In this chapter we will discuss and motivate our choice of theoretical and research approach. We will then move on to describe how our data was collected and what method we used to analyze the data. Finally, there is a discussion around criticism towards the chosen method.
Positivism is a development from a school of thought originating from Aristoteles, the renaissance and the scientific progresses of the 17th and 18th centuries and regards absolute knowledge as the ideal. The term “positivism” was invented by the French sociologist Auguste Comte in the beginning of the 19th century. It refers to the development of positive, i.e. absolute knowledge. Comte’s aim was to develop a scientific methodology that was valid for all scientific disciplines. According to Comte, a man only have two sources to acquire knowledge- what is obtainable through our 5 senses and what we can conclude by applying reasoning and logic. Positivism has its foundation in quantifying and measuring data and to this apply logical reasoning to make it possible to test scientific theories and hypotheses. According to positivism, what scientists come up with or existing theories should be testable and either accepted or rejected (Eriksson & Wiedersheim-Paul, 1999).Positivism is usually associated with objectivity, quantifying technique and generalization (Alvesson & Deetz, 2000). This is the reason why positivism views science as the highest and most valid type of knowledge. Karl Popper, a man often associated with positivism, argues that the aim of the scientist is to search for true knowledge. Due to the fact that it is
almost impossible to conclude that a theory is true, Popper argues that scientists should instead aim to reject theories. It is simpler to conclude that a theory is false than vice versa and by rejecting theories the worst ones are taken out play so that only the ones that are most true are left to be evaluated. Popper has been criticized to advocate to rigorous testing of new theories, so that very few of them can withstand. Instead of rejecting them many argue that they should be enhanced and improved. Thomas Kuhn had a different view on scientific philosophy than Popper. Kuhn stated that improvements in science are due to revolutionizing discoveries rather than slow evolutionary processes that Popper advocates (Hult, 2003).The purpose of our thesis is to decide the trading patterns in volume around corporate announcements so a positivistic view is the given choice. Our approach is to give answer to research problems by either rejecting or accepting hypotheses.
According to Lekvall and Wahlbin (2001) a standpoint has to be taken whether to use a quantitative or a qualitative approach in the study. Because of the characteristics of this study our opinion is that a quantitative approach is best suited. The purpose is to make generalized conclusions from a big sample. With the quantitative data we are able to perform statistical investigations used to make statements about the population. This argumentation is supported by Bell (2000); quantitative surveys gather data and enter deeply into relations between different sets of data. They use scientific methods that can result in conclusions that can be quantifiable and possible to generalize. The other method is the qualitative approach that tries to find out how people experience their environment. Here the goal is to get insight and not to analyze statistics. The method is therefore used to explain a phenomenon with examples.
There are three ways to draw conclusion within a positivistic approach, by induction, deduction or a combination of both. With an inductive method empirical data are collected,which are then processed in order to come up with a new theory. The aim of out thesis is confirmatory so the inductive approach is rejected. Deduction implies that based on existing theories conclusions are drawn (Eriksson & Wiedersheim-Paul, 1999). The thesis is made in such a way that with help from existing theories about trading volume in information asymmetries form logical hypotheses about the subject so that our results finally can be compared with existing theory. Due to this, a deductive approach is selected in the spirit of Karl Popper.
1.2 Research problems
1.2.1 Research problem 1: The trading volume should decrease before a scheduled announcement.
1.2.2 Research problem 2: There should be a corresponding increase in trading volume after the scheduled announcement is released
1.2.3 Research problem 3: The trading volume should increase before an unscheduled announcement
1.2.4 Research problem 4: All the assumed effects should be greater on smaller firms.
2.1 Theoretical approach
2.2 Research approach
2.5 Summary of technical method
2.6 Data Collection
2.7 Analyzing data
2.7.1 Preliminary study
2.7.2 Calculating trading volume
2.7.3 Analyzing trading volume
2.7.4 Robustness tests
2.8 Reliability and validity
3 Theoretical framework
3.1 The importance of trading volume
3.3 Trading volume in information asymmetries
3.3.1 Trading volume prior to scheduled announcements
3.3.2 Trading volume after scheduled announcements
3.3.3 Trading volume around unscheduled announcements
3.4 Critique of the theoretical framework.
4 Previous Studies
4.1 Trading Volume, Information Asymmetry, and Timing
5 Empirical findings
5.1 Preliminary study
5.2 Main study
5.2.1 Scheduled announcements
5.2.2 Unscheduled announcements
5.3 Comparison A-listan and O-listan
5.3.1 Scheduled Announcement
5.3.2 Unscheduled Announcements
5.4 Robustness check
5.4.1 Scheduled announcements
5.4.2 Unscheduled Announcements
6.1 Comparison of studies
6.2 The result’s relation to theory
7 Conclusion and Final Discussion
7.2 Final discussion
7.3 Suggestions for further studies