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Chapter 3 Dissertation
How to Write Chapter 5 Dissertation?| A Beginner’s Guide
Writing a dissertation is a major undertaking. It requires countless hours of research, writing, and editing. One of the most important chapters in your dissertation is Chapter 4. This chapter should provide a detailed explanation of your methodology, results, and analysis.
Here, we'll provide an overview of the chapter 4 dissertation, how to structure it properly, and tips for writing it effectively. Read on to learn more!
Skimming through these dissertations, you can also check out how to craft Chapter 4 and what to discuss.
Example: 1 The Importance of Health and Safety in Construction Industry
Example:2 influence of different socio-physical attributes on individual’s weight.
Keep going through till the end to have a complete idea of how to compose a well-written and structured chapter 4 dissertation.
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What is chapter 4.
In an academic dissertation, chapter 4 is the data analysis chapter—the heart of the research project. That is where you will present the results of your research and analyze them in light of existing literature. In other words, this is where you will explain why your findings are significant and what they mean for the field as a whole.
Structure of Chapter 4
The structure of your chapter 4 should depend on the type of data that you collected during your research process. However, several key elements should be included in chapter 4:
- An introduction that explains the aims and objectives of this chapter.
- A detailed description of the approaches utilized to collect and analyze data.
- Results from both qualitative and quantitative analyses.
- Discussion about the implications for future research; and
- Conclusions about your findings as well as potential limitations or challenges faced in completing this research project.
Keep in mind that these are just general guidelines—your specific dissertation may require additional sections based on its own individual requirements. It's always best to check with your professor before starting work on any section of your dissertation.
Writing an Effective Chapter 4 Dissertation
i. Outline Your Goals & Objectives
Before you begin writing this chapter, it's important to think about the goals and objectives you want to achieve with it.
- What are the main points you want to make?
- What do you expect your readers to understand after they've read this chapter?
Having clear goals and objectives before you start writing will help ensure that your chapter is focused and organized.
ii. Explain Your Methodology
When it comes time to discuss your methodology in Chapter 4, include all relevant details about the methods you used during your research process.
It should include information about what kind of data or materials were collected, how they were analyzed, and why those particular methods were chosen for the study.
It's also important to explain any limitations or challenges encountered during data collection so that readers can fully understand the process.
iii. Discuss Results & Analysis
In Chapter 4 dissertation, it's also essential to discuss the results of your research and any analysis conducted on those results.
It should include detailed descriptions of any patterns or trends in the data collected as well as a discussion on how those patterns or trends may relate to the existing literature in the field or could potentially lead to further research questions in the future.
Make sure that all data presented here is accurate and reliable; If any differences exist between what was anticipated and what was observed, note them here as well.
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Tips for writing your chapter 4.
Here are some suggestions to make the writing process simpler if you have a clear grasp of what should be in your chapter 4;
- Take notes throughout your entire research process so that it's easier for you to compile all relevant information into one cohesive document later on.
- Utilize headings to make it easier for readers to follow along with your arguments.
- Ensure all references are correctly cited using an accepted academic style such as APA, MLA or Harvard.
- Use diagrams or graphs when necessary to visually demonstrate key points or trends among variables.
- Always proofread and edit carefully before submitting each section, so the content is free from errors or inconsistencies.
Writing a dissertation can seem overwhelming at first glance, but with some guidance, knowledge, and practice, it can become much more manageable. This guide provides an overview of everything you need to know about chapter 4 to write an effective dissertation.
Be sure not to forget to discuss both the methodology used during research and any results or analysis obtained from research; these are both integral components of this section that must not be overlooked if an effective Chapter 4 is desired.
To gain more information and academic assistance, check out the following resources:
- How To Write a Report Introduction: A Step-By-Step Guide
- How To Write a Conclusion Good Paragraph: Examples and strategies for an effective conclusion
- Mastering the Art of Academic Writing: Tips and Tricks on How to Write Academically?
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Best Practice: How to Write a Dissertation or Thesis Quantitative Chapter 4
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In the first paragraph of your quantitative chapter 4, the results chapter, restate the research questions that will be examined. This reminds the reader of what you’re going to investigate after having been trough the details of your methodology. It’s helpful too that the reader knows what the variables are that are going to be analyzed.
Spend a paragraph telling the reader how you’re going to clean the data. Did you remove univariate or multivariate outlier? How are you going to treat missing data? What is your final sample size?
