Genetic Programming for Multibiometrics

Biometric systems suffer from some drawbacks: a biometric system can provide in general good performances except with some individuals as its performance depends highly on the quality of the capture. One solution to solve some of these problems is to use multibiometrics where different biometric systems are combined together (multiple captures of the same biometric modality, multiple feature extraction algorithms, multiple biometric modalities...). In this paper, we are interested in score level fusion functions application (i.e., we use a multibiometric authentication scheme which accept or deny the claimant for using an application). In the state of the art, the weighted sum of scores (which is a linear classifier) and the use of an SVM (which is a non linear classifier) provided by different biometric systems provide one of the best performances. We present a new method based on the use of genetic programming giving similar or better performances (depending on the complexity of the database). We derive a score fusion function by assembling some classical primitives functions (+, *, -, ...). We have validated the proposed method on three significant biometric benchmark datasets from the state of the art

IPOs, Trade Sales and Liquidations: Modelling Venture Capital Exits Using Survival Analysis

Using a detailed sample made up of more than 20,000 investment rounds, we analyze the time to ‘IPO’, ‘trade sale’ and ‘liquidation’ for about 6,000 venture backed firms. We model these exit times using competing risks models. Biotech and internet firms have the fastest IPO exits. Internet firms are also the fastest to liquidate, while biotech firms are however the slowest. The conditional probability for IPOs are clearly non-monotonous with respect to time. As time flows, venture capital-backed firms first exhibit an increased likelihood of exiting to an IPO. However, after having reached a plateau, investments that have not yet exited have fewer and fewer possibilities of IPO exits as time increases. The bubble period from 1998 to 2000 was an ‘easy money’ period where venture capitalists gave much more money to firms, many of which did not offer outstanding growth potential as they tended to liquidate much faster than in normal times.IPO, trade sale, venture capital, exit, survival analysis

Modelling daily value-at-risk using realized volatility and arch type models

In this paper we show how to compute a daily VaR measure for two stock indexes (CAC40 and SP500) using the one-day-ahead forecast of the daily realized volatility. The daily re-alized volatility is equal to the sum of the squared intraday returns over a given day and thus uses intraday information to define an aggregated daily volatility measure. While the VaR specification based on an ARFIMAX(0,d,1)-skewed Student model for the daily realized volatility provides adequate one-day-ahead VaR forecasts, it does not really improve on the performance of a VaR model based on the skewed Student APARCH model and estimated using daily data. Thus, for the two financial assets considered in an univariate framework, both methods seem to be equivalent. This paper also shows that daily returns standardized by the square root of the one-day-ahead forecast of the daily realized volatility are not normally distributed.mathematical economics;

Performance Evaluation of Biometric Template Update

Template update allows to modify the biometric reference of a user while he uses the biometric system. With such kind of mechanism we expect the biometric system uses always an up to date representation of the user, by capturing his intra-class (temporary or permanent) variability. Although several studies exist in the literature, there is no commonly adopted evaluation scheme. This does not ease the comparison of the different systems of the literature. In this paper, we show that using different evaluation procedures can lead in different, and contradictory, interpretations of the results. We use a keystroke dynamics (which is a modality suffering of template ageing quickly) template update system on a dataset consisting of height different sessions to illustrate this point. Even if we do not answer to this problematic, it shows that it is necessary to normalize the template update evaluation procedures.Comment: International Biometric Performance Testing Conference 2012, Gaithersburg, MD, USA : United States (2012

Hybrid Template Update System for Unimodal Biometric Systems

Semi-supervised template update systems allow to automatically take into account the intra-class variability of the biometric data over time. Such systems can be inefficient by including too many impostor's samples or skipping too many genuine's samples. In the first case, the biometric reference drifts from the real biometric data and attracts more often impostors. In the second case, the biometric reference does not evolve quickly enough and also progressively drifts from the real biometric data. We propose a hybrid system using several biometric sub-references in order to increase per- formance of self-update systems by reducing the previously cited errors. The proposition is validated for a keystroke- dynamics authentication system (this modality suffers of high variability over time) on two consequent datasets from the state of the art.Comment: IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS 2012), Washington, District of Columbia, USA : France (2012

