L'efficience des marchés financiers face à la crise financière de 2007

La récente crise financière de 2007 a amené plusieurs questionnements sur la structure architecturale de la théorie financière; des critiques se sont mises à prendre cible la théorie de l'efficience des marchés financiers. Considérée comme la pire crise financière que le monde a connue depuis la Grande Dépression, la crise financière de 2007 a fourni des arguments de taille à ceux considérant la théorie de l'efficience comme dépassée. Le travail présent consiste à analyser la validité de la théorie de l'efficience des marchés à travers la crise financière de 2007. Le modèle d'un marché efficient demeure important dans le quotidien des multiples transactions sur le marché bousier. Ainsi, une approche employant des indices bousiers majeurs constitue une bonne source pour l'étude. Divers outils économétriques traditionnels et modernes tels que le test d'autocorrélation, le "runs test", le test du ratio de variance et le test du ratio de variance basé sur les rangs et les signes sont utilisés à cette fin. Les résultats obtenus ont démontré que l'efficience des marchés est toujours validée lorsque nous avons employé les tests d'autocorrélation et le "runs test". Dans le cas des tests du ratio de variance et celle basée sur les rangs et les signes, l'efficience n'a pu être validée dans certains cas. Cependant, l'explication de ce résultat s'explique par la présence de variance variable. En tenant compte de cet effet, les résultats ont soutenu la présence d'un marché efficient. Suite aux résultats trouvés, l'idée de renoncer à la théorie d'efficience des marchés n'a pas pu être retenue.\ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : efficience du marché, crise financière, marche aléatoire, test paramétrique, test non paramétriqu

An Efficient Design of the Piezoresistive Pressure Sensor Applied for Micro Aerial Vehicle

In this research, the developing process of a piezoresistive pressure sensor working in the atmosphere environment applied in micro aerial vehicle using the MEMS fabrication method is introduced. The sensor consists of four Au/Cr piezoresistors in a Wheatstone bridge configuration on a wet oxidized silicon diaphragm. To fabricate the sensor, three lithographic steps were conducted: the first one is to define the resistors and Au/Cr lines/pads, the second and the third ones are to determine the width and the thickness of the square SiO2/Si diaphragm, respectively. The sensor diaphragm shape and thickness were defined by the anisotropic etching of Si in tetramethylammonium hydroxide (TMAH) solution, and the resistors array are formed by sputtering and wet etching method. The sensor size is ~6000 µm by 6000 µm. The sensor output voltage was measured for various applied pressure levels from 0 to 1.2 bar with 5V voltage supply. The fabricated sensor also exhibits a sensitivity of 50.01 mV/bar

An Efficient Design of the Piezoresistive Pressure Sensor Applied for Micro Aerial Vehicle

In this research, the developing process of a piezoresistive pressure sensor working in the atmosphere environment applied in micro aerial vehicle using the MEMS fabrication method is introduced. The sensor consists of four Au/Cr piezoresistors in a Wheatstone bridge configuration on a wet oxidized silicon diaphragm. To fabricate the sensor, three lithographic steps were conducted: the first one is to define the resistors and Au/Cr lines/pads, the second and the third ones are to determine the width and the thickness of the square SiO2/Si diaphragm, respectively. The sensor diaphragm shape and thickness were defined by the anisotropic etching of Si in tetramethylammonium hydroxide (TMAH) solution, and the resistors array are formed by sputtering and wet etching method. The sensor size is ~6000 µm by 6000 µm. The sensor output voltage was measured for various applied pressure levels from 0 to 1.2 bar with 5V voltage supply. The fabricated sensor also exhibits a sensitivity of 50.01 mV/bar

Position control for haptic device based on discrete-time proportional integral derivative controller

