Task one: [up to 1,500 words or equivalent]Write a clear research question in the domain of asset management. Conduct a critical review of the literature on the research question. Identify the...

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Task one: [up to 1,500 words or equivalent]














Write a clear research question in the domain of asset management. Conduct a critical review of the literature on the research question. Identify the boundaries of knowledge on the research problem. Appropriate academic and professional sources must be appropriately referenced.




























Task two: [up to 1,500 words or equivalent]














Develop an application that uses machine learning algorithm(s) to produce empirical evidence on the research question you identified in task one above.








Briefly discuss the mechanics of the application you have developed.








Submit evidence of a working application together with all supporting data (or access to the data) and any relevant programming codes. The work must be reproducible. Work that cannot be reproduced in Python, R, Power Bi or Tableau will be graded according to the grade descriptor.





FT7102 Big Data in Finance (SEM1 - 2023/24) FT7102 001 Individual Portfolio (equivalent to 3,000 words) 100% Completion requirements Opened: Friday, 15 September 2023, 11:00 PM Due:  3 January 2024, 3:00 PM 1. Tutor with responsibility for this assessment  Charles Afriyie ( [email protected] ) is your first point of contact for this element of assessment.  2. The requirements for the assessment  Complete the two tasks below.  Task one: [up to 1,500 words or equivalent] Write a clear research question in the domain of asset management. Conduct a critical review of the literature on the research question. Identify the boundaries of knowledge on the research problem. Appropriate academic and professional sources must be appropriately referenced. Task two: [up to 1,500 words or equivalent] Develop an application that uses machine learning algorithm(s) to produce empirical evidence on the research question you identified in task one above. Briefly discuss the mechanics of the application you have developed. Submit evidence of a working application together with all supporting data (or access to the data) and any relevant programming codes. The work must be reproducible. Work that cannot be reproduced in Python, R, Power Bi or Tableau will be graded according to the grade descriptor.   3. Arrangements for submission  Your individualised submission deadline will be available through your assessment submission point.  Although the Assessment Brief on the Module Guide includes details of the standard submission deadline, in all cases these become individualised for you, and presented to you through the assessment point itself.  This applies to all forms of assessment, with the exception of exams, where the date and time will be available in MyGlos approximately four weeks in advance, and certain forms of assessment such as presentations and performances, for which these details will be clarified by your tutor.     Your assessment will be submitted online via Moodle. Please name the files you are submitting using the convention: MODULE CODE_ASSESSMENT NUMBER (if more than one)_STUDENT NUMBER (plus _FILE NUMBER if more than one file is being submitted) Please ensure you do not use special characters (e.g. brackets, commas, speech marks, question marks, etc.) in the file name. The Maximum file size for uploading is 100MB.  4. How your assessment will be marked  This assessment addresses Learning Outcomes:  1. Apply appropriate machine learning techniques and evaluate their effectiveness  2. Pragmatic application of machine learning in industry and the principles of algorithms.   3. Use sectoral best practice in data analytics to evaluate and improve performance  Demonstrate deep understanding of the interrelationships between data, problems and opportunities in organisational contexts
Answered 1 days AfterNov 07, 2023

Answer To: Task one: [up to 1,500 words or equivalent]Write a clear research question in the domain of asset...

