Know Your Clients' behaviours: a cluster analysis of financial transactions

In Canada, financial advisors and dealers are required by provincial securities commissions and self-regulatory organizations--charged with direct regulation over investment dealers and mutual fund dealers--to respectively collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts. With this information, investors, under their advisor's guidance, make decisions on their investments which are presumed to be beneficial to their investment goals. Our unique dataset is provided by a financial investment dealer with over 50,000 accounts for over 23,000 clients. We use a modified behavioural finance recency, frequency, monetary model for engineering features that quantify investor behaviours, and machine learning clustering algorithms to find groups of investors that behave similarly. We show that the KYC information collected does not explain client behaviours, whereas trade and transaction frequency and volume are most informative. We believe the results shown herein encourage financial regulators and advisors to use more advanced metrics to better understand and predict investor behaviours.Comment: 38 pages, 12 figure

Goal importance, self-focus and the goal setting process

In this study we examine the role played by perceived goal importance and self-focus in the goal-setting process. More specifically, this study tests the interactive hypotheses that (a) task performance is a function of goal level, self-focus, and perceived goal importance; (b) goal level is a function of perceptions of past performance, self-focus, and perceived goal importance; and (c) perceptions of past performance are a function of actual past performance, self-focus, and perceived goal importance. Hierarchical regression analysis, using a sample of 88 retail salespersons, revealed empirical support for the first two hypotheses. Specifically, the variables described by control theory account for an increment of 6 and 8% of the variance explained in task performance and self-set goal level, respectively. Finally, implications for theory, practice, and future research are discussed

Where all the Children are Above Average: A Meta analysis of the Performance Appraisal Purpose Affect

More than 40 years ago, Taylor and Wherry (1951) hypothesized that performance appraisal ratings obtained for administrative purposes, such as pay raises or promotions, would be more lenient than ratings obtained for research, feedback, or employee development purposes. However, research on appraisal purpose has yielded inconsistent results, with roughly half of such studies supporting this hypothesis and the other half refuting it. To account for those differences, a meta-analysis of performance appraisal purpose research was conducted with 22 studies and a total sample size of 57,775. Our results support Taylor and Wherry\u27s hypothesis as performance evaluations obtained for administrative purposes were, on average, one-third of a standard deviation larger than those obtained for research or employee development purposes. In addition, moderator analysis indicated larger differences between ratings obtained for administrative and research purposes when performance evaluations were made in field settings, by practicing managers, and for real world subordinates. Implications for researchers and practitioners are discussed

Turnover functionality versus turnover frequency: A note on work attitudes and organizational effectiveness

Tested whether work attitudes, widely praised as predictors of turnover frequency (i.e., the number of separations), are also useful predictors of turnover functionality (i.e., the nature of separations). Measures on job satisfaction, organizational commitment, job involvement, motivation to turnover, and turnover frequency and functionality were obtained from 112 retail salespersons. Results indicate that (a) the traditional measure of turnover frequency overstates the detrimental effects of turnover on organizational effectiveness, in that 53% of the turnover was functional and (b) turnover functionality, which emphasizes the performance levels of stayers and leavers, is unrelated to work attitudes. Findings suggest that organizations should not devote resources to programs designed to improve employee attitudes, based solely on the expectation that decreasing turnover frequency will result in beneficial consequences

