Assessment Brief 2024/2025
Assignment Information
Course Code
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ACCFIN5231
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Course Title
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Big Data Analytics
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Weighting
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100%
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Question release date
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Friday 8th November 2024
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Submission date:
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Friday 20th December 2024
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Grades and Feedback to be released on:
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Word limit
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3000 (+/- 10%) Refer to word limit policy
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Action to be taken if word limit is exceeded
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Marks will be reduced.
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1. QUESTION/ DESCRIPTION OF ACTIVITY
Individual Assignment Question
As a quantitative analyst specializing in big data analytics and machine learning, your task is to leverage advanced data techniques to extract valuable insights from financial datasets. Your manager has tasked you with writing a 3,000-word research report on a finance-related topic that uses big data techniques to explore complex financial relationships. Potential topics include investigating the relationship between financial variables, analysing capital structure management, designing risk management strategies, implementing trading strategies, optimizing investment portfolios, or forecasting financial metrics like returns and volatilities.
To ensure a comprehensive analysis, your report should adhere to six key sections:
Introduction
Outline the research problem and objectives.
Discuss the significance of the study, including how big data analytics can help in uncovering new insights that traditional methods might overlook.
Literature Review
Review both theoretical and empirical papers relevant to your topic.
Cover studies that use traditional financial methods as well as big data analytics to highlight the advantages of your approach.
Data and Empirical Analysis
Describe the data collection process, including the source and nature of your dataset.
Detail your methodology, focusing on how big data techniques (e.g., machine learning models, predictive analytics, or sentiment analysis) are used to analyze the data.
Present the results of your empirical analysis, using appropriate statistical tools and visualizations to extract meaningful business insights.
Conclusion
Summarize your key findings and discuss the implications for the finance field.
Provide suggestions for further research, emphasizing how big data can continue to uncover new opportunities in finance.
References
Include a complete list of all sources cited, ensuring that your report is grounded in existing literature and empirical studies.
Appendix (if needed)
Include supplementary materials such as datasets, graphs, or code to support your analysis, ensuring transparency and reproducibility of your results.
Throughout your report, ensure each section is concise and contributes to the overall clarity and coherence of your research. The use of big data techniques will not only enhance your empirical analysis but will also provide deeper insights into financial decision-making and strategy formulation.
Please consider ethical issues when you conduct your research.
Intended Learning Outcomes being assessed
1. Demonstrate knowledge of advanced aspects of big data analytics
2. Apply appropriate machine learning techniques to analyse big data sets
3. Assess the statistical significance of data mining results
4. Utilize statistical packages (R and Python) to perform. basic data mining tasks on big data
2. ASSESSMENT RUBRIC/ CRITERIA
Criteria
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Excellent
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Very Good
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Good
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Satisfactory
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Weak
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Selection of research questions
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Innovative, meaningful topic and appropriate by using big data techniques
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Meaningful topic and appropriate by using big data techniques
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Traditional topic and appropriate by using big data techniques
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Traditional topic; no differences by using traditional or big data techniques
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Not appropriate by using big data techniques
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Big data techniques
and analysis
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Advanced and appropriate technique; comprehensive and robust results
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Appropriate technique; comprehensive and robust results
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Appropriate technique; comprehensive results
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Appropriate technique; adequate results
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Inappropriate using the techniques
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Writing and interpretation of the results
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Clear structure, good understanding of financial theories and be able to interpret the economic meaning of the results. Be able to compare it with previous literature.
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Clear structure, good understanding of financial theories and be able to
interpret the economic meaning of the results.
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Good understanding of financial theories and be able to interpret the economic meaning of the results.
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Be able to interpret the economic meaning of the results.
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Not able to correctly interpret the economic meaning of the results.
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