Shareholder value creation in Europe. Eurostoxx 50: 1997-2003

2003 was a good year for the shareholders of the companies in the Euro Stoxx 50: the shareholder value creation of these 50 companies was €150,016 million. The companies that created most value for their shareholder were Siemens (€18,778 million), Telefonica (15,382) and BSCH (12,443). The companies that destroyed most shareholder value were Nokia (-€12,051 million), L'Oreal (-8,089) and Ahold (-5,427). None of the Spanish companies in the Euro Stoxx 50 destroyed shareholder value in 2003. Shareholder value destruction in the three-year period 2001-2003 was €-1.75 trillion. The market value of the 50 companies was €1.65 trillion in 2003, and €1.4 trillion in 2002. We also calculate the created shareholder value of the 50 companies during the seven-year period 1997-2003. Siemens was the top shareholder value creator and Nokia the top shareholder value destroyer during the seven-year period. A portfolio long in the companies that entered the index and short in the companies that abandoned the index had on average a 6% return in the 20 days prior to the index recomposition and a 7% return in the 20 days after the index recomposition. In 2003, the Euro Stoxx 50 was much more volatile than the S&P 500 or the Dow Jones.shareholder value creation; created shareholder value; shareholder value added; shareholder return; required return equity;

Shareholder value creators in the S&P 500: Year 2004

During 2004, 64% of the companies in the S&P 500 created value, while in 2003 the figure was 87%. The market value of the 500 companies was $11.2 trillion in 2004, compared to$10.1 trillion in 2003. The top shareholder value creators in 2004 were Exxon, General Electric, Ebay, Johnson & Johnson and Qualcomm. We define created shareholder value and provide the ranking of created shareholder value for the 500 companies. We also calculate the created shareholder value of the 500 companies during the twelve-year period 1993-2004. General Electric was the top shareholder value creator and AT&T was the top shareholder value destroyer during the twelve-year period. On average, the small market capitalization companies of the S&P were more profitable. Between 1998 and 2004, the volatility of the S&P as a whole fell, but the volatility of its components increased on the average.shareholder value creation; created shareholder value; equity market value; shareholder value added; shareholder return; required return to equity;

Shareholder value creators and shareholder value destroyers in Europe. Year 2002

2002 was a bad year for the shareholders of the companies in the Euro Stoxx 50: the shareholder value destruction of the companies in the Euro Stoxx 50 was 958,968 million euros. In 2002 only Eni created value (3,374 million euros). The remaining 49 companies destroyed value and had negative returns. Alcatel had the lowest shareholder return in 2002 (-77.9%). Shareholder value destruction in the 3-year period 2000-2002 was 1.9 trillion euros. The market value of the 50 companies was 1.42 trillion euros in 2002, and 2.24 trillion euros in 2001, and 2.75 trillion euros in 2001. The author also calculates the created shareholder value of the 50 companies during the six-year period 1997-2002. Nokia was the top shareholder value creator and Allianz the top shareholder value destroyer during the six-year period. A very weak relationship is found between return and size. A portfolio long in the companies that entered the index and short in the companies that abandoned the index had on average a 10% return in the 16 days prior to the index recomposition and a -6% return in the 12 days after the index recomposition. In 2002, the Euro Stoxx 50 was much more volatile than the S&P 500 or the Dow Jones.shareholder value creators; shareholder value destroyers;

Deep learning for an improved diagnostic pathway of prostate cancer in a small multi-parametric magnetic resonance data regime

Prostate Cancer (PCa) is the second most commonly diagnosed cancer among men, with an estimated incidence of 1.3 million new cases worldwide in 2018. The current diagnostic pathway of PCa relies on prostate-specific antigen (PSA) levels in serum. Nevertheless, PSA testing comes at the cost of under-detection of malignant lesions and a substantial over-diagnosis of indolent ones, leading to unnecessary invasive testing such biopsies and treatment in indolent PCa lesions. Magnetic Resonance Imaging (MRI) is a non-invasive technique that has emerged as a valuable tool for PCa detection, staging, early screening, treatment planning and intervention. However, analysis of MRI relies on expertise, can be time-consuming, requires specialized training and in its absence suffers from inter and intra-reader variability and sub-optimal interpretations. Deep Learning (DL) techniques have the ability to recognize complex patterns in imaging data and are able to automatize certain assessments or tasks while offering a lesser degree of subjectiveness, providing a tool that can help clinicians in their daily tasks. In spite of it, DL success has traditionally relied on the availability of large amounts of labelled data, which are rarely available in the medical field and are costly and hard to obtain due to privacy regulations of patients’ data and required specialized training, among others. This work investigates DL algorithms specially tailored to work in a limited data regime with the final objective of improving the current prostate cancer diagnostic pathway by improving the performance of DL algorithms for PCa MRI applications in a limited data regime scenario. In particular, this thesis starts by exploring Generative Adversarial Networks (GAN) to generate synthetic samples and their effect on tasks such as prostate capsule segmentation and PCa lesion significance classification (triage). Following, we explore the use of Auto-encoders (AEs) to exploit the data imbalance that is usually present in medical imaging datasets. Specifically, we propose a framework based on AEs to detect the presence of prostate lesions (tumours) by uniquely learning from control (healthy) data in an outlier detection-like fashion. This thesis also explores more recent DL paradigms that have shown promising results in natural images: generative and contrastive self-supervised learning (SSL). In both cases, we propose specific prostate MRI image manipulations for a PCa lesion classification downstream task and show the improvements offered by the techniques when compared with other initialization methods such as ImageNet pre-training. Finally, we explore data fusion techniques in order to leverage different data sources in the form of MRI sequences (orthogonal views) acquired by default during patient examinations and that are commonly ignored in DL systems. We show improvements in a PCa lesion significance classification when compared to a single input system (axial view)

