Mathematics (Bryn Mawr)http://hdl.handle.net/10066/140352018-03-24T18:03:36Z2018-03-24T18:03:36ZPost-Earnings Announcement Drift and the Impact of Loss Averse InvestorsCummings, Johnhttp://hdl.handle.net/10066/141792018-02-21T13:44:50Z2014-01-01T00:00:00ZPost-Earnings Announcement Drift and the Impact of Loss Averse Investors
Cummings, John
Despite being a highly documented phenomenon, the underlying cause of the post-earnings announcement drift is presently unknown. This study tests whether the tendency for investors to hold losses and realize gains--known as the disposition effect--can partially explain the existence of the post-earnings announcement drift anomaly in equity markets. The data for this paper consists of over six thousand companies from 1992 to 2012 for a total of over 140,000 quarterly earnings announcements. This study finds that the post-earnings announcement drift was most severe before 1998. During this period (1992-1998), a trading strategy that purchased (sold) stocks in the highest (lowest) decile of earnings surprises would have earned an annualized abnormal return of 32% (versus 4% for the later period). Furthermore, results show that the post-earnings announcement drift does not occur when the disposition effect is weakest, implying that the disposition effect plays an important role in the drift.
2014-01-01T00:00:00ZA Development of Basic Stochastic Calculus and its ApplicationsAhsin, Tahahttp://hdl.handle.net/10066/141112016-12-12T15:45:38Z2014-01-01T00:00:00ZA Development of Basic Stochastic Calculus and its Applications
Ahsin, Taha
This paper looks to develop an understanding of stochastic calculus through basic measure theory. It begins by observing the relationships built between set theory and real-valued functions, using propositions related to ordering infinite sets through both subset placements as well as measurable value, subsequently establishing properties of measure spaces. It proceeds by looking at particular measure spaces, that is probability spaces, and properties related to set operations, such as unions, intersections, as well as complements, as it relates to probabilities. This analysis develops the concept of measurable functions in order to open the discussion into random variables on probability spaces. By building the properties of these functions, we derive various subcategories of random variables based on characteristics of their being simple, bounded, positive, arbitrary, and so on. Finally, we conclude the paper with application to financial mathematics.
2014-01-01T00:00:00Z