|Appears in Collections:||Accounting and Finance Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Time-Varying Predictability for Stock Returns, Dividend Growth and Consumption Growth|
asset price movement
|Citation:||McMillan D (2015) Time-Varying Predictability for Stock Returns, Dividend Growth and Consumption Growth. International Journal of Finance and Economics, 20 (4), pp. 362-373. https://doi.org/10.1002/ijfe.1522|
|Abstract:||Using a state-space model, this paper examines time variation in the predictive regressions for stock returns, dividend growth and consumption growth. Moreover, we linked time variation explicitly to movements in economic factors that can account for risk and cash flow. Results support the view that stock return predictability is enhanced when risk is high (negative growth, higher volatility and positive growth/return covariance). In contrast, dividend growth and consumption growth predictability is enhanced during economic expansions. These results are supported by subsample analysis and a vector autoregressive approach. Furthermore, these latter exercises may uncover differences in the stock return predictability relationship when viewed over different time horizons. Overall, the paper contributes to the literature by highlighting the different nature of returns predictability, which arises largely through the risk channel, and dividend and consumption growth predictability, which arise through the cash flow channel.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|McMillan-2015-International_Journal_of_Finance__Economics.pdf||Fulltext - Published Version||318.11 kB||Adobe PDF||Under Embargo until 2999-12-02 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/
If you believe that any material held in STORRE infringes copyright, please contact email@example.com providing details and we will remove the Work from public display in STORRE and investigate your claim.