Forecasting the size premium over different time horizons

被引:9
|
作者
Zakamulin, Valeriy [1 ]
机构
[1] Univ Agder, Fac Econ & Social Sci, N-4604 Kristiansand, Norway
关键词
Size effect; Size premium; Stock return predictability; Active alpha; EXPECTED STOCK RETURNS; CROSS-SECTION; REAL ACTIVITY; PREDICTING RETURNS; EQUITY RETURNS; TERM STRUCTURE; MARKET; INFLATION; PERFORMANCE; RISK;
D O I
10.1016/j.jbankfin.2012.11.006
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
In this paper, we provide evidence that the small stock premium is predictable both in-sample and out-of-sample through the use of a set of lagged macroeconomic variables. We find that it is possible to forecast the size premium over time horizons that range from one month to one year. We demonstrate that the predictability of the size premium allows a portfolio manager to generate an economically and statistically significant active alpha. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:1061 / 1072
页数:12
相关论文
共 50 条
  • [41] Different Forecasting Horizons Based Performance Analysis of Electricity Load Forecasting Using Multilayer Perceptron Neural Network
    Madhiarasan, Manogaran
    Louzazni, Mohamed
    [J]. FORECASTING, 2021, 3 (04): : 804 - 838
  • [42] HOW DO LESS ADVANCED FORECASTING METHODS PERFORM ON WEEKLY REVPAR IN DIFFERENT FORECASTING HORIZONS FOLLOWING THE RECESSION?
    Zheng, Tianshu
    Bloom, Barry
    Wang, Xiaofan
    Schrier, Thomas
    [J]. TOURISM ANALYSIS, 2012, 17 (04): : 459 - 472
  • [43] Forecasting the Equity Premium: Mind the News!
    Adaemmer, Philipp
    Schuessler, Rainer A.
    [J]. REVIEW OF FINANCE, 2020, 24 (06) : 1313 - 1355
  • [44] Mixture Models for Improved Earthquake Forecasting with Short-to-Medium Time Horizons
    Rhoades, David A.
    [J]. BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA, 2013, 103 (04) : 2203 - 2215
  • [45] Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons
    Zaher Mundher Yaseen
    Minglei Fu
    Chen Wang
    Wan Hanna Melini Wan Mohtar
    Ravinesh C. Deo
    Ahmed El-shafie
    [J]. Water Resources Management, 2018, 32 : 1883 - 1899
  • [46] Constructing dynamic treatment regimes over indefinite time horizons
    Ertefaie, Ashkan
    Strawderman, Robert L.
    [J]. BIOMETRIKA, 2018, 105 (04) : 963 - 977
  • [47] Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons
    Yaseen, Zaher Mundher
    Fu, Minglei
    Wang, Chen
    Mohtar, Wan Hanna Melini Wan
    Deo, Ravinesh C.
    El-shafie, Ahmed
    [J]. WATER RESOURCES MANAGEMENT, 2018, 32 (05) : 1883 - 1899
  • [48] Influencing Opinions of Heterogeneous Populations over Finite Time Horizons
    Saxena, Arunabh
    Kumar, Bhumesh
    Gupta, Anmol
    Sahasrabudhe, Neeraja
    Moharir, Sharayu
    [J]. 2021 INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS & NETWORKS (COMSNETS), 2021, : 474 - 482
  • [49] Resource allocation for epidemic control over short time horizons
    Zaric, GS
    Brandeau, ML
    [J]. MATHEMATICAL BIOSCIENCES, 2001, 171 (01) : 33 - 58