Yes / This paper investigates the mean-variance relation during different time periods within trading days. We reveal that there is a positive mean-variance relation when the stock market is closed (i.e., overnight), but the positive relation is distorted when the market is open (i.e., intraday). The evidence offers a new explanation for the weak risk-return tradeoff in stock markets.

published_or_final_version / abstract / China Development Studies / Master / Master of Arts

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Thesis advisor: Tracy Regan / This study analyzes the response of pharmaceutical firms’ stock prices to the release of information regarding successful Phase III clinical studies and final FDA marketing approval. I employ an event study methodology to show that positive abnormal returns occur at these drug development stages, and that larger abnormal returns occur over a three-day window surrounding a sample of successful Phase III trial announcements in comparison to a sample of FDA approval announcements. To my knowledge, all previous literature of this kind has compared a random sample of firms making Phase III announcements to a random sample of FDA approval announcements. This study advances drug development literature by conducting a second set of event studies that compares the abnormal returns of the same drugs at the two drug development stages, and it finds that controlling for the unique characteristics of the drugs analyzed in event studies leads to a smaller difference in returns at the two drug development stages. The drugs selected for analysis were taken from IMS Health’s lists of the top 100 (or 200) best-selling pharmaceuticals from 2003 to 2010. They were split into 13 therapeutic classes, such as drugs for cardiovascular ailments and drugs for respiratory ailments. Regression analysis was conducted on the returns of the three-day window to find a positive relationship between the FDA approval of alimentary and cardiovascular drugs and stock price increases for larger pharmaceutical firms and the approval of nervous system drugs and stock price increases for smaller pharmaceutical firms. To my knowledge, this is the first study to show these relationships. / Thesis (BA) — Boston College, 2015. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Economics.

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The diploma thesis examines the implicit pension debt in the fifteen EU countries. The Holzmann et al. (2011) methodology is applied to show the impact of population ageing on the pension systems in the EU. The implicit pension debts demonstrate the considerable hidden debt burden in the all fifteen countries. The implicit pension debts range in the interval from 47 % of GDP for the Czech Republic to 906 % for Greece. Nine of the analyzed countries record the implicit pension debts in the interval 100 - 300 % of GDP. The sensitivity analysis and the comparison with other studies confirm our findings. The thesis points out sizeable imbalances among the particular countries, genders and age cohorts.

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This research is to improve the efficiency of present prediction factors. It has been tested that many factors have prediction power toward stocks returns. Although the prediction power is not stable, the factors are still valuable. This research analyzes preceding factors by neural network in order to make better use of these factors. Besides, we examine 15 companies respectively and compare the results between neural network and liner regression of those companies. Data are divided into training period and prediction period. We use data of training period to build up our model and test the model by the data from prediction period to verify the prediction powers of the models. The results show neural network has better solution compared to liner regression in both training and prediction period. Neural network is more precision and has less prediction error.