Preventing financial disasters: Macroprudential policy and financial crises

The ultimate goal of macroprudential policy is to prevent and reduce the costs of systemic financial crises, and thus contribute to promoting sustainable economic growth. However, despite the active role played by such policies in recent decades, there is still limited empirical evidence regarding whether prudential regulation is effective to enhance financial stability by preventing and mitigating crisis risk. This paper seeks to close that gap by studying the relationship between macroprudential policy and both the likelihood and severity of financial crises. The contribution of the paper is twofold. First, I show that macroprudential policy tightenings are successful at reducing the frequency of systemic financial crises. Moreover, this result holds even if macroprudential policies are implemented when the economy is already experiencing a financial boom or when monetary conditions are rather accommodative. I point to the prevention and mitigation of financial booms as the main transmission mechanism through which macroprudential policy defuses crisis risk. Second, I find that macroprudential policy enhances the resilience of the financial system, by dampening the output losses associated with future systemic financial crises. The latter result implies that macroprudential policy not only makes financial crises less likely, but also less painful

Characterization and Correction of Evaporative Artifacts in Speleothem Fluid Inclusion Isotope Analyses as Applied to a Stalagmite From Borneo

Fluid inclusion water isotope measurements in speleothems have great potential for paleoclimate studies as they enable the reconstruction of precipitation dynamics and land temperatures. Several previous observations, however, suggest that inclusion waters do not always reflect the isotopic composition of surface precipitation. In such cases, dripwaters are thought to be modified by evaporation in the cave environment that results in more positive δ 2H and δ 18O values and shallow δ 2H/δ 18O slopes. Although evaporation can occur in cave systems, water can also be lost to evaporation during analysis but before water extraction. Here, we examine the likelihood of this possibility with a stalagmite from Borneo. We demonstrate that many samples lose water, and that water loss is controlled by the type and size of inclusions. With multiple replicate measurements of coeval samples, we calculate an evaporative δ 2H/δ 18O slope of 1.0 ± 0.6 (2SE). This value is consistent with model predictions of evaporative fractionation at high analytical temperature and low humidity. Finally, we propose a method to correct for this effect. We find that fluid–calcite δ 18O paleotemperatures calculated with corrected δ 18O data show excellent agreement with recent microthermometry temperature estimates for Borneo, supporting the validity of our approach and implying limited stalagmite δ 18O disequilibrium variations. Corrected fluid inclusion δ 18O and δ 2H values follow the expected hydroclimate response of Borneo to periods of reduced Atlantic Ocean meridional overturning circulation. Our results suggest that careful petrographic examination and multiple replicate measurements are necessary for reliable paleoclimate reconstructions with speleothem fluid inclusion water isotopes.The Norwegian Research Council (Grant 262353/F20)European Research Council (Grant 101001957 to A.N.M.)FARLAB (RCN Grant 245907)Juan de la Cierva Fellowship (IJC2019040065-I)Spanish Ministry of Science and Innovation and co-funded by the European Development Fund and the European Social Fun

Avances en el control del bitter pit en manzano.

En este trabajo se realiza una sucinta recopilación de los últimos avances en la investigación aplicada al control del bitter pit en la Estación Experimental de Aula Dei (EEAD-CSIC). Se describen nuevas formulaciones y estrategias de aplicación foliar con calcio, un método físico postcosecha y el método de tinción selectiva de calcio en frut

Rock Classification in Organic Shale Based on Petrophysical and Elastic Rock Properties Calculated from Well Logs

This thesis introduces a rock classification technique for organic-rich shale that takes into account well-log-based estimates of compositional, petrophysical, and elastic properties. Well logs and laboratory core measurements were used to calculate depth-by-depth petrophysical and compositional properties of three wells in two organic-rich formations. Then, either acoustic well logs or effective medium theories helped estimate formation elastic properties. Estimates of total porosity, Total Organic Content (TOC), fluid saturation, volumetric concentrations of mineral constituents, and elastic properties facilitated identification of different rock classes, using an unsupervised artificial neural network. A good rock classification technique improves (a) petrophysical evaluation of organic-rich shale reservoirs, (b) fluid flow characterization, (c) detection of productive zones for fracturing jobs, and (d) prediction of hydraulic fracturing and stimulation effectiveness. Then, a rock classification method was then applied to the field examples from the Haynesville shale and Woodford shales for rock classification. The estimates of porosity, TOC, bulk modulus, shear modulus, and volumetric concentrations of minerals were obtained and then validated by comparing them to laboratory measurements. These calculated properties and well logs served as inputs to an artificial neural network to identify the different rock classes in both formations. Finally, the rock classes enabled identification of good candidate zones for fracture stimulation

Rentabilidad y creación de valor para los accionistas de las empresas españolas y del Ibex 35. 1992-2004

En este trabajo se analiza la evolución del IBEX y de las 75 empresas españolas que cotizaron en bolsa (en el mercado continuo) desde diciembre de 1992 hasta diciembre de 2004. Los datos de 2004 se presentan en los Anexos. Las definiciones que se utilizan se toman del libro "Valoración de Empresas", y son: 1) capitalización: valor de todas las acciones de la empresa; 2) aumento del valor para los accionistas; 3) rentabilidad para los accionistas; 4) la rentabilidad exigida a las acciones, y 5) creación de valor para los accionistas.Valor mercado de la empresa; valor añadido para los accionistas; rentabilidad del accionista; rentabilidad requerida recursos propios;