Financial Literacy, Financial Markets Index, and Investors’ Biased Responses

Using earnings data from Q1 2012 to Q4 2015 for 300 stocks in 15 countries, this study aims to investigate relations between financial literacy, financial markets index, and investors’ biased responses to earnings news. Financial literacy refers to an individual’s abilities and skills to manage financial problems and make informed decisions that benefit his or her personal financial well-being, including retirement, investing, and loans, etc. (Lusardi & Mitchell, 2014). Financial markets index reflects how developed a financial market is, including its depth, access, and efficiency (Svirydzenka, 2016). Stock prices’ biased responses happen when prices fail to reflect all available information. A variety of studies have been done to investigate why stock prices underreact or overreact to earnings news. There is, however, few or no study trying to link financial education and financial markets development to stock price’s biased responses. Therefore, objectives of this study are to better understand whether a higher level of financial education would ease investors’ sensitivity to news, and if a more developed financial market would lessen underreactions and overreactions of stock prices to earnings announcements. The methodology of this study is regression analysis. Major findings are that the level of financial literacy does not have a significant influence on the magnitude of earnings surprise, and that financial markets index is negatively correlated to investors’ biased responses to earnings surprise. The more developed a market is, the better market movements incorporate anticipated information.No embargoAcademic Major: Financ

Spinel Transition Metal Oxide Nanoparticle-Pigmented Solar Selective Coatings with High Thermal Efficiency and High-Temperature Thermal Stability in Air

This thesis explores spinel-structure transition metal oxide nanoparticle pigmented solar selective coatings with high thermal efficiency (\u3e90%) and high-temperature (~750 ºC) thermodynamic stability via cost-effective and facile fabrication methods. Compared to the preliminary work, we reduce the emittance loss by selecting silicones with a lower emittance loss as the matrix. We further move from purchasing simple commercial oxide nanoparticles to systematically designing and synthesizing spinel-structure based three-transition-metal-incorporated oxide nanoparticles for a better optical response of nanoparticle pigmented coatings. Nanoparticles of three systems are studied, including Ni-Mn-Fe oxide, Cu-Mn-Fe oxide, and Cu-Mn-Cr oxide systems. Among, Cu-Mn-Cr oxide nanoparticle pigmented silicone solar selective coatings on Inconel 625 substrates with an outer diameter of 76mm show an optimal optical-to-thermal conversion performance, with a solar absorbance of 97.9%, thermal emittance of 59.4% and a record-high thermal efficiency up to 94.2% at a temperature of 750 ºC and solar concentration ratio of 1000. According to some electronic structure investigations, the excellent absorbing behaviors are attributed to the joint result of d-d transitions, charge transfer effect and defects in the structure. Simulation results based on the four-flux radiative model confirm no need for precise control over volume and volume fraction of nanoparticles in coatings, and prove that our current recipes lie in the optimized region for absorptance. Up to 60 simulated day (12h)-night (12h) thermal cycles (a total annealing time of 720h) at 750 ºC and/or 800 ºC are conducted for stability verification of Cu-Mn-Fe oxide and Cu-Mn-Cr oxide nanoparticle pigmented solar selective coatings. No more than 1% efficiency loss is observed for coatings after thermal cycles at 750 ºC and 800 ºC, indicating the superior resistance against thermal degradations caused by long-time operations at high temperatures. Inter-diffusion under very high temperatures is confirmed to enhance the adhesion of the interface, and therefore improve the mechanical stability against slight scratches. This study offers a promising approach to high-efficiency, high-temperature stable and economically friendly solar selective coatings with feasibility of scaling up for the next generation CSP systems

Do households react to policy uncertainty by increasing savings?

Studying the impact of policy uncertainty on household savings is essential to understanding how policymaking affects households’ economic behavior. Previous studies suggest that policy uncertainty could dampen consumption and encourage savings. However, these studies did not consider the effects of the business cycle and endogeneity and the roles of financial development and institutional quality in the uncertainty-saving nexus. Using quarterly data from 21 countries from 1987–2021, we find that a one-standard-deviation rise in policy uncertainty increases household saving rates by three percentage points within six quarters. This effect persists even after accounting for the business cycle and endogeneity. In addition, high financial development and institutional quality mitigate the policy uncertainty effect on savings by about 1.1 and 0.7 percentage points, respectively. This study enriches the study on policy uncertainty and household savings while also providing new insights to better identify the impact of policy uncertainty

On a computational framework to model material degradation due to moisture, temperature, and chemical reactions

Degradation is a major, widespread, and an important engineering problem. Its manifestations have been well known in infrastructure and various other real-life applications. This can be attributed to the fact that not only the durability of materials will be reduced, but also the material properties can be affected. For instance, thermal conductivity and diffusivity can change its behavior from isotropic to anisotropic because of the influence of material damage. Degradation can be caused by various mechanisms such as mechanical processes, chemical dissolution, oxidation, photolysis, biological effects, and radiation. Moreover, coupling effects between these mechanisms can have a significant impact on the rate of deterioration of materials and structures. Therefore, developing an appropriate framework to model material degradation is very useful to predict the life span of a given structure. Hence, a comprehensive knowledge on the effects of degradation not only plays a pivotal role in improving the reliability of existing infrastructure, but also has a tremendous impact on the economy. However, it should be noted that developing a unified thermodynamic and computational framework to encompass the above set of mechanisms for material degradation is still an open problem. Furthermore, the governing equations to model even a simple degradation mechanism such as moisture or thermal by-itself is complicated and difficult to construct. In this discussion, we shall assume that predominant degradation mechanisms are moisture/chemical reactions and temperature and aim to propose a general a three-way strongly coupled degradation model based on a thermodynamic framework. In general, there are two approaches to build a thermodynamically consistent degradation model. The first one is based on the theory of internal variables. In this method, one models degradation using an internal variable. The second method is to investigate the dependence of material properties on concentration and temperature. The main disadvantage of the first approach is that it is difficult (or sometimes impossible) to measure the internal variables via experiments. However, the second methodology can compensate it. Moreover, the degradation parameters based on the second approach have a physical basis as compared to the first method. Hence, in this discussion, we shall use the second approach to construct a thermodynamically consistent degradation model in which all the damage parameters can be measured in experiments. It should be noted that the resulting governing equations for the proposed degradation model are coupled and highly nonlinear. In many cases, obtaining analytical solutions is extremely difficult. Consequently, we shall describe a numerical framework to solve such coupled nonlinear partial differential equations. Employing this computational framework, we shall solve representative boundary value problems pertaining to degradation of slabs. We shall also compare the behavior of an infinite degrading slab with the behavior of a finite-sized degrading slab. This highlights the limitations of the typical semi-inverse solutions, which are commonly employed in engineering and design practice. Finally, through such numerical examples, we shall shed light on the load carrying capacity and structural response of degrading structural members, which is vital for better design and safety codes