Abstract
Time series regression techniques are widely used in the analysis of financial data and for estimating and testing models for asset prices and returns like the capital asset pricing model and the arbitrage pricing model. They are used to uncover and exploit predictive relationships between financial variables. For example, the predictability of asset returns using valuation ratios like dividend/price, earnings/price and book/market is usually established using time series regression techniques, and the resulting regression models are used to forecast future returns. Time series regression techniques are also used for testing the informational efficiency of financial markets. Market efficiency often implies that certain financial variables should not be predictable based on observable information, and time series regression techniques may be used to verify efficiency implications.
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(2006). Time Series Regression Modeling. In: Modeling Financial Time Series with S-PLUS®. Springer, New York, NY. https://doi.org/10.1007/978-0-387-32348-0_6
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DOI: https://doi.org/10.1007/978-0-387-32348-0_6
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