The next paragraph should describe the sample using demographics and research variables. Provide frequencies and percentages for nominal and ordinal level variables and means and standard deviations for the scale level variables. You can provide this information in figures and tables.
Here’s a sample:
Frequencies and Percentages. The most frequently observed category of Cardio was Yes ( n = 41, 72%). The most frequently observed category of Shock was No ( n = 34, 60%). Frequencies and percentages are presented.
Summary Statistics. The observations for MiniCog had an average of 25.49 ( SD = 14.01, SE M = 1.87, Min = 2.00, Max = 55.00). The observations for Digital had an average of 29.12 ( SD = 10.03, SE M = 1.33, Min = 15.50, Max = 48.50). Skewness and kurtosis were also calculated. When the skewness is greater than 2 in absolute value, the variable is considered to be asymmetrical about its mean. When the kurtosis is greater than or equal to 3, then the variable’s distribution is markedly different than a normal distribution in its tendency to produce outliers (Westfall & Henning, 2013).
Now that the data is clean and descriptives have been conducted, turn to conducting the statistics and assumptions of those statistics for research question 1. Provide the assumptions first, then the results of the statistics. Have a clear accept or reject of the hypothesis statement if you have one. Here’s an independent samples t-test example:
Introduction. An two-tailed independent samples t -test was conducted to examine whether the mean of MiniCog was significantly different between the No and Yes categories of Cardio.
Assumptions. The assumptions of normality and homogeneity of variance were assessed.
Normality. A Shapiro-Wilk test was conducted to determine whether MiniCog could have been produced by a normal distribution (Razali & Wah, 2011). The results of the Shapiro-Wilk test were significant, W = 0.94, p = .007. These results suggest that MiniCog is unlikely to have been produced by a normal distribution; thus normality cannot be assumed. However, the mean of any random variable will be approximately normally distributed as sample size increases according to the Central Limit Theorem (CLT). Therefore, with a sufficiently large sample size ( n > 50), deviations from normality will have little effect on the results (Stevens, 2009). An alternative way to test the assumption of normality was utilized by plotting the quantiles of the model residuals against the quantiles of a Chi-square distribution, also called a Q-Q scatterplot (DeCarlo, 1997). For the assumption of normality to be met, the quantiles of the residuals must not strongly deviate from the theoretical quantiles. Strong deviations could indicate that the parameter estimates are unreliable. Figure 1 presents a Q-Q scatterplot of MiniCog.
Homogeneity of variance. Levene’s test for equality of variance was used to assess whether the homogeneity of variance assumption was met (Levene, 1960). The homogeneity of variance assumption requires the variance of the dependent variable be approximately equal in each group. The result of Levene’s test was significant, F (1, 54) = 18.30, p < .001, indicating that the assumption of homogeneity of variance was violated. Consequently, the results may not be reliable or generalizable. Since equal variances cannot be assumed, Welch’s t-test was used instead of the Student’s t-test, which is more reliable when the two samples have unequal variances and unequal sample sizes (Ruxton, 2006).
Results. The result of the two-tailed independent samples t -test was significant, t (46.88) = -4.81, p < .001, indicating the null hypothesis can be rejected. This finding suggests the mean of MiniCog was significantly different between the No and Yes categories of Cardio. The mean of MiniCog in the No category of Cardio was significantly lower than the mean of MiniCog in the Yes category. Present the results of the two-tailed independent samples t -test, and present the means of MiniCog(No) and MiniCog(Yes).
In the next paragraphs, conduct stats and assumptions for your other research questions. Again, assumptions first, then the results of the statistics with appropriate tables and figures.
Be sure to add all of the in-text citations to your reference section. Here is a sample of references.
Conover, W. J., & Iman, R. L. (1981). Rank transformations as a bridge between parametric and nonparametric statistics. The American Statistician, 35 (3), 124-129.
DeCarlo, L. T. (1997). On the meaning and use of kurtosis. Psychological Methods, 2(3), 292-307.
Levene, H. (1960). Contributions to Probability and Statistics. Essays in honor of Harold Hotelling, I. Olkin et al. eds., Stanford University Press, 278-292.
Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. Journal of Statistical Modeling and Analytics, 2 (1), 21-33.
