Using a behavioral finance approach we study the impact of behavioral bias. We construct an artificial market consisting of fundamentalists and chartists to model the decision-making process of various agents. The agents differ in their strategies for evaluating stock prices, and exhibit differing memory lengths and confidence levels. When we increase the heterogeneity of the strategies used by the agents, in particular the memory lengths, we observe excess volatility and kurtosis, in agreement with real market fluctuations—indicating that agents in real-world financial markets exhibit widely differing memory lengths. We incorporate the behavioral traits of adaptive confidence and observe a positive correlation between average confidence and return rate, indicating that market sentiment is an important driver in price fluctuations. The introduction of market confidence increases price volatility, reflecting the negative effect of irrationality in market behavior.

industrialization in sub-saharan africa and import substitution policy ana pauLa F. MenDes MáriO a. BerteLLa ruDOLpH F. a. p. teixeira* This article aims to contribute to the understanding of the process of import substitution in Sub-Saharan Africa. The process of industrialization in Sub-Saharan Africa occurred in two phases: a first step, even very early during the colonial regime began around the 1920s and ended in the late forties; a second phase of industrialization began in the late fifties and gained momentum in the sixties, when import substitution was implemented more widely. Although these countries were the last to embark on the strategy of import substitution, they followed the same steps of Latin American countries, and as the structural domestic and external constraints were too strong, the failure of the policy of import substitution arrived early and the negative impact on these economies had a greater magnitude.

Complex non-linear interactions between banks and assets we model by two time-dependent Erdős Renyi network models where each node, representing bank, can invest either to a single asset (model I) or multiple assets (model II). We use dynamical network approach to evaluate the collective financial failure-systemic risk-quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided on sub-periods, where within each sub-period banks may contiguously fail due to links to either (i) assets or (ii) other banks, controlled by two parameters, probability of internal failure p and threshold T h ("solvency" parameter). The systemic risk non-linearly increases with p and decreases with average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can sustain (smaller T h ), the smaller the systemic risk-for some T h values in I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic (ii) controlled by probability p2-a condition for the bank to be solvent (active) is stochastic-the systemic risk decreases with decreasing p2. We analyse asset allocation for the U.S. banks.

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index—both generated by our model—are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant.