Conditional Performance Measurement Using Portfolio Weights: Evidence for Pension Funds

This paper combines the use of portfolio holdings data and conditioning information to create a new performance measure. Our conditional weight-based measure has several advantages. Using conditioning information avoids biases in weight-based measures as discussed by Grinblatt and Titman (1993). When conditioning information is used, returns-based measures face a bias if managers can trade between observation dates. The new measures avoid this interim trading bias. We use the new measures to provide fresh insights about performance in a sample of U.S. equity pension fund managers.

Potentiation of the startle reflex is in line with contingency reversal instructions rather than the conditioning history

In the context of fear conditioning, different psychophysiological measures have been related to different learning processes. Specifically, skin conductance responses (SCRs) have been related to cognitive expectancy learning, while fear potentiated startle (FPS) has been proposed to reflect affective learning that operates according to simple associative learning principles. On the basis of this two level account of fear conditioning we predicted that FPS should be less affected by verbal instructions and more affected by direct experience than SCRs. We tested this hypothesis by informing participants that contingencies would be reversed after a differential conditioning phase. Our results indicate that contingency reversal instructions led to an immediate and complete reversal of FPS regardless of the previous conditioning history. This change was accompanied by similar changes on US expectancy ratings and SCRs. These results conform with an expectancy model of fear conditioning but argue against a two level account of fear conditioning

High-temperature capacitive strain measurement system

Capacitive strain gage and signal conditioning system measures stress-induced strain and cancels thermal expansion strain at temperatures to 1,500 F (815 C). Gage does not significantly restrain or reinforce specimen

Can I use a Panel? Panel Conditioning and Attrition Bias in Panel Surveys

Over the past decades there has been an increasing use of panel surveys at the household or individual level, instead of using independent cross-sections. Panel data have important advantages, but there are also two potential drawbacks: attrition bias and panel conditioning effects. Attrition bias can arise if respondents drop out of the panel non-randomly, i.e., when attrition is correlated to a variable of interest. Panel conditioning arises if responses in one wave are in°uenced by participation in the previous wave(s). The experience of the previous interview(s) may affect the answers of respondents in a next interview on the same topic, such that their answers differ systematically from the answers of individuals who are interviewed for the first time. The literature has mainly focused on estimating attrition bias; less is known on panel conditioning effects. In this study we discuss how to disentangle the total bias in panel surveys due to attrition and panel conditioning into a panel conditioning and an attrition effect, and develop a test for panel conditioning allowing for non-random attrition. First, we consider a fully nonparametric approach without any assumptions other than those on the sample design, leading to interval identification of the measures for the attrition and panel conditioning effect. Second, we analyze the proposed measures under additional assumptions concerning the attrition process, making it possible to obtain point estimates and standard errors for both the attrition bias and the panel conditioning effect. We illustrate our method on a variety of questions from two-wave surveys conducted in a Dutch household panel. We found a significant bias due to panel conditioning in knowledge questions, but not in other types of questions. The examples show that the bounds can be informative if the attrition rate is not too high. Point estimates of the panel conditioning effect do not vary a lot with the different assumptions on the attrition process.panel conditioning;attrition bias;measurement error;panel surveys

Combining internal- and external-training-load measures in professional rugby league

Purpose: This study investigated the effect of training mode on the relationships between measures of training load in professional rugby league players. Methods: Five measures of training load (internal: individualized training impulse, session rating of perceived exertion; external—body load, high-speed distance, total impacts) were collected from 17 professional male rugby league players over the course of two 12-week pre-season periods. Training was categorized by mode (small-sided games, conditioning, skills, speed, strongman, and wrestle) and subsequently subjected to a principal component analysis. Extraction criteria were set at an eigenvalue of greater than one. Modes that extracted more than one principal component were subjected to a varimax rotation. Results: Small-sided games and conditioning extracted one principal component, explaining 68% and 52% of the variance, respectively. Skills, wrestle, strongman, and speed extracted two principal components explaining 68%, 71%, 72%, and 67% of the variance respectively. Conclusions: In certain training modes the inclusion of both internal and external training load measures explained a greater proportion of the variance than any one individual measure. This would suggest that in those training modes where two principal components were identified, the use of only a single internal or external training load measure could potentially lead to an underestimation of the training dose. Consequently, a combination of internal and external load measures is required during certain training modes