Ruxton, G. D. (2006). The unequal variance t-test is an underused alternative to Student’s t-test and the Mann-Whitney U test. Behavioral Ecology, 17 (4), 688-690.
Intellectus Statistics [Online computer software]. (2019). Retrieved from https://analyze.intellectusstatistics.com/
Stevens, J. P. (2009). Applied multivariate statistics for the social sciences (5th ed.). Mahwah, NJ: Routledge Academic.
Westfall, P. H., & Henning, K. S. S. (2013). Texts in statistical science: Understanding advanced statistical methods. Boca Raton, FL: Taylor & Francis.
Dissertation Chapter 4: How To Write Your Results Chapter
The results chapter , or dissertation chapter 4, is an integral part of any dissertation research. The professionals at Statistics Solutions have assisted thousands of doctoral candidates with their dissertation results chapter.
The results chapter of your dissertation is one of the most important components of your study, where the accurate statistical analysis must be performed, assumptions examined, and findings reported and clearly explained. Once you conduct your analyses, you have to present your results in a way that shows clear support or non-support of your hypotheses. Statistical expertise is needed to effectively present the results and defend your findings.
Discover How We Assist to Edit Your Dissertation Chapters
Aligning theoretical framework, gathering articles, synthesizing gaps, articulating a clear methodology and data plan, and writing about the theoretical and practical implications of your research are part of our comprehensive dissertation editing services.
- Bring dissertation editing expertise to chapters 1-5 in timely manner.
- Track all changes, then work with you to bring about scholarly writing.
- Ongoing support to address committee feedback, reducing revisions.
Statistics Solutions can assist you with your dissertation chapter 4 in the following ways:
Data Management
- Enter, code and clean data: The first step in creating a results chapter is to import your data from Excel to SPSS. (We also use stat-transfer if the data is in another form). Once the data is in SPSS, the variables must be labeled and the levels of the variables assigned (e.g., male=1, female=2). The data cleaning typically entails screening the variables for both univariate and multivariate outliers, normality, addressing missing values, and assessing for linearity.
Statistical Analysis
- Statistical analysis: The actual analyses takes many forms. Most, if not all, dissertation results chapters include descriptive statistics of the demographic variables (means, standard deviation, frequencies and percentages), as well as the reliabilities of any composite scores. The analyses should then be focused on addressing the research hypotheses by assessing, addressing and reporting of the assumptions of the particular analysis, and then the conducting and reporting of the relevant statistical output in the results chapter.
- Write results: The results chapter should be presented logically. First the descriptives and then the results of the analyses that address the hypotheses. The tables and figures must be in APA 6th edition. The results chapter should flow smoothly, where the reader does not have to stop to question why an analysis was conducted. There is an old saying that “hard writing makes for easy reading”–you want the committee to have a very easy time reading your results chapter.
Understanding Your Results
- Explain statistics: You must be able to defend every word of the results chapter. At Statistics Solutions, we are teachers as well as statisticians and methodologists. We make sure you completely understand what was conducted, why it was conducted, and the implications of the results.
Presenting Your Results
- Create APA-style tables and figures: Tables and figures can be a stumbling block for graduate students and is especially important when formulating the results chapter. APA 6th edition has changed their format a bit from the 5th edition, and Statistics Solutions will make sure it is correct. For example, there is a greater emphasis on reporting confidence intervals and the regression tables have been substantially modified.
- Dissertation editing: While the results chapter should be edited properly, we can edit your entire dissertation for both APA and for basic English grammar, style, paragraphing, and punctuation.
- At Statistics Solutions, we use of SPSS, SAS , LISREL, M-Plus, AMOS, statistical packages, and NVIVO for qualitative data.
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Discussion Chapter Template
The fastest (and smartest) way to craft a strong discussion section for your dissertation, thesis or research project.
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What It Covers
This template covers all the core components required in the discussion chapter (or section) of a typical dissertation or thesis, including:
- The opening/ overview section
- Overview of key findings
- Interpretation of the findings
- Concluding summary
The purpose of each section is explained in plain language, followed by an overview of the key elements that you need to cover. The template also includes practical examples to help you understand exactly what’s required, along with links to additional free resources (articles, videos, etc.) to help you along your research journey.
The cleanly formatted Google Doc can be downloaded as a fully editable MS Word Document (DOCX format), so you can use it as-is or convert it to LaTeX.