An international analysis of earnings, stock prices and bond yields

This paper assesses the possible contemporaneous relationship between stock index prices, earnings and long-term government bond yields for a large number of countries and over a time period that spans several decades. In a cointegration framework, our analysis looks at three hypotheses. First, is there a long-term contemporaneous relationship between earnings, stock prices and government bond yields? Second, does a deviation from this possible long-run equilibrium impact stock prices such that the equilibrium is restored? Third, do government bond yields play a significant role in the long-run relationship or does the latter only involve stock prices and earnings? We also study the short-term impact of changes in long-term government bond yields on stock prices and discuss our short-term and long-term results in light of the recent developments regarding the so-called Fed model.stock indexes, earnings, long-run relationships, interest rates, inflation, market valuation

Fast computation of the performance evaluation of biometric systems: application to multibiometric

The performance evaluation of biometric systems is a crucial step when designing and evaluating such systems. The evaluation process uses the Equal Error Rate (EER) metric proposed by the International Organization for Standardization (ISO/IEC). The EER metric is a powerful metric which allows easily comparing and evaluating biometric systems. However, the computation time of the EER is, most of the time, very intensive. In this paper, we propose a fast method which computes an approximated value of the EER. We illustrate the benefit of the proposed method on two applications: the computing of non parametric confidence intervals and the use of genetic algorithms to compute the parameters of fusion functions. Experimental results show the superiority of the proposed EER approximation method in term of computing time, and the interest of its use to reduce the learning of parameters with genetic algorithms. The proposed method opens new perspectives for the development of secure multibiometrics systems by speeding up their computation time.Comment: Future Generation Computer Systems (2012

Web-Based Benchmark for Keystroke Dynamics Biometric Systems: A Statistical Analysis

Most keystroke dynamics studies have been evaluated using a specific kind of dataset in which users type an imposed login and password. Moreover, these studies are optimistics since most of them use different acquisition protocols, private datasets, controlled environment, etc. In order to enhance the accuracy of keystroke dynamics' performance, the main contribution of this paper is twofold. First, we provide a new kind of dataset in which users have typed both an imposed and a chosen pairs of logins and passwords. In addition, the keystroke dynamics samples are collected in a web-based uncontrolled environment (OS, keyboards, browser, etc.). Such kind of dataset is important since it provides us more realistic results of keystroke dynamics' performance in comparison to the literature (controlled environment, etc.). Second, we present a statistical analysis of well known assertions such as the relationship between performance and password size, impact of fusion schemes on system overall performance, and others such as the relationship between performance and entropy. We put into obviousness in this paper some new results on keystroke dynamics in realistic conditions.Comment: The Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP 2012), Piraeus : Greece (2012

How does liquidity react to stress periods in a limit order market?

This paper looks at the interplay of volatility and liquidity on the Euronext trading platform during the December 2, 2002 to April 30, 2003 time period. Using transaction and order book data for some large- and mid-cap Brussels-traded stocks on Euronext, we study the ex-ante liquidity vs volatility and ex-post liquidity vs volatility relationships to ascertain if the high volatility led to decreases in liquidity and large trading costs. We show that the provision of liquidity remains adequate when volatility increases, although we do find that it is more costly to trade and that the market dynamics is somewhat affected when volatility is high.order book, volatility, liquidity

Volatility regimes and the provisions of liquidity in order book markets

We analyze whether the liquidity provision in a pure order book market during normal market conditions (low volatility regime) differs from what is observed when the market is under stress (high volatility regime). We show that the static relationship between liquidity and volatility is resilient to regime changes in volatility. Nevertheless, we do find that it is more costly to trade when volatility is large. A VAR analysis shows that the liquidity dynamics is similar in the low and high volatility regimes, although the drop in liquidity subsequent to volatility shocks is larger in the high volatility regime. Finally, the market is more resilient to volatility or liquidity shocks in periods of turnoils.order book; volatility; liquidity