Thesis Writing
TO-WHOM: MSc in Applied Statistics, Department of Statistics, University of Sri Jayewardenepura
Dr Thiyanga S. Talagala
August 21, 2021
Thesis Writing
- Physical space
Thesis Writing
Physical space
Calendar space
Thesis Writing
Physical space
Calendar space
Mental space
Focus
- Application
Talagala, T. (2015). Distributed lag nonlinear modelling approach to identify relationship between climatic factors and dengue incidence in Colombo District, Sri Lanka. Epidemiology, Biostatistics and Public Health, 12(4).
- Methodological framework
Montero-Manso, P., Athanasopoulos, G., Hyndman, R. J., & Talagala, T. S. (2020). FFORMA: Feature-based forecast model averaging. International Journal of Forecasting, 36(1), 86-92
Focus (cont.)
- Development and application of a methodological framework
Talagala, Thiyanga S., Feng Li, and Yanfei Kang. "FFORMPP: Feature-based forecast model performance prediction." International Journal of Forecasting (2021).
Types of Theses
Traditional thesis
Thesis by publication
Types of Theses
Thesis by publication
Traditional thesis
Thesis Structure
Abstract and Keywords
Table of Contents
List of Figures
List of Tables
List of Abbreviations
Declaration
Acknowledgements
Introduction
Literature Review
Methodology
Results
Discussion and Conclusions
Bibliography or list of references
Appendix
Thesis Structure
Abstract and Keywords
Table of Contents
List of Figures
List of Tables
List of Abbreviations
Declaration
Acknowledgements
Introduction
Literature Review
Methodology
Results
Discussion and Conclusions
Bibliography or list of references
Appendix
Abstract
Do you want to make a good first impression?
A concise summary of the entire thesis
First part that most people will read
The last thing that you write
Chapter 1: Introduction
1.1 Background of the study
1.2 Objectives of the study
1.3 Significance of the study
1.4 Thesis outline
Chapter 1: Introduction
1.1 Background of the study
1.2 Objectives of the study
1.3 Significance of the study
1.4 Thesis outline
1.1 Background of the study
- Give an overview of your research topic
1.1 Background of the study
Give an overview of your research topic
Outline current methods/ brief review of current knowledge
1.1 Background of the study
Give an overview of your research topic
Outline current methods/ brief review of current knowledge
Motivation for your research: Evaluate current methods/ knowledge
Show there is a need to be further research
1.1 Background of the study
Give an overview of your research topic
Outline current methods/ brief review of current knowledge
Motivation for your research: Evaluate current methods/ knowledge
Show there is a need to be further research
Introduce your research problem
1.1 Background of the study
Give an overview of your research topic
Outline current methods/ brief review of current knowledge
Motivation for your research: Evaluate current methods/ knowledge
Show there is a need to be further research
Introduce your research problem
State research aims/ objectives
1.1 Background of the study
Give an overview of your research topic
Outline current methods/ brief review of current knowledge
Motivation for your research: Evaluate current methods/ knowledge
Show there is a need to be further research
Introduce your research problem
State research aims/ objectives
Outline the order of the information in the chapter
Exercise 1
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019). Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators. International Journal of Forecasting, 35(4), 1250-1262.
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"The VIX index represents the market’s estimate of the future volatility of the S&P 500 over the next thirty days. It provide a benchmark of the short-term expected volatility, as futures and options contracts can be inscribed on (see Whaley, 2008). In fact, implied volatility reflects the market makers’ point of view about the expected volatility of the futures’ underlying assets. Therefore, since market makers are often among the most informed agents, implied volatility should outperform the historical one in forecasting the realized volatility of the futures’ underlying asset (Shu and Zhang, 2012)."
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"The VIX index represents the market’s estimate of the future volatility of the S&P 500 over the next thirty days. It provide a benchmark of the short-term expected volatility, as futures and options contracts can be inscribed on (see Whaley, 2008). In fact, implied volatility reflects the market makers’ point of view about the expected volatility of the futures’ underlying assets. Therefore, since market makers are often among the most informed agents, implied volatility should outperform the historical one in forecasting the realized volatility of the futures’ underlying asset (Shu and Zhang, 2012)."