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FAQs: Thesis Discussion Template
Faq: thesis discussion template, what types of dissertations/theses can this template be used for.
The discussion chapter template follows the standard format for academic research projects, which means it will be suitable for the majority of dissertations, theses and research projects (especially those within the sciences).
Keep in mind that the exact requirements for the discussion chapter/section will vary between universities and degree programs. For example, your university may require that the discussion chapter and conclusion chapter are merged into one, or that the results and discussion are covered together (this is often the case with qualitative research). So, be sure to double-check your university’s requirements before you finalise your structure.
Is this template for an undergrad, Master or PhD-level thesis?
This template can be used for a dissertation, thesis or research project at any level of study. Doctoral-level projects typically require the discussion chapter to be more extensive/comprehensive, but the structure will typically remain the same. Again, be sure to check your university’s requirements and norms in terms of document structure.
How long should the discussion chapter be?
This can vary a fair deal, depending on the level of study (undergrad, Master or Doctoral), the field of research, as well as your university’s specific requirements. Therefore, it’s best to check with your university or review past dissertations from your program to get an accurate estimate.
Can I share this template with my friends/colleagues?
Yes, you’re welcome to share this template in its original format (no editing allowed). If you want to post about it on your blog or social media, please reference this page as your source.
What format is the template (DOC, PDF, PPT, etc.)?
The dissertation discussion chapter template is provided as a Google Doc. You can download it in MS Word format or make a copy to your Google Drive. You’re also welcome to convert it to whatever format works best for you, such as LaTeX or PDF.
Do you have templates for the other chapters?
Yes, we do. We are constantly developing our collection of free resources to help students complete their dissertations and theses. You can view all of our template resources here .
Can Grad Coach help me with my discussion/analysis?
Yes, we can provide coaching-based assistance with your discussion chapter (or any other chapter). If you’re interested, get in touch to discuss our private coaching services .
Additional Resources
If you’re working on a dissertation or thesis, you’ll also want to check these out…
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- Dissertation & Thesis Outline | Example & Free Templates
Dissertation & Thesis Outline | Example & Free Templates
Published on June 7, 2022 by Tegan George . Revised on November 21, 2023.
A thesis or dissertation outline is one of the most critical early steps in your writing process . It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding the specifics of your dissertation topic and showcasing its relevance to your field.
Generally, an outline contains information on the different sections included in your thesis or dissertation , such as:
- Your anticipated title
- Your abstract
- Your chapters (sometimes subdivided into further topics like literature review, research methods, avenues for future research, etc.)
In the final product, you can also provide a chapter outline for your readers. This is a short paragraph at the end of your introduction to inform readers about the organizational structure of your thesis or dissertation. This chapter outline is also known as a reading guide or summary outline.
Table of contents
How to outline your thesis or dissertation, dissertation and thesis outline templates, chapter outline example, sample sentences for your chapter outline, sample verbs for variation in your chapter outline, other interesting articles, frequently asked questions about thesis and dissertation outlines.
While there are some inter-institutional differences, many outlines proceed in a fairly similar fashion.
- Working Title
- “Elevator pitch” of your work (often written last).
- Introduce your area of study, sharing details about your research question, problem statement , and hypotheses . Situate your research within an existing paradigm or conceptual or theoretical framework .
- Subdivide as you see fit into main topics and sub-topics.
- Describe your research methods (e.g., your scope , population , and data collection ).
- Present your research findings and share about your data analysis methods.
- Answer the research question in a concise way.
- Interpret your findings, discuss potential limitations of your own research and speculate about future implications or related opportunities.
For a more detailed overview of chapters and other elements, be sure to check out our article on the structure of a dissertation or download our template .
To help you get started, we’ve created a full thesis or dissertation template in Word or Google Docs format. It’s easy adapt it to your own requirements.
Download Word template Download Google Docs template
It can be easy to fall into a pattern of overusing the same words or sentence constructions, which can make your work monotonous and repetitive for your readers. Consider utilizing some of the alternative constructions presented below.
Example 1: Passive construction
The passive voice is a common choice for outlines and overviews because the context makes it clear who is carrying out the action (e.g., you are conducting the research ). However, overuse of the passive voice can make your text vague and imprecise.
Example 2: IS-AV construction
You can also present your information using the “IS-AV” (inanimate subject with an active verb ) construction.
