scholarly journals Mimicking Portfolios with Conditioning Information

2006 ◽  
Vol 41 (3) ◽  
pp. 607-635 ◽  
Author(s):  
Wayne Ferson ◽  
Andrew F. Siegel ◽  
Pisun (Tracy) Xu

AbstractMimicking portfolios have long been useful in asset pricing research. In most empirical applications, the portfolio weights are assumed to be fixed over time, while in theory they may be functions of the economic state. This paper derives and characterizes mimicking portfolios in the presence of predetermined state variables, or conditioning information. The results generalize and integrate multifactor minimum variance efficiency (Fama (1996)) with conditional and unconditional mean-variance efficiency (Hansen and Richard (1987), Ferson and Siegel (2001)). Empirical examples illustrate the potential importance of time-varying mimicking portfolio weights and highlight challenges in their application.

Author(s):  
Chikashi Tsuji

After the recent US and international related literature review, this paper explores the state variables that are priced in the Intertemporal Capital Asset Pricing Model (ICAPM) in Japan. Deriving the time-varying covariance risks by using the multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, we analyze the ICAPM in the Tokyo Stock Exchange. Our empirical examinations clarify that in Japan, the time-varying covariance between the first difference of the seasonally adjusted Consumer Price Index and market return and the time-varying covariance between the first difference of the trading volume divided by Japanese Gross Domestic Product and market return are priced in Merton’s ICAPM. Further, we discuss the prospect for asset pricing and accounting research by reviewing the recent combined studies.


Author(s):  
José Novoa ◽  
Jorge Wuth ◽  
Juan Pablo Escudero ◽  
Josué Fredes ◽  
Rodrigo Mahu ◽  
...  

2018 ◽  
Vol 5 (3) ◽  
pp. 1322-1334 ◽  
Author(s):  
Philip E. Pare ◽  
Carolyn L. Beck ◽  
Angelia Nedic

2020 ◽  
pp. 107754632098244
Author(s):  
Hamid Razmjooei ◽  
Mohammad Hossein Shafiei ◽  
Elahe Abdi ◽  
Chenguang Yang

In this article, an innovative technique to design a robust finite-time state feedback controller for a class of uncertain robotic manipulators is proposed. This controller aims to converge the state variables of the system to a small bound around the origin in a finite time. The main innovation of this article is transforming the model of an uncertain robotic manipulator into a new time-varying form to achieve the finite-time boundedness criteria using asymptotic stability methods. First, based on prior knowledge about the upper bound of uncertainties and disturbances, an innovative finite-time sliding mode controller is designed. Then, the innovative finite-time sliding mode controller is developed for finite-time tracking of time-varying reference signals by the outputs of the system. Finally, the efficiency of the proposed control laws is illustrated for serial robotic manipulators with any number of links through numerical simulations, and it is compared with the nonsingular terminal sliding mode control method as one of the most powerful finite-time techniques.


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