Give an overview of your research topic: state the general topic - define terms
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"The VIX index represents the market’s estimate of the future volatility of the S&P 500 over the next thirty days. It provide a benchmark of the short-term expected volatility, as futures and options contracts can be inscribed on (see Whaley, 2008). In fact, implied volatility reflects the market makers’ point of view about the expected volatility of the futures’ underlying assets. Therefore, since market makers are often among the most informed agents, implied volatility should outperform the historical one in forecasting the realized volatility of the futures’ underlying asset (Shu and Zhang, 2012)."
Give an overview of your research topic: Narrow down your topic
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"The VIX index represents the market’s estimate of the future volatility of the S&P 500 over the next thirty days. It provide a benchmark of the short-term expected volatility, as futures and options contracts can be inscribed on (see Whaley, 2008). In fact, implied volatility reflects the market makers’ point of view about the expected volatility of the futures’ underlying assets. Therefore, since market makers are often among the most informed agents, implied volatility should outperform the historical one in forecasting the realized volatility of the futures’ underlying asset (Shu and Zhang, 2012).**"
Give an overview of your research topic: Ideas/ arguments are linked together.
Exercise 1 (cont.): Paragraph 2
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"Despite the importance and the common use of VIX as a volatility measure, only little attention has been paid to the problem of forecasting it. In particular, the few works on the subject show that the VIX is to some extent predictable. This finding, albeit theoretically interesting, is not necessarily helpful for traders, because VIX is tradable only as derivative contracts, whose dynamics does not always follow that of the VIX index. For example, Asensio (2013), Degiannakis (2008), Kostantinidi et al. (2008), Konstantinidi and Skiadopoulos (2011), who are among the few authors focusing on VIX futures (henceforth referred to as VXFs), highlight only a weak evidence of statistical predictability and experience a low level of profitability when implementing trading strategies based on VIX forecasts. The overall picture is not encouraging for investors: on the one hand, there is evidence that VIX is predictable; on the other, it seems very hard to trade VXFs by learning from the (predicted) VIX dynamics. "
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"Despite the importance and the common use of VIX as a volatility measure, only little attention has been paid to the problem of forecasting it. In particular, the few works on the subject show that the VIX is to some extent predictable. This finding, albeit theoretically interesting, is not necessarily helpful for traders, because VIX is tradable only as derivative contracts, whose dynamics does not always follow that of the VIX index. For example, Asensio (2013), Degiannakis (2008), Kostantinidi et al. (2008), Konstantinidi and Skiadopoulos (2011), who are among the few authors focusing on VIX futures (henceforth referred to as VXFs), highlight only a weak evidence of statistical predictability and experience a low level of profitability when implementing trading strategies based on VIX forecasts. The overall picture is not encouraging for investors: on the one hand, there is evidence that VIX is predictable; on the other, it seems very hard to trade VXFs by learning from the (predicted) VIX dynamics. "
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"Despite the importance and the common use of VIX as a volatility measure, only little attention has been paid to the problem of forecasting it. In particular, the few works on the subject show that the VIX is to some extent predictable. This finding, albeit theoretically interesting, is not necessarily helpful for traders, because VIX is tradable only as derivative contracts, whose dynamics does not always follow that of the VIX index. For example, Asensio (2013), Degiannakis (2008), Kostantinidi et al. (2008), Konstantinidi and Skiadopoulos (2011), who are among the few authors focusing on VIX futures (henceforth referred to as VXFs), highlight only a weak evidence of statistical predictability and experience a low level of profitability when implementing trading strategies based on VIX forecasts. The overall picture is not encouraging for investors: on the one hand, there is evidence that VIX is predictable; on the other, it seems very hard to trade VXFs by learning from the (predicted) VIX dynamics. "