A chapter is an inanimate object, so it is not capable of taking an action itself (e.g., presenting or discussing). However, the meaning of the sentence is still easily understandable, so the IS-AV construction can be a good way to add variety to your text.
Example 3: The “I” construction
Another option is to use the “I” construction, which is often recommended by style manuals (e.g., APA Style and Chicago style ). However, depending on your field of study, this construction is not always considered professional or academic. Ask your supervisor if you’re not sure.
Example 4: Mix-and-match
To truly make the most of these options, consider mixing and matching the passive voice , IS-AV construction , and “I” construction .This can help the flow of your argument and improve the readability of your text.
As you draft the chapter outline, you may also find yourself frequently repeating the same words, such as “discuss,” “present,” “prove,” or “show.” Consider branching out to add richness and nuance to your writing. Here are some examples of synonyms you can use.
Address | Describe | Imply | Refute |
Argue | Determine | Indicate | Report |
Claim | Emphasize | Mention | Reveal |
Clarify | Examine | Point out | Speculate |
Compare | Explain | Posit | Summarize |
Concern | Formulate | Present | Target |
Counter | Focus on | Propose | Treat |
Define | Give | Provide insight into | Underpin |
Demonstrate | Highlight | Recommend | Use |
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When you mention different chapters within your text, it’s considered best to use Roman numerals for most citation styles. However, the most important thing here is to remain consistent whenever using numbers in your dissertation .
The title page of your thesis or dissertation goes first, before all other content or lists that you may choose to include.
A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.
- Your chapters (sometimes subdivided into further topics like literature review , research methods , avenues for future research, etc.)
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Ensemble Deep Reinforcement Learning for Financial Trading
- First Online: 28 August 2024
Cite this chapter
- Mendhikar Vishal 7 , 8 ,
- Vadlamani Ravi 7 &
- Ramanuj Lal 9
Part of the book series: Intelligent Systems Reference Library ((volume 254))
Stocks trading strategy plays an important role in financial investment. However, it is challenging to come up with an optimal profit-making portfolio in a volatile market. In this thesis, we proposed a couple of ensemble methods that use a few deep reinforcement learning (DRL) architectures to train on dynamic markets and learn complex trading strategies to achieve maximum returns on investments. We proposed three ensemble strategies with three different RL Actor-Critic algorithms as constituents: Twin Delayed Deep Deterministic Policy Gradient (TD3), Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC). These three ensembles are as follows: (i) PPO, TD3, and DDPG (ii) SAC, PPO, and TD3 (iii) DDPG, SAC, and PPO and compared their performance with that of the state-of-the-art ensemble method, performance namely, Advantage Actor Critic (A2C), PPO, and DDPG. The ensemble techniques adapt to various market conditions by utilizing the best aspects of all three algorithms. The effectiveness of these ensembles is demonstrated on 30 Sensex stocks with sufficient liquidity and 30 Dow Jones Industrial Average (DJIA) indexed stocks. The Sharpe ratio and maximum drawdown are employed to evaluate the performance of the ensemble methods.
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Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press (2018)
Google Scholar
Rubinstein, M.: Markowitz’s “portfolio selection”: a fifty-year retrospective. J. Finance 57 (3), 1041–1045 (2002)
Article Google Scholar
Betancourt, C., Chen, W.H.: Deep reinforcement learning for portfolio management of markets with a dynamic number of assets. Exp. Syst. Appl. 164 , 114002 (2021)
Bertsekas, D.: Dynamic Programming and Optimal Control, vol. 1. Athena Scientific (2012)
Schulman, J., Levine, S., Abbeel, P., Jordan, M., Moritz, P.: Trust region policy optimization. In: International Conference on Machine Learning, pp. 1889–1897. PMLR (2015)
Zhang, Z., Zohren, S., Roberts, S.: Deep reinforcement learning for trading. J. Finan. Data Sci. 2 (2), 25–40 (2020)