Bhaumik answered on Nov 09 2023
43 Votes
FT7102 001 Individual Portfolio
Task one:
· Write a clear research question in the domain of asset management. Conduct a critical review of the literature on the research question. Identify the boundaries of knowledge on the research problem. Appropriate academic and professional sources must be appropriately referenced.
Research Question:
"What are the key factors influencing the performance of sustainable investment strategies in asset management, and how do they impact long-term financial returns?"
Introduction:
Asset management is a critical component of the financial industry, and it plays a crucial role in allocating resources efficiently and generating returns for investors. In recent years, there has been a growing
interest in sustainable investment strategies within asset management, which consider not only financial returns but also environmental, social, and governance (ESG) factors. This shift towards sustainability raises important questions about the performance and efficacy of such strategies. This literature review aims to investigate the factors that influence the performance of sustainable investment strategies in asset management and understand their impact on long-term financial returns.
Asset management stands as a cornerstone of the broader financial industry, where it shoulders the significant responsibility of efficiently allocating resources and, in turn, yields return for the diverse spectrum of investors. However, in recent years, a noticeable paradigm shift has emerged within the asset management domain, characterized by an escalating interest in sustainable investment strategies. These strategies transcend the traditional focus solely on financial returns and extend their purview to encompass a more holistic perspective, encompassing environmental, social, and governance (ESG) factors. This reorientation toward sustainability introduces a host of intriguing questions and considerations, particularly concerning the performance and efficacy of such strategies.
As societies and economies grapple with the multifaceted challenges posed by climate change, social inequality, and ethical governance, the integration of ESG factors into investment practices has become a pressing concern. Sustainable investment strategies have garnered substantial attention from both investors and asset managers, as they promise not only financial gains but also the alignment of investments with ethical and sustainability goals. This fundamental transition within the asset management landscape has catalyzed the exploration of how ESG considerations interplay with financial performance and, more significantly, how they influence long-term financial returns.
In light of these considerations, this literature review embarks on a comprehensive exploration of the intricate ecosystem within sustainable investment strategies. It endeavors to delve into the intricate web of factors that influence the performance of such strategies in the realm of asset management, casting a discerning eye on their dynamic interplay with the ultimate determinant – long-term financial returns. By scrutinizing the extensive body of academic and professional literature, we seek to identify and assess the crucial elements that mold the landscape of sustainable investment strategies and their implications for the financial industry.
As we navigate through this review, our objective is to provide a comprehensive and insightful analysis that informs practitioners, policymakers, and academics alike. By critically examining the existing knowledge and identifying the boundaries therein, we aim to contribute to a more nuanced understanding of how sustainable investment strategies can be harnessed to foster both financial prosperity and the greater good of society and the environment. This exploration is of paramount importance, particularly in an era where the financial sector carries a substantial role in addressing global challenges, and the ways we manage assets can potentially be a driving force for positive change.
Literature Review:
In their study, Dumitrescu et al. (2023) have examined the performance of 121 passive U.S. equity SRI ETFs between January 2010 and December 2020, comparing it to a benchmark portfolio comprising passive S&P 500 ETFs. The findings drawn for ETFs, a type of investment representing a basket of selected securities such as stocks or bonds, can easily be extended to portfolio management and as such, we can confidently draw some interesting conclusions from this study [1].
In their paper, Steuer and Utz (2023) start by providing a description of the current methodology used by asset managers for portfolio construction both if they consider ESG preferences of their clients or not. A distinction is also made between portfolio construction approaches that make use of a simple ESG screening from those that go further by also implementing a tri-criterion optimization model, which we will comment on in-depth as it will be the base of our study. Steuer and Utz (2023) distinguish three categories of mutual funds type, that can be regarded as asset allocation styles in the context of this master thesis [2].
Sustainable Investment Strategies:
The concept of sustainable investment strategies refers to the integration of environmental, social, and governance (ESG) factors into the investment decision-making process. This approach seeks to promote investments that are not only financially viable but also socially responsible and environmentally sustainable. Sustainable investing includes a variety of strategies, such as ESG integration, exclusionary screening, impact investing, and engagement with companies on ESG issues.
Performance and Sustainable Investing:
To evaluate the performance of sustainable investment strategies, various studies have explored financial returns, risk reduction, and the potential impact on portfolio diversification. Research by Lipton, Z. C. (2015) found that companies with strong ESG performance tend to have lower costs of capital and higher profitability, which suggests a positive correlation between ESG performance and financial returns [3].
Factors Influencing Performance:
1. ESG Data Quality:
The quality and availability of ESG data play a significant role in sustainable investment performance. Research by Hodnett, K., & Hsieh, H. (2012) highlights the importance of reliable and comparable ESG data for investors to make informed decisions. Inconsistencies or gaps in ESG data can hinder the effectiveness of sustainable investment strategies [4].
2. Regulatory Environment:
The regulatory environment has a profound impact on the adoption and success of sustainable investment strategies. Stringent ESG regulations can incentivize companies to improve their ESG performance, making sustainable investing more attractive. Regulatory changes can also affect disclosure requirements and reporting standards for ESG information, which, in turn, impact the assessment of ESG risks and opportunities.
3. Investor Attitudes and Preferences:
Investor attitudes and preferences play a pivotal role in the success of sustainable investment strategies. The increasing awareness of social and environmental issues among investors has driven demand for sustainable investment products. A study by Morgan Stanley revealed that 85% of investors...
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