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"Despite the importance and the common use of VIX as a volatility measure, only little attention has been paid to the problem of forecasting it. In particular, the few works on the subject show that the VIX is to some extent predictable. This finding, albeit theoretically interesting, is not necessarily helpful for traders, because VIX is tradable only as derivative contracts, whose dynamics does not always follow that of the VIX index. For example, Asensio (2013), Degiannakis (2008), Kostantinidi et al. (2008), Konstantinidi and Skiadopoulos (2011), who are among the few authors focusing on VIX futures (henceforth referred to as VXFs), highlight only a weak evidence of statistical predictability and experience a low level of profitability when implementing trading strategies based on VIX forecasts. The overall picture is not encouraging for investors: on the one hand, there is evidence that VIX is predictable; on the other, it seems very hard to trade VXFs by learning from the (predicted) VIX dynamics. "
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"Despite the importance and the common use of VIX as a volatility measure, only little attention has been paid to the problem of forecasting it. In particular, the few works on the subject show that the VIX is to some extent predictable. This finding, albeit theoretically interesting, is not necessarily helpful for traders, because VIX is tradable only as derivative contracts, whose dynamics does not always follow that of the VIX index. For example, Asensio (2013), Degiannakis (2008), Kostantinidi et al. (2008), Konstantinidi and Skiadopoulos (2011), who are among the few authors focusing on VIX futures (henceforth referred to as VXFs), highlight only a weak evidence of statistical predictability and experience a low level of profitability when implementing trading strategies based on VIX forecasts. The overall picture is not encouraging for investors: on the one hand, there is evidence that VIX is predictable; on the other, it seems very hard to trade VXFs by learning from the (predicted) VIX dynamics. "
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"Despite the importance and the common use of VIX as a volatility measure, only little attention has been paid to the problem of forecasting it. In particular, the few works on the subject show that the VIX is to some extent predictable. This finding, albeit theoretically interesting, is not necessarily helpful for traders, because VIX is tradable only as derivative contracts, whose dynamics does not always follow that of the VIX index.For example, Asensio (2013), Degiannakis (2008), Kostantinidi et al. (2008), Konstantinidi and Skiadopoulos (2011), who are among the few authors focusing on VIX futures (henceforth referred to as VXFs), highlight only a weak evidence of statistical predictability and experience a low level of profitability when implementing trading strategies based on VIX forecasts. The overall picture is not encouraging for investors: on the one hand, there is evidence that VIX is predictable; on the other, it seems very hard to trade VXFs by learning from the (predicted) VIX dynamics. "
Exercise 1 (cont.): Paragraph 3
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"In the present paper, in order to fill this “forecasting gap”, we present a new approach for modelling VXF returns that provides a significant amount of predictability and allows us to build profitable trading strategies. "
Ballestra, L. V., Guizzardi, A., & Palladini, F. (2019), IJF
"In the present paper, in order to fill this “forecasting gap”, we present a new approach for modelling VXF returns that provides a significant amount of predictability and allows us to build profitable trading strategies."
Introduce the research problem
Exercise 2
Saha, M., Santara, A., Mitra, P., Chakraborty, A., & Nanjundiah, R. S. (2021). Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model. International Journal of Forecasting, 37(1), 58-71
Saha Moumita and others, 2021, IJF
"The Indian summer monsoon is a complex climatic phenomenon. It refers to the rainfall occurring between June and September, which contributes to more than 75% of the aggregate annual rainfall of the country. The India Meteorological Department defines the monsoon process as the seasonal reversal of the wind direction down the shores of the Indian Ocean; blowing from the southwest direction. "
Saha Moumita and others, 2021, IJF
"The Indian summer monsoon is a complex climatic phenomenon. It refers to the rainfall occurring between June and September, which contributes to more than 75% of the aggregate annual rainfall of the country. The India Meteorological Department defines the monsoon process as the seasonal reversal of the wind direction down the shores of the Indian Ocean; blowing from the southwest direction."
