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- Creators: Barrett, The Honors College
- Creators: Arizona State University
Description
I study the performance of hedge fund managers, using quarterly stock holdings from 1995 to 2010. I use the holdings-based measure built on Ferson and Mo (2012) to decompose a manager's overall performance into stock selection and three components of timing ability: market return, volatility, and liquidity. At the aggregate level, I find that hedge fund managers have stock picking skills but no timing skills, and overall I do not find strong evidence to support their superiority. I show that the lack of abilities is driven by the large fluctuations of timing performance with market conditions. I find that conditioning information, equity capital constraints, and priority in stocks to liquidate can partly explain the weak evidence. At the individual fund level, bootstrap analysis results suggest that even top managers' abilities cannot be separated from luck. Also, I find that hedge fund managers exhibit short-horizon persistence in selectivity skill.
ContributorsKang, MinJeong (Author) / Aragon, George O. (Thesis advisor) / Hertzel, Michael G (Committee member) / Boguth, Oliver (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cancer is the second leading cause of death in the United States and novel methods of treating advanced malignancies are of high importance. Of these deaths, prostate cancer and breast cancer are the second most fatal carcinomas in men and women respectively, while pancreatic cancer is the fourth most fatal in both men and women. Developing new drugs for the treatment of cancer is both a slow and expensive process. It is estimated that it takes an average of 15 years and an expense of $800 million to bring a single new drug to the market. However, it is also estimated that nearly 40% of that cost could be avoided by finding alternative uses for drugs that have already been approved by the Food and Drug Administration (FDA). The research presented in this document describes the testing, identification, and mechanistic evaluation of novel methods for treating many human carcinomas using drugs previously approved by the FDA. A tissue culture plate-based screening of FDA approved drugs will identify compounds that can be used in combination with the protein TRAIL to induce apoptosis selectively in cancer cells. Identified leads will next be optimized using high-throughput microfluidic devices to determine the most effective treatment conditions. Finally, a rigorous mechanistic analysis will be conducted to understand how the FDA-approved drug mitoxantrone, sensitizes cancer cells to TRAIL-mediated apoptosis.
ContributorsTaylor, David (Author) / Rege, Kaushal (Thesis advisor) / Jayaraman, Arul (Committee member) / Nielsen, David (Committee member) / Kodibagkar, Vikram (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2013
Description
I show that firms' ability to adjust variable capital in response to productivity shocks has important implications for the interpretation of the widely documented investment-cash flow sensitivities. The variable capital adjustment is sufficient for firms to capture small variations in profitability, but when the revision in profitability is relatively large, limited substitutability between the factors of production may call for fixed capital investment. Hence, firms with lower substitutability are more likely to invest in both factors together and have larger sensitivities of fixed capital investment to cash flow. By building a frictionless capital markets model that allows firms to optimize over fixed capital and inventories as substitutable factors, I establish the significance of the substitutability channel in explaining cross-sectional differences in cash flow sensitivities. Moreover, incorporating variable capital into firms' investment decisions helps explain the sharp decrease in cash flow sensitivities over the past decades. Empirical evidence confirms the model's predictions.
ContributorsKim, Kirak (Author) / Bates, Thomas (Thesis advisor) / Babenko, Ilona (Thesis advisor) / Hertzel, Michael (Committee member) / Tserlukevich, Yuri (Committee member) / Arizona State University (Publisher)
Created2013
Description
The bleomycins are a family of glycopeptide-derived antibiotics isolated from various Streptomyces species and have been the subject of much attention from the scientific community as a consequence of their antitumor activity. Bleomycin clinically and is an integral part of a number of combination chemotherapy regimens. It has previously been shown that bleomycin has the ability to selectively target tumor cells over their non-malignant counterparts. Pyrimidoblamic acid, the N-terminal metal ion binding domain of bleomycin is known to be the moiety that is responsible for O2 activation and the subsequent chemistry leading to DNA strand scission and overall antitumor activity. Chapter 1 describes bleomycin and related DNA targeting antitumor agents as well as the specific structural domains of bleomycin. Various structural analogues of pyrimidoblamic acid were synthesized and subsequently incorporated into their corresponding full deglycoBLM A6 derivatives by utilizing a solid support. Their activity was measured using a pSP64 DNA plasmid relaxation assay and is summarized in Chapter 2. The specifics of bleomycin—DNA interaction and kinetics were studied via surface plasmon resonance and are presented in Chapter 3. By utilizing carefully selected 64-nucleotide DNA hairpins with variable 16-mer regions whose sequences showed strong binding in past selection studies, a kinetic profile was obtained for several BLMs for the first time since bleomycin was discovered in 1966. The disaccharide moiety of bleomycin has been previously shown to be a specific tumor cell targeting element comprised of L-gulose-D-mannose, especially between MCF-7 (breast cancer cells) and MCF-10A ("normal" breast cells). This phenomenon was further investigated via fluorescence microscopy using multiple cancerous cell lines with matched "normal" counterparts and is fully described in Chapter 4.
