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Institute
In this paper a partial least squares (PLS) approach to dynamic modelling with latent variables is proposed. Let Y be a matrix of manifest variables and H the matrix of the corresponding latent variables. And let H = BH+ε be a structural PLS model with a coefficient matrix B. Then this model can be made a dynamic one by substituting for B a matrix F = B + CL containing the lag operator L. Then the structural dynamic model H = FH+ε is formally estimated like an ordinary PLS model. In an exploratory way the model can be used for forecasting purposes. The procedure is being programmed in ISP.
Dynamic causal links between the russian stock exchange and selected international stock markets
(2004)
Core inflation in Russia : different approaches for the period from january 1997 to april 2003
(2005)
Persistence of stock returns is an extensively studied and discussed theme in the analysis of financial markets. Antipersistence is usually attributed to volatilities. However, not only volatilities but also stock returns can exhibit antipersistence. Antipersistent noise has a somewhat rougher appearance than Gaussian noise. Heuristically spoken, price movements are more likely followed by movements in the opposite direction than in the same direction. The pertaining integrated process exhibits a smaller range – prices seem to stay in the vicinity of the initial value. We apply a widely used test based upon the modified R/S-Method by Lo [1991] to daily returns of 21 German stocks from 1960 to 2008. Combining this test with the concept of moving windows by Carbone et al. [2004], we are able to determine periods of antipersistence for some of the series under examination. Our results suggest that antipersistence can be found for stocks and periods where extraordinary corporate actions such as mergers & acquisitions or financial distress are present. These effects should be properly accounted for when choosing and designing models for inference.