Saha Moumita and others, 2021, IJF
"The Indian summer monsoon is a complex climatic phenomenon. It refers to the rainfall occurring between June and September, which contributes to more than 75% of the aggregate annual rainfall of the country. The India Meteorological Department defines the monsoon process as the seasonal reversal of the wind direction down the shores of the Indian Ocean; blowing from the southwest direction."
Saha Moumita and others, 2021, IJF
"The Indian summer monsoon is a complex climatic phenomenon. It refers to the rainfall occurring between June and September, which contributes to more than 75% of the aggregate annual rainfall of the country. The India Meteorological Department defines the monsoon process as the seasonal reversal of the wind direction down the shores of the Indian Ocean; blowing from the southwest direction."
Saha Moumita and others, 2021, IJF
"The Indian summer monsoon is a complex climatic phenomenon. It refers to the rainfall occurring between June and September, which contributes to more than 75% of the aggregate annual rainfall of the country. The India Meteorological Department defines the monsoon process as the seasonal reversal of the wind direction down the shores of the Indian Ocean; blowing from the southwest direction."
...
"The monsoon has a significant impact on agriculture, growth of flora-fauna, hydro-electricity production, freshwater renewal, and on the overall economic growth of the country."
Chapter 1: Introduction
1.1 Background of the study
1.2 Objectives of the study
1.3 Significance of the study
1.4 Thesis outline
1.2 Objectives and aims of the study
Aim: what you hope to achieve.
Objective: the action(s) you will take in order to achieve the aim.
The main research objective
Specific aims of your research
Objectives should be SMART
Specific
Measureable
Achievable
Realistic
Time constrained
Example
Comparison of Plant Species and Soil Traits at Sites Where Physaria ludoviciana (Silvery Bladderpod) is Present or Absent in Three States
"The overall goal of this research is to understand biogeographical and environmental factors that may explain why Physaria ludoviciana is present in some sand prairies but absent from the biological composition in others. For this project, areas where P. ludoviciana is growing will be compared to nearby or parallel areas where it is absent from the community structure in three different states (IL, MN, and NE). The specific objectives are to compare:
a) Plant species composition, and
b) Soil traits (texture, calcium, magnesium, manganese, zinc, potassium, boron, copper, iron, sodium, phosphorus, sulfur, cation exchange capacity, organic matter, buffer pH and soil pH). "
source: https://www2.illinois.gov/dnr/grants/documents/wpfgrantreports/2008010w.pdf
Chapter 1: Introduction
1.1 Background of the study
1.2 Objectives of the study
1.3 Significance of the study
1.4 Thesis outline
1.3 Significance of the study
Why your research is needed
Who benefits?
How that specific audience will benefit from its findings
What contribution will your study make to the literature or to the field?
Example
Konarasinghe, K. M. U. B. (2021). Forecasting COVID-19 Outbreak in the Philippines and Indonesia. Journal of New Frontiers in Healthcare and Biological Sciences, 2(1), 1-19.
Forecasting COVID-19 Outbreak in the Philippines and Indonesia
"The results of this study could be a tool to be proactive and protect Indonesia and the Philippines from the outbreak of the pandemic. It could be useful to develop various strategies and policies to control the spread of the pandemic. The results of this study would be useful to work out the health care and medical resources with minimum waste. Base on the results the authorities can decide the lockdown schedules and impose the supply delivery systems to attenuate the movement of the general public (Konarasinghe, 2020). The results of this study could be another guide for business. They can decide how to improve their business functions to gain maximum benefits and retain their external stakeholders. "
]
Chapter 1: Introduction
1.1 Background of the study
1.2 Objectives of the study
1.3 Significance of the study
1.4 Thesis outline
1.4 Thesis outline
The remaining portion of this thesis is structured as follows: Chapter 2 provides a detailed overview of the literature. Chapter 3 illustrates the methodology used by the thesis. .....
