langue
anglais
mots-clé
stock return predictability market efficiency random walk DAX ARMA model multivariate regression technical analysis fundamental analysis behavioral finance
Sécurité des produits
GRIN Publishing GmbH
Citation du texte
Marc Seibert (Auteur), 2015, Are stock returns predictable?, Munich, GRIN Verlag, https://www.grin.com/document/1737281
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