Haptic devices had known as advanced technology with the goal is creating the experiences of touch by applying forces and motions to the operator based on force feedback. Especially in unmanned aerial vehicle (UAV) applications, the position of the end-effector Falcon haptic sets the velocity command for the UAV. And the operator can feel the experience vibration of the vehicle as to the acceleration or collision with other objects through a forces feedback to the haptic device. In some emergency cases, the haptic can report to the user the dangerous situation of the UAV by changing the position of the end-effector which is be obtained by changing the angle of the motor using the inverse kinematic equation. But this solution may not accurate due to the disturbance of the system. Therefore, we proposed a position controller for the haptic based on a discrete-time proportional integral derivative (PID) controller. A Novint Falcon haptic is used to demonstrate our proposal. From hardware parameters, a Jacobian matrix is calculated, which combines with the force output from the PID controller to make the torque for the motors of the haptic. The experiment was shown that the PID has high accuracy and a small error position

The Nonlinearity of Working Capital and Cross-Sectional Stock Returns: Does Financial Constraints Matter?

This study is the first to examine the impacts of working capital (WC) and financial constraints on cross-sectional stock returns in Taiwan. The findings indicate a non-linear relationship between WC and stock returns. Moreover, the nonlinearity between WC and cross-sectional stock returns is robust after controlling for financial constraints, risk, and growth factors, before the Covid-19 pandemic. In contrast, there is no evidence of nonlinearity between WC and stock returns throughout the Covid-19 outbreak. In addition, the study shows that any deviations from the minimum WC level enhance the stock returns cross-sectionally. It is found that a positive Deviation effect exists in the Taiwan stock exchange before the Covid-19 pandemic by employing portfolio sorting methodologies. The return difference of the long buying highest Deviation and short selling lowest Deviation portfolios earn from 0.6% to 0.9% per month after controlling for financial constraints, risks, and growth factors. Interestingly, it is determined that the deviation effect becomes negative for small stocks during the Covid-19 pandemic, implying that investors prefer small stocks to maintain minimum working capital. The results support the trade-off theory and liquidity preference theory. Finally, the study provides insights into working capital management for managers, and investment strategies for investors during the pandemic

How Foreign Ownership and Competition Affect the Credit Growth of Commercial Banks: Evidence from A Transitional Economy

This study examines the relationship between foreign ownership and market competition, proxied by bank market power, affecting the credit growth of 32 commercial banks in Vietnam from 2010 to 2020. The Random Effects Model and the Dynamic System Generalized Method of Moments were used to analyze an unbalanced panel of 278 annual observations. The findings report that foreign ownership reduces credit growth, with each percentage increase in foreign ownership reducing credit growth by 0.74%. The results indicate an inverse U-shaped relationship between competitive advantage and credit growth, with a turning point of 0.46. The main findings were found to be robust after employing an alternative market power proxy. The study recommends that bank managers and policymakers limit foreign ownership and control commercial banks’ market power to promote sustainable credit growth

Optimization Parameters of Milling Process of Mould Material for Decreasing Machining Power and Surface Roughness Criteria

Improving milling performances is an effective solution to decrease the costs required. This paper addressed a multi-response optimization to simultaneously decrease the machining power consumed Pm, arithmetical roughness Ra, and ten-spot roughness Rz. The Grey-Response Surface Method-Multi Island Genetic Algorithm (GRMA) consisting of grey relational analysis (GRA), response surface method (RSM), and multi-island genetic algorithm (MA) was proposed to predict the optimal parameters and yield optimum milling performances. The experimental trials were conducted with the support of a CNC milling center. The influences of spindle speed (S), depth of cut (ap), feed rate (fz), and tip radius (r) were explored using GRA. The nonlinear relationship between machining parameters and grey grade (GG) model was developed using RSM. Finally, two optimization techniques, including desirability approach (DA) and MA were performed to observe the optimal values. The results indicated that the machining power was greatly affected by processing factors and the radius has a significant impact on the roughness criteria. The measured reductions using optimal parameters of Pm, Ra, and Rz are approximately 77.05%, 50.00%, and 58.02%, respectively, as compared to initial settings. The GRMA can be considered as an effective approach to generate reliable values of processing conditions and technological performances in the milling process