Forward Plan

Future work can be divided in four main parts:

• Analytical study of moments and other parameters using the one-factor model and the multifactor model. Multifactor model with intra-sector and inter-sector terms. One term is just related with the correlations between stocks of the same sector and the other with the correlations of stocks from different sectors. Explaining the correlation between moments of correlations and distances in the MST and the MST arrangement in clusters. Derive the equation for the spectrum of eigenvalues of the correlation matrix for multifactor models.

• Study of large amount of data of daily stock prices from different markets. How these stocks will cluster is the main propose of this study. In our studies we saw that stocks from the same market (London Stock Exchange, FTSE100) clustered together in terms of industrial sectors, and that indices from different countries cluster in terms of geographical distance. Now we want to now if the geographical distance is more important that the industrial classification.

• Simulation of stock prices using a new model, based on our studies of multifactor models, for the return of the price of a stock. We want to create a new stochastic model for the returns and compare the results with our empirical data.

• Simulation of a wealth distribution model, with dynamical networks, with few parameters, that will mimic the real results of a Pareto's Law with an exponent between $1.5$ and $2.5$. This model should be able to get a distribution of wealth with double Pareto tail, as we can see in many different results of empirical data, a Pareto exponent for the richest individuals, and another exponent for the few very rich that normally appear in the top richest list, like Forbes.

Table 4.1: Gantt chart.

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