In an experiment, we systematically tested the risk tolerance for trading stock shares that vary in the initial
price of the shares. Persons inexperienced with the stock market had to set the selling points for 60 stocks in the
case of (a) decreasing or (b) rising prices. First, a stronger risk aversion for falling compared to rising prices was
obtained. Second, the experiment revealed a dramatic increase in risk tolerance the lower the buying prices of the
stocks were; nearly perfectly following a power function (Pearson-R’s>.93). Furthermore, it seemed very difficult for
persons to grasp the consequences of share price neglect, namely that the initial share price has a significant impact
on the readiness to take higher risks, whether in a positive or negative direction. Therefore, we are also referring to
it as a “hidden risk tolerance”. This paper offers insights into irrational decision making in trading stocks. It allows
the formation of estimates regarding trading volume and share price potential on the basis of the initial share price.Furthermore, it provides clues for the consequent reduction of risk-seeking behavior.
We present a morphological texture contrast (MTC) operator that allows detection of textural and non-texture regions in images. We show that in contrast to other approaches, the MTC discriminates between texture details and isolated features and does not extend borders of texture regions. A comparison with other methods used for texture detection is provided. Using the ideas underlying the MTC operator, we develop a complementary operator called morphological feature contrast (MFC) that allows extraction of isolated features while not being confused by texture details. We illustrate an application of the MFC operator to extraction of isolated objects such as individual trees or buildings that should be distinguished from forests or urban centers. We also propose an MFC based detector of isolated linear features and compare it with an alternative approach used for detection of edges and lines in cluttered scenes. We furthermore derive an extended version of the MFC that can be directly applied to vector-valued images.
The study considers some of the factors determining budget balance. In particular, it
investigates the relationship between budget balance and inflation. The analysis focuses on
European states in the period between 1999 and 2007, and concludes that the relationship
between budget balance and inflation is not demonstrable. In the literature, attempts to
quantify the relationship between the two factors have faced severe difficulties.
Inflation influences both the revenue side and the expenditure side of the budget, often
increasing one and reducing the other at the same time. These effects might balance each
other out, leaving the budget balance unchanged.
“While crystallized intelligence (gc) is recognized in many contemporary intelligence frameworks, there is no consensus as to the nature and contents of the construct. Originally conceptualized as capturing acquired skills and declarative knowledge in different content domains, more recent definitions and typical indicators focus on verbal ability. We investigated the relationship between verbal ability and declarative knowledge under consideration of individual differences in fluid intelligence in a large-scale assessment study with 6,701 adolescents. Structural equation modeling was used to examine the factorial distinctness of verbal ability and declarative knowledge with three analytical strategies: (i) Estimating correlations between latent variables, (ii) estimating the amount of unique variance in each factor after accounting for differences in the other ability constructs, and (iii) investigating associations with covariates including school achievement, students’ characteristics, and psychological traits. The correlation between latent variables representing verbal ability, measured with items from six language domains, and knowledge in 16 content domains was very high (ρ = .91), but significantly different from unity. About 17% of the variance in the knowledge factor was independent of individual differences in verbal ability and fluid intelligence. Associations with covariates revealed unique correlational patterns for each ability construct. The findings suggest that verbal ability and knowledge are closely related, but empirically distinguishable facets of crystallized intelligence. The discussion focuses on the construct validity of verbal tests for the measurement of gc and the interpretation of the common factor of a broad knowledge assessment as a causal variable.”