Do long-tailed macaques (Macaca fascicularis) know what others can and cannot hear?

Theory of mind has been defined as the ability to attribute mental sates such as perceptions, knowledge, and belief to others. Studies examining theory of mind in primates have been the center of intense controversy. Much of the research on this subject has focused on designing methodologies to test a primate’s ability to discern the perceptions of others. Namely, many studies have examined an individual’s knowledge of what others can and cannot see. However, other sensory modalities have not undergone as much extensive research. This study aimed to replicate the methodology of a previous experiment with the addition of two novel experimental conditions. Individual long-tailed macaques (Macaca fascicularis) were allowed to approach one of two identical, lidded, clear boxes which had jingle bells attached to them. One of the boxes had the metal bits removed from inside of the jingle bells attached to it, thus creating one “silent” box and leaving the remaining one “noisy”. The experimenter either looked directly at the subject, down at the ground between their knees, or in the novel conditions, turned their back to the subject, or wore a welder’s mask while facing the subject after demonstrating each box’s auditory properties. It was predicted that subjects would choose to approach the silent container in the latter three conditions. The results indicated that subjects selected boxes at random in all conditions. Additionally, in order to explore the possibility of perspective-taking representing a derived trait in the genus Macaca, a phylogeny of the genus was created and annotated to display the presence of perspective-taking as a phenotypic trait in extant species. Three likely evolutionary scenarios leading to the current distribution of perspective-taking are postulated and analyzed for parsimony through the number of assumed gains and losses. The most parsimonious tree suggests that perspective taking could be a conserved trait among the order, giving credence to the argument that some other variable was responsible the negative results in this experiment. It is suggested that the results of the present study represent an artifact of the social environment of the subject population. Moreover, arguments are made for the development of more naturalistic studies for examining mental state attribution in primates.

Using extreme value theory to value stock market returns

Extreme stock price movements are of great concern to both investors and the entire economy. For investors, a single negative return, or a combination of several smaller returns, can possible wipe out so much capital that the firm or portfolio becomes illiquid or insolvent. If enough investors experience this loss, it could shock the entire economy. An example of such a case is the stock market crash of 1987. Furthermore, there has been a lot of recent interest regarding the increasing volatility of stock prices. ^ This study presents an analysis of extreme stock price movements. The data utilized was the daily returns for the Standard and Poor's 500 index from January 3, 1978 to May 31, 2001. Research questions were analyzed using the statistical models provided by extreme value theory. One of the difficulties in examining stock price data is that there is no consensus regarding the correct shape of the distribution function generating the data. An advantage with extreme value theory is that no detailed knowledge of this distribution function is required to apply the asymptotic theory. We focus on the tail of the distribution. ^ Extreme value theory allows us to estimate a tail index, which we use to derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of stock prices. There are three possible limit laws for the maximum: Gumbel (thick-tailed), Fréchet (thin-tailed) or Weibull (no tail). Results indicated that extreme returns during the time period studied follow a Fréchet distribution. Thus, this study finds that extreme value analysis is a valuable tool for examining stock price movements and can be more efficient than the usual variance in measuring risk. ^