Return Profile Research Articles

Comprehensive Analysis of Risk and Return Associated with Equity Stock Investment

This study provides a comprehensive analysis of the risk and return profiles of six prominent Indian automobile stocks: TVS Motor, Ashok Leyland, Bajaj Auto, MRF Ltd, Hero MotoCorp, and Mahindra & Mahindra, covering the period from 2020 to 2024. The findings reveal significant growth across the sector, with varying degrees of volatility. Key metrics such as stock price growth, earnings per share (EPS), return on equity (ROE), and price-to- earnings (P/E) ratios were analyzed, highlighting the importance of understanding both growth potential and associated risks

A Study on Analysing Risk and Return Profiles of Top Two Companies in Nifty 50

This study conducts a comparative analysis of the risk and return profiles of two leading software companies in the Nifty 50 index, Tata Consultancy Services (TCS) and Infosys, over the period from 2019 to 2024. The analysis aims to provide insights into the historical returns, volatility, and risk-adjusted performance of these companies using financial metrics such as standard deviation, beta, and alpha. Through hypothesis testing, the study evaluates correlations between risk and return, examining both companies’ sensitivity to market conditions. Findings indicate that while both firms offer positive alpha and substantial returns, TCS exhibits slightly higher stability, whereas Infosys shows higher volatility. The results provide valuable guidance for investors, highlighting considerations for portfolio diversification and strategic investment in the Indian IT sector. Keywords: Nifty 50, Risk-return analysis, volatility.

Dynamic portfolio optimization with the MARCOS approach under uncertainty

This paper introduces a dynamic portfolio selection approach that integrates the robustness of interval type-2 fuzzy sets (IT2FSs) with the flexibility of the MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method, offering a novel framework for asset evaluation amidst uncertainty. The IT2FSs enhance the adaptability of asset criteria representation, while the innovative application of MARCOS within the IT2FS environment refines the asset selection process. The weighted semi-absolute deviation metric is embraced to capture portfolio risk characteristic, which ingeniously harnesses the utility function values derived from the IT2F-MARCOS framework to delineate the anticipated return profile. On this basis, a dynamic bi-objective portfolio allocation model with realistic constraints and dynamic risk preference is formulated to rebalance portfolio periodically. Empirical evidence demonstrates the robustness and effectiveness of this approach compared to benchmark indexes, different allocation strategies, and the TOPSIS-based selection method, offering significant advancements in portfolio optimization for investors navigating uncertain markets. This study endeavors to contribute to the field of portfolio management, providing a thoughtful approach that enhances both theoretical understanding and practical application.

Portfolio Evaluation of Selected Large cap & Midcap Mutual Fund Schemes

"Wealth, place & power are no measure of sources. The only true measure is the ratio between what we might have been & what we have become". In this regard people should upgrade their knowledge & keep in pace with changing technology & market condition to reach their desired goal. As new opportunities are opening up in every field all over the world. The desired goal can achieve only when both theory and practical go together hand in hand. This article is such an attempt to understand or link the theoretical concept with that of practical applicability. It provides an in-depth analysis of Mutual Funds Schemes, encompassing their benefits, various facts crucial to understand and associated risks. Furthermore, the theoretical background of mutual funds, including the types of funds available, their advantages, and potential risks have been dealt with. The study majorly focuses on evaluating the performance of specific mutual fund schemes in the large-cap and mid- cap categories. By analyzing various portfolio evaluation models, including Sharpe, Treynor, and Jensen's alpha, as well as other metrics such as Standard Deviation, Beta, and Portfolio Return, the research aims to identify top- performing funds. The study utilizes correlation analysis and the ARIMA model to forecast the Net Asset Value (NAV) of the highest-ranked funds, providing insights into risk and return profiles, and assisting advisors in recommending suitable investment choices to investors. The study concludes by emphasizing the importance of professional management and diversification in investment, particularly within the dynamic and unpredictable stock market environment. Keywords: Risk, Return, Beta, Standard Deviation (SD), Net Asset Value (NAV) & Assets under Management (AUM), Autoregressive Integrated Moving Average (ARIMA)

