scholarly journals Fitting dynamic factor models to non-stationary time series

2011 ◽  
Vol 163 (1) ◽  
pp. 51-70 ◽  
Author(s):  
Michael Eichler ◽  
Giovanni Motta ◽  
Rainer von Sachs
Keyword(s):  
Time Series ◽  
Factor Models ◽  
Stationary Time Series ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Stationary Time

Rotation in the dynamic factor modeling of multivariate stationary time series

Psychometrika ◽  
2001 ◽  
Vol 66 (1) ◽  
pp. 99-107 ◽  
Author(s):  
Peter C. M. Molenaar ◽  
John R. Nesselroade
Keyword(s):  
Time Series ◽  
Stationary Time Series ◽  
Dynamic Factor ◽  
Stationary Time ◽  
Factor Modeling

An empirical testing of comparative efficiency of static and dynamic factor models towards stock returns’ predictability in capital market of Pakistan

2020 ◽  
Vol 4 (2) ◽  
pp. 141-162
Author(s):  
Laila Taskeen Qazi ◽  
Atta ur Rahman ◽  
Shahid Ali ◽  
Sohail Alam
Keyword(s):  
Time Series ◽  
Stock Returns ◽  
Time Series Data ◽  
Factor Model ◽  
Efficient Market Hypothesis ◽  
Factor Models ◽  
Series Data ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Returns Predictability

Efficient Market Hypothesis has its supporters and critics as it has invited significant attention of research scholarship in recent years. The taxonomy and existence of this hypothesis is widely debated in terms of making economic decisions in the capital markets. Stock returns predictability has galvanized researchers to use forecasting models. Literature shows that forecasting is possible yet it debates problems associated with the techniques used for forecasting from the time series data. The study relies on stock returns for 67 randomly selected companies listed on the Pakistan Stock Exchange. The static and the dynamic factor models are compared in terms of forecast efficiency. The study also uses eight macroeconomic variables to forecast stock returns by including gold prices, crude oil prices, market capitalization, PSX- 100 index, PSX-100 index turnover, KIBOR 1-month rates, KIBOR 3 years rates and Rupee to Dollar rates. The results of the hit rates and out-of-sample forecasting technique suggest that dynamic factor model is the best multivariate time series forecasting model in the Pakistani context.

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