scholarly journals Asset Performance Evaluation with the Mean-Variance Ratio

2011 ◽  
Author(s):  
Zhidong Bai ◽  
Keyan Wang ◽  
Wing-Keung Wong ◽  
Kok Fai Phoon



Author(s):  
Kerry E. Back

The CAPM and factor models in general are explained. Factors can be replaced by the returns or excess returns that are maximally correlated (the projections of the factors). A factor model is equivalent to an affine representation of an SDF and to spanning a return on the mean‐variance frontier. The use of alphas for performance evaluation is explained. Statistical factor models are defined as models in which factors explain the covariance matrix of returns. A proof is given of the Arbitrage Pricing Theory, which states that statistical factors are approximate pricing factors. The CAPM and the Fama‐French‐Carhart model are evaluated relative to portfolios based on sorts on size, book‐to‐market, and momentum.



2012 ◽  
Author(s):  
Fabian Irek ◽  
Thorsten Lehnert
Keyword(s):  
The Mean ◽  


2013 ◽  
Vol 20 (5) ◽  
pp. 415-449 ◽  
Author(s):  
S. T. Tse ◽  
P. A. Forsyth ◽  
J. S. Kennedy ◽  
H. Windcliff




2013 ◽  
Vol 110 (3) ◽  
pp. 621-639 ◽  
Author(s):  
Bryan M. Krause ◽  
Matthew I. Banks

The neural mechanisms of sensory responses recorded from the scalp or cortical surface remain controversial. Evoked vs. induced response components (i.e., changes in mean vs. variance) are associated with bottom-up vs. top-down processing, but trial-by-trial response variability can confound this interpretation. Phase reset of ongoing oscillations has also been postulated to contribute to sensory responses. In this article, we present evidence that responses under passive listening conditions are dominated by variable evoked response components. We measured the mean, variance, and phase of complex time-frequency coefficients of epidurally recorded responses to acoustic stimuli in rats. During the stimulus, changes in mean, variance, and phase tended to co-occur. After the stimulus, there was a small, low-frequency offset response in the mean and modest, prolonged desynchronization in the alpha band. Simulations showed that trial-by-trial variability in the mean can account for most of the variance and phase changes observed during the stimulus. This variability was state dependent, with smallest variability during periods of greatest arousal. Our data suggest that cortical responses to auditory stimuli reflect variable inputs to the cortical network. These analyses suggest that caution should be exercised when interpreting variance and phase changes in terms of top-down cortical processing.



2012 ◽  
Author(s):  
Wing-Keung Wong ◽  
Yongchang Hui ◽  
Zhidong Bai


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