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4709219: Research Methods I - IFS - specialization Part

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Semester:SS 19
Type:Lecture
Language:English
Scheduled in semester:4
Semester Hours per Week / Contact Hours:30.0 L / 22.5 h
Self-directed study time:67.5 h

Module coordination/Lecturers

Curricula

Bachelor's degree programme in Business Administration (01.09.2012)

Description

  • Introduction to R
  • Collection of Financial Data from Financial Databases
  • Descriptive and Inferential Statistics for Financial Data (using R)
  • Modelling and Forecasting Financial Timeseries (using R)
  • Developing and formulating hypotheses
  • Collecting primary data using experiments
  • Collecting primary data using interviews or questionnaires
  • Sample selection

Qualifications

    • know how to conduct financial research and analysis
    • know and learn to use specific financial databases
    • name and understand descriptive statistics that are of relevance in financial research
    • learn and understand the properties of linear regression and time series analysis
    • understand and explain the different objectives of qualitative and quantitative research
    • understand the importance of sample selection as well as different sampling strategies
    • know and understand the basic principles of experimental design
    • know and understand the basic principles of designing surveys and interviews
    • know how to gather and analyse data
    • choose the correct method for an analysis
    • use "R" as a software package to analyse data
    • consider assumptions underlying specific statistical methods/models
    • find suitable approaches to statistically address given research questions
    • apply the methods learnt within a statistical software package (here: R)
    • interpret empirical/statistical findings prudently
    • can formulate testable hypotheses
    • can choose and motivate appropriate data collection methods for given research objectives
    • can choose and motivate appropriate sampling strategies for given research objectives
    • are aware of potential biases and confounders in primary data collection
    • listen carefully, read and repeat, practice until they understand the logic and mathematics behind models
    • work together and motivate peers who tend to give up as a reaction to the difficulty of mathematical problems
    • take responsibility and organize/explain their solution to others who have problems and tend to give up
    • comprehend arguments that are based on divergent epistemological, and ontological assumptions
    • understand and critically discuss the arguments of fellow students
    • understand the flaws and problems of fellow students, reaction without offense
    • reflect and question their own research philosophy
    • acknowledge the importance of diversity in academic thinking

Lectures Method

Lecture

Literature

Brooks, C. (2014). Introductory econometrics for finance. Cambridge university press.
DeFusco, R. A., McLeavey, D. W., Anson, M. J., Pinto, J. E., & Runkle, D. E. (2015). Quantitative investment analysis. John Wiley & Sons.
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. John Wiley & Sons.

Exam Modalities

  • written examination

Dates

DatumZeitRaum
20.02.201910:00 - 11:30S3
27.02.201910:00 - 11:30S3
06.03.201910:00 - 11:30S3
13.03.201910:00 - 11:30S3
20.03.201910:00 - 11:30S3
27.03.201910:00 - 11:30S3
03.04.201910:00 - 11:30S3
10.04.201910:00 - 11:30S3
17.04.201910:00 - 11:30S3
08.05.201910:00 - 11:30S3
15.05.201910:00 - 11:30S3
22.05.201910:00 - 11:30S3
29.05.201910:00 - 11:30S3

Exams

  • PWW-BA-12_Research Methods I - IFS - Specialization - VO (SS 19, bewertet)
  • PWW-BA-12_HT_Research Methods I - IFS - Specialization - VO (SS 19, bestätigt)
  • PWW-BA-12_Research Methods I - IFS - Specialization - VO (WS 19/20, bestätigt)