Soliton Turbulence in Shallow Water Ocean Surface Waves

We analyze shallow water wind waves in Currituck Sound, North Carolina and experimentally confirm, for the first time, the presence of $soliton$ $turbulence$ in ocean waves. Soliton turbulence is an exotic form of nonlinear wave motion where low frequency energy may also be viewed as a $dense$ $soliton$ $gas$, described theoretically by the soliton limit of the Korteweg-deVries (KdV) equation, a $completely$ $integrable$ $soliton$ $system$: Hence the phrase "soliton turbulence" is synonymous with "integrable soliton turbulence." For periodic/quasiperiodic boundary conditions the $ergodic$ $solutions$ of KdV are exactly solvable by $finite$ $gap$ $theory$ (FGT), the basis of our data analysis. We find that large amplitude measured wave trains near the energetic peak of a storm have low frequency power spectra that behave as $\sim\omega^{-1}$. We use the linear Fourier transform to estimate this power law from the power spectrum and to filter $densely$ $packed$ $soliton$ $wave$ $trains$ from the data. We apply FGT to determine the $soliton$ $spectrum$ and find that the low frequency $\sim\omega^{-1}$ region is $soliton$ $dominated$. The solitons have $random$ $FGT$ $phases$, a $soliton$ $random$ $phase$ $approximation$, which supports our interpretation of the data as soliton turbulence. From the $probability$ $density$ $of$ $the$ $solitons$ we are able to demonstrate that the solitons are $dense$ $in$ $time$ and $highly$ $non$ $Gaussian$.Comment: 4 pages, 7 figure

Recruiting Sources and Posthire Outcomes for Job Applicants and New Hires: A Test of Two Hypotheses

This study, unlike most recruitment source research, tested for and ruled out the contaminating effects of prescreening and self-selection bias by examining applicants and new hires for nursing positions (S. L. Rynes and A. E. Barber, 1990). Consistent with the predictions of A. Rees (1966) and J. C. Ullman (1966), recruitment sources reached differently qualified applicants in terms of nursing experience and education which, in turn, were valid predictors of subsequent nurse performance. In a similar manner, recruitment sources produced sharply different levels of prehire knowledge, which was inversely related to voluntary turnover after 1 yr. However, contrary to both hypotheses, prehire knowledge, education, and experience did not mediate the relationship between recruitment sources and posthire outcomes. Recruitment sources with greater prehire knowledge did not always result in lower voluntary turnover. Likewise, despite recruitment source differences in nursing experience and education, recruitment sources were not related to nursing performance. Finally, the extent to which applicants use multiple recruitment sources was investigated, and the methodological problem that this creates for recruitment source research was discussed

Correcting turnover correlations: A critique

In this article, the authors argue that turnover correlations do not need to be corrected. First, they maintain that correction formulas cannot correct for poor construct validity. Second, they discuss the original purposes of turnover correction formulas. Third, the authors describe the logical fallacies of correcting turnover correlations. Finally, they show why turnover correlations are not, as is widely believed, statistically limited to a maximum of .80

The Software Required for the Computer Generation of Virtual Environments

Presence, Vol. 2, No. 2, pp. 130-140..Accepted/Published Paper (Refereed

Dynamical Mean-Field Theory within the Full-Potential Methods: Electronic structure of Ce-115 materials

We implemented the charge self-consistent combination of Density Functional Theory and Dynamical Mean Field Theory (DMFT) in two full-potential methods, the Augmented Plane Wave and the Linear Muffin-Tin Orbital methods. We categorize the commonly used projection methods in terms of the causality of the resulting DMFT equations and the amount of partial spectral weight retained. The detailed flow of the Dynamical Mean Field algorithm is described, including the computation of response functions such as transport coefficients. We discuss the implementation of the impurity solvers based on hybridization expansion and an analytic continuation method for self-energy. We also derive the formalism for the bold continuous time quantum Monte Carlo method. We test our method on a classic problem in strongly correlated physics, the isostructural transition in Ce metal. We apply our method to the class of heavy fermion materials CeIrIn_5, CeCoIn_5 and CeRhIn_5 and show that the Ce 4f electrons are more localized in CeRhIn_5 than in the other two, a result corroborated by experiment. We show that CeIrIn_5 is the most itinerant and has a very anisotropic hybridization, pointing mostly towards the out-of-plane In atoms. In CeRhIn_5 we stabilized the antiferromagnetic DMFT solution below 3K, in close agreement with the experimental N\'eel temperature.Comment: The implementation of Bold-CTQMC added and some test of the method adde