Bayesian Analysis of Structural Credit Risk Models with Microstructure Noises

In this paper a Markov chain Monte Carlo (MCMC) technique is developed for the Bayesian analysis of structural credit risk models with microstructure noises. The technique is based on the general Bayesian approach with posterior computations performed by Gibbs sampling. Simulations from the Markov chain, whose stationary distribution converges to the posterior distribution, enable exact finite sample inferences of model parameters. The exact inferences can easily be extended to latent state variables and any nonlinear transformation of state variables and parameters, facilitating practical credit risk applications. In addition, the comparison of alternative models can be based on devian information criterion (DIC) which is straightforwardly obtained from the MCMC output. The method is implemented on the basic structural credit risk model with pure microstructure noises and some more general specifications using daily equity data from US and emerging markets. We find empirical evidence that microstructure noises are positively correlated with the firm values in emerging markets.MCMC, Credit risk, Microstructure noise, Devian information criterion

Inkjet Printing Retinal cells vs. Gene Therapy in the treatment of Glaucoma

The neurodegenerative disease glaucoma is one of the leading causes of blindness and accounts for over ten million visits to physicians for treatment. Unfortunately, there is yet to be a concrete accepted approach to alleviating the effects of glaucoma. This dissertation examines recent studies and reports on the specifics of viral vectors, non-viral vectors, piezoelectric inkjet printing, heat inkjet printing, and glaucoma. A few of the studies involve the progression of an experiment while others combine and discuss the results of multiple experiments. Using these articles I compared the effectiveness of gene therapy to the use of inkjet printing to create retinal cells. By replacing, adding, or deleting a specific sequence in the human body, the gene expression of the eye can be altered. There are two different types of injections for gene therapy, viral vectors and non-viral vectors. Both methods typically target the trabecular meshwork and neuroretina to regulate the aqueous humor outflow and lower the intraocular pressure. In the case of glaucoma, the treatment solely provides neuroprotection instead of curing the disease, thus patients must undergo repeated injections in order to keep the disease from deteriorating. Inkjet printing of retinal cells have shown to produce three dimensional tissue grafts that may replace defective tissues. The printed cells have been tested for survivability and regeneration properties, since it has been suggested that the printing process can cause defects. Both heat inkjet printing and piezoelectric printing have been used to create neural cells. By evaluating the advantages and disadvantages of gene therapy as well as printing, I can evaluate whether or not inkjet printing can overtake gene therapy to become a conventional treatment for glaucoma in the near future. There have not been many clinical trials done on either of these methods for glaucoma, thus it is difficult to obtain a certain answer to the question at hand. At this point advancements in the area of three-dimensional printing neural sheets may provide a more promising cure. However, more research must be done on how each of these treatments affect glaucoma in humans.https://scholarscompass.vcu.edu/uresposters/1112/thumbnail.jp

The Stone People Effect: A Visual Generated in Houdini

The short film RhizComics, created in collaboration with Jason Helms, explores comics and comic theory. The opening scene showcases a special effect created in Houdini made to illustrate the ideas in RhizComics. The effect involves two characters morphing into stones and tumbling to the ground. This paper documents the production design for the scene and the steps taken to achieve the effect

What is FOCAC? Three historic stages in the China-Africa relationship

The FOCAC partnership platform between China and Africa has produced increasingly deep and complex relations between regions. Africa has benefited from significant investments and China has developed extensive soft power. In its 22nd year, Shirley Ze Yu looks at four stages in FOCAC’s evolution and how they shaped the China-Africa relationship today

FOCAC and the future of China-Africa relations

The FOCAC partnership platform between China and Africa has undergone multiple stages of evolution since its creation in 2000. But as the Chinese economy loses momentum, has the ever-deepening engagement between these regions reached maximum capacity

Why substantial Chinese FDI is flowing into Africa

In recent years, China has overtaken the US to become the world’s largest foreign direct investor into Africa. LSE Senior Visiting Fellow Shirley Yu explains the motivations behind the rise of these investments and the extent of similarities between the African continent and twentieth-century China

Three reasons why Africa’s digital future is deeply intertwined with China

Chinese influence over Africa’s digital economy has grown rapidly with no sign of slowing, extending beyond infrastructure investments to reshaping entire business models. LSE Fellow Dr Shirley Yu outlines three reasons why Africa’s digital future is intertwined with China and what this means for the continent’s industrial development

Learning to Predict the Cosmological Structure Formation

Matter evolved under influence of gravity from minuscule density fluctuations. Non-perturbative structure formed hierarchically over all scales, and developed non-Gaussian features in the Universe, known as the Cosmic Web. To fully understand the structure formation of the Universe is one of the holy grails of modern astrophysics. Astrophysicists survey large volumes of the Universe and employ a large ensemble of computer simulations to compare with the observed data in order to extract the full information of our own Universe. However, to evolve trillions of galaxies over billions of years even with the simplest physics is a daunting task. We build a deep neural network, the Deep Density Displacement Model (hereafter D$^3$M), to predict the non-linear structure formation of the Universe from simple linear perturbation theory. Our extensive analysis, demonstrates that D$^3$M outperforms the second order perturbation theory (hereafter 2LPT), the commonly used fast approximate simulation method, in point-wise comparison, 2-point correlation, and 3-point correlation. We also show that D$^3$M is able to accurately extrapolate far beyond its training data, and predict structure formation for significantly different cosmological parameters. Our study proves, for the first time, that deep learning is a practical and accurate alternative to approximate simulations of the gravitational structure formation of the Universe.Comment: 8 pages, 5 figures, 1 tabl

Chapter 16- Becoming AWARES: Mentoring Undergraduate Women in Engineering and Sciences

The Aspiration for Women’s Advancement and Retention in Engineering and Sciences (AWARES) mentorship program was designed to support women in science, technology, engineering, and mathematics (STEM) majors as they transition from their undergraduate degree programs to the workforce. The AWARES program was structured around topics relevant to women in STEM careers, including but not limited to interviewing and job offer negotiation, career development, navigating social dynamics in the workplace, and establishing and growing a professional network. Based in tenets of social cognitive theory, AWARES aims to use expert and group mentorship to increase young women’s self-efficacy for career-related soft skills that are associated with retention in STEM professions. We examined quantitative and qualitative outcomes for both mentors and mentees and found that women graduate the program with high levels of self-efficacy and that mentors also feel highly efficacious in their mentorship roles. In addition to mentee and mentor outcomes, quantitative and qualitative evaluation of the program was conducted so that participant feedback can be considered for future iterations of AWARES. Finally, program design, sustainability, and lessons learned are also discussed

Building Legitimacy for Green IS Innovations in Taiwan

The environmental concerns are leading to the growing interest in the adoption of Green IS. From legitimacy perspective, this paper argues that the adoption and diffusion of Green IS among organizations are modulated by pragmatic, normative, and cultural-cognitive influences in the institutional environment. The study therefore applies topology of legitimacy to develop a taxonomy to understand actors’ strategies in shaping the understanding and development of Green IS. Using content analysis of news articles in Taiwan, the study contributes to a practical understanding of the complex institutional influences in forming the greener industry