ContributorsBozeman, Trevor C (Author) / Hecht, Sidney M. (Thesis advisor) / Chaput, John (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
Description
The Dodd-Frank Act was created to promote financial stability in the United States. However, no one is quite sure what it is yet. While action had to be taken and Dodd-Frank has some positives, Dodd-Frank, as it is deciphered today, has severe drawbacks. Since Dodd-Frank is only in its infancy, it is difficult to form an interim conclusion about its effects on agricultural lending at this point. After passing Dodd-Frank in 2010, the government began trying to figure out what it means. Four years later, they are still trying and are about half way through making the rules. This law essentially replaces Glass-Steagall, which was repealed several years ago. Many believe repealing Glass-Steagall was a big reason for the financial collapse of 2008. While Glass-Steagall was a short, easily understood document, Dodd Frank adds many more regulations and pages. This creates a long, bulky, confusing law that seems to be extremely tough to comprehend legally or as a banker. In this study, I try to balance the positives and negatives of Dodd-Frank to understand if it is more detrimental or beneficial to agricultural lending. While we find that Dodd-Frank does help keep banks from some of the risky investments that many believe led to the financial crisis, the added paperwork, compliance costs, and strain it puts on small banks can be worrisome. I interviewed several agriculture-lending professionals who regularly deal with the rules and regulations of Dodd-Frank to discover the impact the new law has on banks, their customers, and the economy as a whole. These interviews give insight into what Dodd-Frank means to the agriculture-lending market and what changes have had to occur since the law was passed. These interviews demonstrate that Dodd-Frank is largely looked down upon by the banking industry. The professionals interviewed are very experienced. After the extensive research, interviews, and discoveries that came of this study, it was concluded that Dodd-Frank seems to hurt the lending industry much more than it helps. One major concern is the strain Dodd-Frank puts on small banks and how it makes "too big to fail" banks even bigger.
ContributorsBettencourt, Bradley D (Author) / Thor, Eric (Thesis advisor) / Manfredo, Mark (Committee member) / Englin, Jeff (Committee member) / Arizona State University (Publisher)
Created2014
Description
Genomic structural variation (SV) is defined as gross alterations in the genome broadly classified as insertions/duplications, deletions inversions and translocations. DNA sequencing ushered structural variant discovery beyond laboratory detection techniques to high resolution informatics approaches. Bioinformatics tools for computational discovery of SVs however are still missing variants in the complex cancer genome. This study aimed to define genomic context leading to tool failure and design novel algorithm addressing this context. Methods: The study tested the widely held but unproven hypothesis that tools fail to detect variants which lie in repeat regions. Publicly available 1000-Genomes dataset with experimentally validated variants was tested with SVDetect-tool for presence of true positives (TP) SVs versus false negative (FN) SVs, expecting that FNs would be overrepresented in repeat regions. Further, the novel algorithm designed to informatically capture the biological etiology of translocations (non-allelic homologous recombination and 3&ndashD; placement of chromosomes in cells –context) was tested using simulated dataset. Translocations were created in known translocation hotspots and the novel&ndashalgorithm; tool compared with SVDetect and BreakDancer. Results: 53% of false negative (FN) deletions were within repeat structure compared to 81% true positive (TP) deletions. Similarly, 33% FN insertions versus 42% TP, 26% FN duplication versus 57% TP and 54% FN novel sequences versus 62% TP were within repeats. Repeat structure was not driving the tool's inability to detect variants and could not be used as context. The novel algorithm with a redefined context, when tested against SVDetect and BreakDancer was able to detect 10/10 simulated translocations with 30X coverage dataset and 100% allele frequency, while SVDetect captured 4/10 and BreakDancer detected 6/10. For 15X coverage dataset with 100% allele frequency, novel algorithm was able to detect all ten translocations albeit with fewer reads supporting the same. BreakDancer detected 4/10 and SVDetect detected 2/10 Conclusion: This study showed that presence of repetitive elements in general within a structural variant did not influence the tool's ability to capture it. This context-based algorithm proved better than current tools even with half the genome coverage than accepted protocol and provides an important first step for novel translocation discovery in cancer genome.
ContributorsShetty, Sheetal (Author) / Dinu, Valentin (Thesis advisor) / Bussey, Kimberly (Committee member) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Arizona State University (Publisher)
Created2014
Description
In a 2004 paper, John Nagy raised the possibility of the existence of a hypertumor \emph{i.e.}, a focus of aggressively reproducing parenchyma cells that invade part or all of a tumor. His model used a system of nonlinear ordinary differential equations to find a suitable set of conditions for which these hypertumors exist. Here that model is expanded by transforming it into a system of nonlinear partial differential equations with diffusion, advection, and a free boundary condition to represent a radially symmetric tumor growth. Two strains of parenchymal cells are incorporated; one forming almost the entirety of the tumor while the much more aggressive strain
appears in a smaller region inside of the tumor. Simulations show that if the aggressive strain focuses its efforts on proliferating and does not contribute to angiogenesis signaling when in a hypoxic state, a hypertumor will form. More importantly, this resultant aggressive tumor is paradoxically prone to extinction and hypothesize is the cause of necrosis in many vascularized tumors.
appears in a smaller region inside of the tumor. Simulations show that if the aggressive strain focuses its efforts on proliferating and does not contribute to angiogenesis signaling when in a hypoxic state, a hypertumor will form. More importantly, this resultant aggressive tumor is paradoxically prone to extinction and hypothesize is the cause of necrosis in many vascularized tumors.
