Recurrence analysis of the NASDAQ crash of April 2000

Recurrence Plot (RP) and Recurrence Quantification Analysis RQA) are signal numerical analysis methodologies able to work with non linear dynamical systems and non stationarity. Moreover they well evidence changes in the states of a dynamical system. It is shown that RP and RQA detect the critical regime in financial indices (in analogy with phase transition) before a bubble bursts, whence allowing to estimate the bubble initial time. The analysis is made on NASDAQ daily closing price between Jan. 1998 and Nov. 2003. The NASDAQ bubble initial time has been estimated to be on Oct. 19, 1999.Comment: 5 pages, 3 figures, 1 table, 12 references, to be published in "Fruits of Econophysics", H. Takayasu, Ed. Springer 200

Delegated Portfolio Management with Socially Responsible Investment Constraints

We consider the problem of how to set a compensation for a portfolio manager who is required to restrict the investment set, as it happens when applying socially responsible screening. This is a problem of Delegated Portfolio Management where the reduction of the investment opportunities to the subset of sustainable assets involves a loss in the expected earnings for the portfolio manager, compensated by the investor through an extra bonus on the realized return. Under simple assumptions on the investor, the manager and the market, we compute the optimal bonus as a function of the manager's risk aversion and his expertise, and of the impact of the portfolio restriction on the Mean Variance efficient frontier. We conclude by discussing the problem of selecting the best managers when his ability is not directly observable by the investor.Delegated portfolio management; Socially responsible investment; Incentives; Extrinsic incentives; Intrinsic motives

A Markov chain approach to ABM calibration

Agent based model are nowadays widely used, however the lack of general methods and rules for their calibration still prevent to exploit completely their potentiality. Rarely such a kind of models can be studied analytically, more often they are studied by using simulation. Reference [1] show that many computer simulation models, like ABM, can be represented as Markov Chains. Exploting such an idea we illustrate an example of how to calibrate an ABM when it can be revisited as a Markov chain

Are openness and intellect valid and reliable constructs? : a psychometric investigation

Openness and Intellect have been proposed as two distinct personality constructs located between the broad Openness/Intellect domain and its facets. Although they have shown to be useful in clarifying the associations between Openness/Intellect and different variables, their factor structure has not been empirically supported. This study a) adapted the Openness and Intellect scales for the Brazilian context and b) tested the factor structure of these scales using robust statistical techniques in two Brazilian samples (n = 750 and n = 612). Confirmatory factor analysis (CFA) did not support the original second-order model. Instead, a bifactor model with a general and two specific factors presented the best fit to the data. Evidence of validity and reliability for the Openness and Intellect aspects is presented and theoretical implications of these results are discussed

an agent based model for a double auction with convex incentives

We studied the influence of convex incentives, e.g. option-like compensations, on the behavior of financial markets. Such incentives, usually offered to portfolio managers, have been often considered a potential source of market instability. We built an agent-based model of a double-auction market where some of the agents are endowed with convex contracts. We show that these contracts encourage traders to buy more aggressively, increasing total demand and market prices. Our analysis suggests that financial markets with many managers with convex contracts are more likely to be more unstable and less efficient

Random distributions via Sequential Quantile Array

We propose a method to generate random distributions with known quantile distribution, or, more generally, with known distribution for some form of generalized quantile. The method takes inspiration from the random Sequential Barycenter Array distributions (SBA) proposed by Hill and Monticino (1998) which generates a Random Probability Measure (RPM) with known expected value. We define the Sequential Quantile Array (SQA) and show how to generate a random SQA from which we can derive RPMs. The distribution of the generated SQA-RPM can have full support and the RPMs can be both discrete, continuous and differentiable. We face also the problem of the efficient implementation of the procedure that ensures that the approximation of the SQA-RPM by a finite number of steps stays close to the SQA-RPM obtained theoretically by the procedure. Finally, we compare SQA-RPMs with similar approaches as Polya Tree