Have new fraud and earnings manipulation detecting tools improved confidence in capital markets? To answer this question, I will provide a survey of tools currently used to detect fraud and earnings manipulation, discuss the effects of fraud and earnings manipulation, and look at changes in historical records of consumer confidence and investment returns as a test to our question.

Fantasy football is a game derived from America’s National Football League and involves players managing “teams” of fantasy football players. Given that the game contains elements of value, risk, and reward, this project aims to draw parallels between fantasy football and Modern Portfolio Theory, a well-regarded theory describing portfolio construction and performance in financial markets. This hypothesis is tested through a simulation of the 2019 – 2020 fantasy football season using this strategy; a sample team is generated, the team is adjusted as per the rules outlined in the risk-reducing and value-preserving strategy, and the results are tabulated per the team’s fantasy football scoring output. The results show that a volatility-reducing strategy fails to achieve a consistent, good performance from the fantasy team portfolio, but can result in a relatively successful season. Key issues to consider in this outcome are the low volume of data, the high volatility and situational nature of the underlying statistics from which fantasy scoring is derived, and the inefficiency of financial markets. The value of this research demonstrates that strict algorithmic, numerical, or technical methods are insufficient to succeed in fantasy football, and that information availability, access, and speed, along with a significant allotment of luck, are needed to succeed. The implication for the financial field is that the rules and theories formulated for it are based on certain crucial assumptions such as a centralized supply and demand for securities, an objective theory of value, and efficiency of markets, which cannot be translated directly to fantasy football.

Purpose: This paper serves to illustrate the risks that affect multinational organizations during this new era of global production and increased supply chain complexity. This paper also strives to showcase the benefits of conducting a Network Optimization analysis on a firm’s logistics system including but not limited to reducing the impact of supply chain market and operational risk, improving efficiency, and increasing cost savings across the organization. Approach: This paper will have two main sections beginning with an in depth look into the theory supporting supply chain logistics network optimizations. Through this literature review, the best practices in the industry will be compared to risk mitigation methodology to determine an analytical process that can be applied to companies considering conducting a network optimization. The second stage of this paper takes a clinical look at the aerospace industry and the implementation process of a Logistics Network Optimization at an industry leader to ultimately recommend additional considerations they should implement into their process. Recommendation: To ensure the effective adoption of a network optimization in the aerospace industry, and other manufacturing industries, the maintenance of logistics data and creation of long term 3PL partnerships are needed for success. It is also important to frame a network optimization not as an operational project, but rather a critical business process aimed to mitigate risk within the supply chain though a four-stage risk identification process.

Amidinates and guanidinates are promising supporting ligands in organometallic and coordination chemistry, highly valued for their accessibility, tunability, and comparability with other popular anionic N-chelating hard donor ligands like β-diketiminates. By far the most powerful way to access these ligands involves direct metal-nucleophile insertion into N,N’- substituted carbodiimides. However, the majority of reported examples require the use of commercially accessible carbodiimide peptide coupling reagents with simple alkyl substituents leading to low variation in potential substituents. Presented here is the design, synthesis, and isolation of a novel N,N’-bis[3-(diphenylphosphino)propyl]carbodiimide via an Aza-Wittig reaction between two previously described air stable substrates. At room temperature, 3-(diphenylphosphanyl-borane)-propylisocyanate was added to N-(3-(diphenylphospino)propyl)-triphenylphosphinimine, leading to product formation in minutes. One-pot phosphine-borane deprotection, followed by simple filtration of the crude mixture through a small, basic silica plug using pentane and diethyl ether granted the corresponding carbodiimide in high purity and yield (over 70%), confirmed by 1H, 13C, and 31P NMR spectroscopy. In addition to accessing different central carbon substituents, modification of phosphine substituents should be easily accessible through minor variations in the synthesis. With these precursors, anionic amidinates and guanidinates capable of κ4 -N,N,P,P-coordination may be accessed. The ability of the labile phosphine arms to associate and dissociate may facilitate catalysis. Thus, this carbodiimide provides a tunable, reliable one step precursor to novel substituted amidinates and guanidinates for homogeneous transition metal catalysis.

This project analyzed the utilization rates of respective factories for Company X compared to the Manufacturing Utilization Policy to identify discrepancies in the policy baseline trigger and when the factories are ramped to full utilization. The current policy bases three different factory types, ATM, DS/DP, and FSM all on the same baseline of FSM. This was originally set in place from a lack of sufficient data for the other factories and now that there is enough data to identify the utilization rates of each factory type, a more suitable baseline for each can be determined. If continuing to use the FSM baseline, Company X will be designating certain factories as underutilized, triggering the manufacturing utilization policy and inefficiently allocating the building expenses, thus increasing the cost per unit of products produced.

In this paper, I cover the background and economic history of green buildings, including four case studies. Based on this exploration, I find that green roofs and walls are best suited to dense, highly paved cities with little capacity to expand their sewer systems. Green infrastructure is best suited for stormwater management to avoid combined sewer overflow (CSO) pollution and managing urban heat island (UHI) effects, while at the same time providing many positive externalities for people and the environment. Green buildings take those benefits and fit them into a smaller area (on roofs and walls), which is most applicable where tearing up pavement to provide more ground-level green space and expanding the sewer systems would be too costly.