Xiong, Z., Liu, X.Y., Zhong, S., Yang, H., Walid, A.: Practical deep reinforcement learning approach for stock trading (2018). arXiv preprint arXiv:1811.07522
Bekiros, S.D.: Heterogeneous trading strategies with adaptive fuzzy actor–critic reinforcement learning: a behavioral approach. J. Econ. Dyn. Control 34 (6), 1153–1170 (2010)
Article MathSciNet Google Scholar
Li, J., Rao, R., Shi, J.: Learning to trade with deep actor critic methods. In: 2018 11th International Symposium on Computational Intelligence and Design (ISCID), vol. 2, pp. 66–71. IEEE (2018)
Jiang, Z., Liang, J.: Cryptocurrency portfolio management with deep reinforcement learning. In: 2017 Intelligent Systems Conference (IntelliSys), pp. 905–913. IEEE (2017)
Moody, J., Saffell, M.: Learning to trade via direct reinforcement. IEEE Trans. Neural Netw. 12 (4), 875–889 (2001)
Deng, Y., Bao, F., Kong, Y., Ren, Z., Dai, Q.: Deep direct reinforcement learning for financial signal representation and trading. IEEE Trans. Neural Netw. Learn. Syst. 28 (3), 653–664 (2016)
Chen, L., & Gao, Q.: Application of deep reinforcement learning on automated stock trading. In: 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS), pp. 29–33. IEEE (2019)
Dang, Q.V.: Reinforcement learning in stock trading. In: International Conference on Computer Science, Applied Mathematics and Applications, pp. 311–322. Springer, Cham (2019)
Jeong, G., Kim, H.Y.: Improving financial trading decisions using deep Q-learning: predicting the number of shares, action strategies, and transfer learning. Exp. Syst. Appl. 117 , 125–138 (2019)
Wang, X., Gu, Y., Cheng, Y., Liu, A., Chen, C.P.: Approximate policy-based accelerated deep reinforcement learning. IEEE Trans. Neural Netw. Learn. Syst. 31 (6), 1820–1830 (2019)
Bertoluzzo, F., Corazza, M.: Testing different reinforcement learning configurations for financial trading: Introduction and applications. Proc. Econ. Finance 3 , 68–77 (2012)
Pendharkar, P.C., Cusatis, P.: Trading financial indices with reinforcement learning agents. Exp. Syst. Appl. 103 , 1–13 (2018)
Fischer, T.G.: Reinforcement Learning in Financial Markets—A Survey. No. 12/2018. FAU Discussion Papers in Economics (2018)
Weng, L., Sun, X., Xia, M., Liu, J., Xu, Y.: Portfolio trading system of digital currencies: a deep reinforcement learning with multidimensional attention gating mechanism. Neurocomputing 402 , 171–182 (2020)
García-Galicia, M., Carsteanu, A.A., Clempner, J.B.: Continuous-time reinforcement learning approach for portfolio management with time penalization. Exp. Syst. Appl. 129 , 27–36 (2019)
Raffin, A., Hill, A., Ernestus, M., Gleave, A., Kanervisto, A., Dormann, N.: Stable baselines3 (2019)
Gold, C.: FX trading via recurrent reinforcement learning. In: 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings, pp. 363–370. IEEE (2003)
Almahdi, S., Yang, S.Y.: An adaptive portfolio trading system: a risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown. Exp. Syst. Appl. 87 , 267–279 (2017)
Carapuço, J., Neves, R., Horta, N.: Reinforcement learning applied to Forex trading. Appl. Soft Comput. 73 , 783–794 (2018)
Hu, Y.J., Lin, S.J.: Deep reinforcement learning for optimizing finance portfolio management. In: 2019 Amity International Conference on Artificial Intelligence (AICAI), pp. 14–20. IEEE (2019)
Kim, T.W., Khushi, M.: Portfolio optimization with 2D relative-attentional gated transformer. In: 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), pp. 1–6. IEEE (2020)
Katongo, M., Bhattacharyya, R.: The use of deep reinforcement learning in tactical asset allocation. Available at SSRN 3812609 (2021)
Koratamaddi, P., Wadhwani, K., Gupta, M., Sanjeevi, S.G.: Market sentiment-aware deep reinforcement learning approach for stock portfolio allocation. Eng. Sci. Technol. Int. J. 24 (4), 848–859 (2021)
Zarkias, K.S., Passalis, N., Tsantekidis, A., Tefas, A.: Deep reinforcement learning for financial trading using price trailing. In: ICASSP 2019–2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3067–3071. IEEE (2019)
Mabu, S., Chen, Y., Hirasawa, K., Hu, J.: Stock trading rules using genetic network programming with actor-critic. In: 2007 IEEE Congress on Evolutionary Computation, pp. 508–515. IEEE (2007)
Ponomarev, E.S., Oseledets, I.V., Cichocki, A.S.: Using reinforcement learning in the algorithmic trading problem. J. Commun. Technol. Electron. 64 (12), 1450–1457 (2019)
Liu, Y., Liu, Q., Zhao, H., Pan, Z., & Liu, C.: Adaptive quantitative trading: an imitative deep reinforcement learning approach. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 02, pp. 2128–2135 (2020)