ContributorsAlvarez, Roberto L (Author) / Milner, Fabio A (Thesis advisor) / Nagy, John D. (Committee member) / Kuang, Yang (Committee member) / Thieme, Horst (Committee member) / Mahalov, Alex (Committee member) / Smith, Hal (Committee member) / Arizona State University (Publisher)
Created2014
Description
One theoretical research topic in organizational economics is the information issues raised in different organizations. This has been extensively studied in last three decades. One common feature of these research is focusing on the asymmetric information among different agents within one organization. However, in reality, we usually face the following situation. A group of people within an organization are completely transparent to each other; however, their characters are not known by other organization members who are outside this group. In my dissertation, I try to study how this information sharing would affect the outcome of different organizations. I focus on two organizations: corporate board and political parties. I find that this information sharing may be detrimental for (some of) the members who shared information. This conclusion stands in contrast to the conventional wisdom in both corporate finance and political party literature.
ContributorsWu, Zhenhua (Author) / Friedenberg, Amanda (Thesis advisor) / Manelli, Alejandro (Committee member) / Chade, Hector (Committee member) / Arizona State University (Publisher)
Created2014
Description
The processes of a human somatic cell are very complex with various genetic mechanisms governing its fate. Such cells undergo various genetic mutations, which translate to the genetic aberrations that we see in cancer. There are more than 100 types of cancer, each having many more subtypes with aberrations being unique to each. In the past two decades, the widespread application of high-throughput genomic technologies, such as micro-arrays and next-generation sequencing, has led to the revelation of many such aberrations. Known types and subtypes can be readily identified using gene-expression profiling and more importantly, high-throughput genomic datasets have helped identify novel sub-types with distinct signatures. Recent studies showing usage of gene-expression profiling in clinical decision making in breast cancer patients underscore the utility of high-throughput datasets. Beyond prognosis, understanding the underlying cellular processes is essential for effective cancer treatment. Various high-throughput techniques are now available to look at a particular aspect of a genetic mechanism in cancer tissue. To look at these mechanisms individually is akin to looking at a broken watch; taking apart each of its parts, looking at them individually and finally making a list of all the faulty ones. Integrative approaches are needed to transform one-dimensional cancer signatures into multi-dimensional interaction and regulatory networks, consequently bettering our understanding of cellular processes in cancer. Here, I attempt to (i) address ways to effectively identify high quality variants when multiple assays on the same sample samples are available through two novel tools, snpSniffer and NGSPE; (ii) glean new biological insight into multiple myeloma through two novel integrative analysis approaches making use of disparate high-throughput datasets. While these methods focus on multiple myeloma datasets, the informatics approaches are applicable to all cancer datasets and will thus help advance cancer genomics.
ContributorsYellapantula, Venkata (Author) / Dinu, Valentin (Thesis advisor) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Keats, Jonathan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Financing lease has bloomed as a new financing tool in China for the last several years. In this thesis I investigate the factors that influence China’s automobile financial leasing decisions by both lessors and lessees through market surveys. Based on Probit regression analysis of the data collected from 250 companies and 300 individuals, I find that a firm is more likely to use automobile financial leasing when its corporate tax rate is lower, growth potential is more stabilized, and profit is higher. It is also more likely to happen when a firm's long-term debt ratio and its degree of internationalization are higher. At the individual level, I find that the likelihood of individuals’ leasing decision is influenced by their risk preference, income level, and car price. Individuals’ gender, age and education level show no effect.
Using the analytic hierarchy process (AHP) analysis, I further find that financing costs, service value-added, and products diversity are the three most important competitive factors for the auto financial leasing service providers. This is the case for both the corporate and individual customers in the sample. By contrast, the factors of sales channel and government relationship are found to be much less important. Finally, through an in-depth case study of the leasing company Shanghai Auto Financial Leasing, I find that the key factors determining the customers’ credit default risk are interest rate and automobile type. I also investigate factors that influence business risk during the automobile procurement stage, at the selling stage, and toward the disposition stage. The managerial implications of the above results are discussed throughout the thesis.
Using the analytic hierarchy process (AHP) analysis, I further find that financing costs, service value-added, and products diversity are the three most important competitive factors for the auto financial leasing service providers. This is the case for both the corporate and individual customers in the sample. By contrast, the factors of sales channel and government relationship are found to be much less important. Finally, through an in-depth case study of the leasing company Shanghai Auto Financial Leasing, I find that the key factors determining the customers’ credit default risk are interest rate and automobile type. I also investigate factors that influence business risk during the automobile procurement stage, at the selling stage, and toward the disposition stage. The managerial implications of the above results are discussed throughout the thesis.
ContributorsLin, Zhen, Ph.D (Author) / Zhang, Anming (Thesis advisor) / Pei, Ker-Wei (Thesis advisor) / Chen, Hong (Committee member) / Arizona State University (Publisher)
Created2015