Is financial instability male-driven? Gender and cognitive skills in experimental asset markets

The hypothesis that price stability would reliably increase with the fraction of women operating in financial markets has been frequently suggested in policy discussions. To test this hypothesis we conducted 10 male-only, 10 female-only and 10 mixed-gender experimental asset markets, and compared the effects of gender composition, confidence, risk attitude and cognitive skills. Male and female markets have comparable volatility and deviations from fundamentals, whereas mixed-gender markets are substantially more stable. On the other hand, higher average cognitive skills of the group are associated with reduced market volatility. Individual-level analysis shows that subjects with higher cognitive skills trade at prices closer to fundamental values and earn significantly higher profits; similarly, mixed markets exhibit lower mispricing, particularly for traders with lower cognitive skills. Our results are demonstrated to hold in other experimental asset market studies, suggesting that a mixed-gender composition reduces mispricing across different types of asset markets.

An evolutive approach for the delineation of local labour markets

This paper presents a new approach to the delineation of local labour markets based on evolutionary computation. The main objective is the regionalisation of a given territory into functional regions based on commuting flows. According to the relevant literature, such regions are defined so that (a) their boundaries are rarely crossed in daily journeys to work, and (b) a high degree of intra-area movement exists. This proposal merges municipalities into functional regions by maximizing a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. Real results are presented based on the latest database from the Census of Population in the Region of Valencia. Comparison between the results obtained through the official method which currently is most widely used (that of British Travel-to-Work Areas) and those from our approach is also presented, showing important improvements in terms of both the number of different market areas identified that meet the statistical criteria and the degree of aggregate intra-market interaction.

A memetic algorithm for the delineation of local labour markets

Given a territory composed of basic geographical units, the delineation of local labour market areas (LLMAs) can be seen as a problem in which those units are grouped subject to multiple constraints. In previous research, standard genetic algorithms were not able to find valid solutions, and a specific evolutionary algorithm was developed. The inclusion of multiple ad hoc operators allowed the algorithm to find better solutions than those of a widely-used greedy method. However, the percentage of invalid solutions was still very high. In this paper we improve that evolutionary algorithm through the inclusion of (i) a reparation process, that allows every invalid individual to fulfil the constraints and contribute to the evolution, and (ii) a hillclimbing optimisation procedure for each generated individual by means of an appropriate reassignment of some of its constituent units. We compare the results of both techniques against the previous results and a greedy method.