Literature Review
To review the literature means to be able to identify:
What has been established
Areas of controversy
Emerging trends and new approaches
Landmark papers/ Key references
Literature review matrix
Chapter 2: Literature Review
Introduction
- Organisational pattern of the literature review
Body paragraphs
Historical background
Methodologies
What contributions do they make to the field?
Body paragraphs (cont.)
- The limitations of a study/the gaps in the study.
Conclusions
The main agreement and disagreement
What you have drawn from reviewing the literature review?
Literature review
Chronological
Thematic
Methodological
Chronological
According to when they were published
- The development of the field over time
Talagala, T. S., Hyndman, R. J., & Athanasopoulos, G. (2018). Meta-learning how to forecast time series. Monash Econometrics and Business Statistics Working Papers, 6, 18.
Thematic
Reviews of literature are organized around a topic or issue, rather than the progression of time.
Different aspects of the topic
Methodological
- Compare the results that emerge from using different methods
Chapter 3: Methodology
Research design
Sources of Data
Sampling design
Statistical software
Data analysis/ Statistical methods
Chapter 4: Results
Reporting results is not enough
Establish the connections between the patterns that emerge from your analysis and your research questions
Relate those connections to the existing research, theory and knowledge
Data Visualization
Cognitive Principles
Less cognitive effort to read the chart (what is presented) and save the time to think about the content of the chart
- Good visualizations take advantage of the human visual system's ability to process information with little effort.
Cognitive Principles
Less cognitive effort to read the chart (what is presented) and save the time to think about the content of the chart
- Good visualizations take advantage of the human visual system's ability to process information with little effort.
Preattentive graph perception
It requires no conscious effort from the viewer to do understand what is presented through the design. It's automated and takes between 200-500 milliseconds to complete in the spatial memory.
Cognitive Principles
Less cognitive effort to read the chart (what is presented) and save the time to think about the content of the chart
- Good visualizations take advantage of the human visual system's ability to process information with little effort.
Preattentive graph perception
It requires no conscious effort from the viewer to do understand what is presented through the design. It's automated and takes between 200-500 milliseconds to complete in the spatial memory.
(Spatial working memory entails the ability to keep spatial information active in working memory over a short period of time.)
Preattentive visual properties
Color
Form: collinearity, curvature, marks, shape, size, spatial grouping, length, width, breadth
Spatial position: 2D, 3D
Movement: flicker, movement
These are processed in our sensory memory without our conscious thoughts (without having knowledge of something).
Cognitive principles
1. Proximity
2. Similarity
3. Common region
4. Common fate
4. Common fate
Visualize same data under different angles
US vs India
US vs Russia
US vs India
US vs Russia
5. Working memory
More than seven categories decrease readability and increase comprehension time.
Working with Figures
Extracted from:
Wang, E., Cook, D., & Hyndman, R. J. (2020). Calendar-based graphics for visualizing people’s daily schedules. Journal of Computational and Graphical Statistics, 29(3), 490-502.
Exercise
US Adults Opinions on Climate Change Relevant Regulations
Q1. Require producing 20% of electricity from clean energy
Q2. Regulate CO2 as a pollutant
Q3. Fund more research into renewable energy
Response: Strongly support (1), Somewhat support (2), Refused (3), Somewhat oppose (4), Strongly opposed (5)
| 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|
| Q1 | 15 | 20 | 2 | 38 | 25 |
| Q2 | 10 | 14 | 2 | 44 | 30 |
| Q3 | 6 | 9 | 2 | 41 | 42 |
Tables: Talagala and others, FFORMPP, IJF, 2021
Referring to Figures and Tables: present tense
…results are presented in Table 5.1. Figure 2 shows…
Chapter 5: Discussion and Conclusions
Discussion
Synthesis of ideas and main findings
Significance of research findings
Problems encountered
Limitations
Future directions of research
Chapter 5: Discussion and Conclusions
Conclusions
Final statement that sums up the thesis as a whole
Reconnects to the introduction and main research problem
A broad general conclusions emerging from the discussion