Briola, A., Turiel, J., Marcaccioli, R., Aste, T.: Deep reinforcement learning for active high frequency trading (2021). arXiv preprint arXiv:2101.07107
Li, Y., Zheng, W., Zheng, Z.: Deep robust reinforcement learning for practical algorithmic trading. IEEE Access 7 , 108014–108022 (2019)
Olschewski, S., Diao, L., Rieskamp, J.: Reinforcement learning about asset variability and correlation in repeated portfolio decisions. J. Behav. Exp. Finance 32 , 100559 (2021)
Yang, H., Liu, X.-Y., Zhong, S., Walid, A.: Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. SSRN (2020)
Aroussi, R.: yfinance. PyPI (2019). Retrieved July 15, 2022. https://pypi.org/project/yfinance
Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., Zaremba, W.: Openai gym (2016). arXiv preprint arXiv:1606.01540
Sutton, R.S., McAllester, D., Singh, S., Mansour, Y.: Policy gradient methods for reinforcement learning with function approximation. Adv. Neural Inf. Process. Syst. 12 (1999)
Mnih, V., Badia, A.P., Mirza, M., Graves, A., Lillicrap, T., Harley, T., et al.: Asynchronous methods for deep reinforcement learning. In: International Conference on Machine Learning, pp. 1928–1937. PMLR (2016)
Lillicrap, T.P., Hunt, J.J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., et al.: Continuous control with deep reinforcement learning (2015). arXiv preprint arXiv:1509.02971
Sewak, M., Sahay, S.K., Rathore, H.: Policy-approximation based deep reinforcement learning techniques: an overview. In: Information and Communication Technology for Competitive Strategies (ICTCS 2020), pp. 493–507 (2022)
Buşoniu, L., de Bruin, T., Tolić, D., Kober, J., Palunko, I.: Reinforcement learning for control: performance, stability, and deep approximators. Annu. Rev. Control. 46 , 8–28 (2018)
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Acknowledgements
The authors are thankful to the senior domain expert, Mr. Rajiv Ramachandran for helping us in understanding the concepts of the stock market and guiding us in the project during his tenure at IDRBT.
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Mendhikar Vishal & Vadlamani Ravi
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Mendhikar Vishal
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Ramanuj Lal
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Leandros A. Maglaras
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Vishal, M., Ravi, V., Lal, R. (2024). Ensemble Deep Reinforcement Learning for Financial Trading. In: Maglaras, L.A., Das, S., Tripathy, N., Patnaik, S. (eds) Machine Learning Approaches in Financial Analytics. Intelligent Systems Reference Library, vol 254. Springer, Cham. https://doi.org/10.1007/978-3-031-61037-0_9
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This report analyses and interprets the results of a survey on AIDS education workshops conducted by the Department of Education in South Africa. It covers topics such as attendance, age, blood test, language, and counselling methods of the workshops.
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CHAPTER 4. H RESULTS AND ANALYSIS4.1 INTRODUCTIONThis chapter reviews the results and analysis of the qualitative data, the compilation of the questionnaire and the results and analysis of. the quantitative findings of the study. The findings are also discussed in the light of previous research findings and available literature, where ...
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Dissertation OverviewThe traditional dissertation is organized into 5 chapters and includes the following elements and pages:Title page (aka cover page) Signature ...
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4.1 INTRODUCTION. This chapter describes the analysis of data followed by a discussion of the research findings. The findings relate to the research questions that guided the study. Data were analyzed to identify, describe and explore the relationship between death anxiety and death attitudes of nurses in a private acute care hospital and to ...
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4.2 Stock Market Environment. Environment for multiple stocks. We used continuous action space to model the trading of several stocks, in our portfolio, there are 30 stocks. 4.2.1 State Space. We used a dimensional vector consisting of seven values that represent the state space. [b t, p t, M t, C t, X t, h t, R t]. 4.2.2 Action Space