Impact of ESG Risk on Portfolio Optimization and Returns: An Analysis Using the Markowitz Model

This paper explores the integration of Environmental, Social, and Governance (ESG) factors into portfolio optimization using the Markowitz Model, focusing on two groups of ten stocks each from the Technology, Media, and Telecom (TMT) sectors. These stocks are categorized into low and high ESG risk groups according to established ESG rating agencies. Employing historical data, the study computes key financial metrics such as annualized returns, standard deviation, and Sharpe ratios to conduct various portfolio optimizations including the minimal risk frontier, efficient frontier, and inefficient frontier, while also applying five specific operational constraints reflective of real-world investment limits. The analysis distinctly highlights the superior performance of the low ESG risk group, which demonstrated higher returns and better risk-adjusted return profiles, as evidenced by elevated Sharpe ratios. These findings suggest that ESG integration not only aligns with broader societal goals but also enhances financial performance, especially under diverse regulatory and strategic constraints. This research enriches the discourse on sustainable investing by providing empirical evidence on how ESG factors influence traditional portfolio management strategies, potentially guiding future investor decisions and promoting a shift towards more sustainable investment practices.

ESG and firm value: A hybrid literature review on cost of capital implications from Scopus database

AbstractThe relationship between ESG and firm value has been a relevant subject of study in recent years. We conducted a hybrid literature review to understand the literature's findings on this relationship and its implications in terms of cost of capital. First, a keyword co‐occurrence analysis on a 122 ABS ranked journals articles selection from Scopus database was adopted to identify and investigate the main research fields of the current literature. Then a content analysis through the bibliographic coupling of the most globally cited contributions was made, defining a final sample of 50 articles obtained through a minimum threshold of at least 15 total global citations (TGCs). We found that studies on the cost of debt configuration are more aimed at determining the implications on firm value, while most contributions on the cost of equity focus on the assessment of the risk–return profile for the investor or the construction of an ESG portfolio. Furthermore, we found that most of the literature has a consensus view on the lack of transparency behind the ESG ratings and their construction methodology, stating that disagreement on ESG ratings not only limits the results of empirical analysis, but can also negatively affect firm value due to a higher level of uncertainty.

Mechanisms for implementing fossil fuel divestment in portfolio management with impact on risk, return and carbon reduction

Mechanisms to incentivize divestment strategies, such as divestment schedules, are an important component of carbon reduction strategies. We use dynamic asset allocation methodologies to assess this impact over time on index portfolios (S&P 500 and FTSE 100), and global exchange-traded funds (ETFs). Although return profiles are not affected, the risk profile of S&P 500 divestment portfolios is impacted by rapid divestment strategies as divestment concentration increases. Instantaneous divestment may benefit management structure, while slower divestment provides greater stability in portfolios’ tracking errors and benefits carbon reduction, especially from reinvested capital. Divesting from energy and utilities sectors reduces carbon footprint of up to 7%, while ETFs’ divesting from highly carbon concentrated ETFs offers further carbon footprint reductions. Investing in funds with low carbon footprint results in lower dividend returns and management fees. Although ETFs’ returns are insensitive to divestment strategies and schedules, their risk profiles are affected, proportionally to their carbon intensity, especially for rapid divestment and at the expense of higher tracking errors. Divestment strategies based on ESG rating screening of FTSE 100 portfolios improve diversification and impact risk/return performance. Our study underscores the importance of considering investors’ demographics, such as dividends, management structure, and carbon reduction targets.

RISK AND RETURN ANALYSIS OF SIP V/S LUMP SUM INVESTMENT IN MUTUAL FUND SCHEME (EQUITY & HYBRID & ELSS)

This paper conducts a comprehensive risk and return analysis comparing systematic investment plan (SIP) and lump sum investment approaches in various categories of mutual fund schemes, including equity, hybrid, and Equity Linked Savings Schemes (ELSS). The study examines historical data to evaluate the performance, volatility, and risk-adjusted returns of both SIP and lump sum investments over different time horizons. Key metrics such as annualized returns, standard deviation, Sharpe ratio, and maximum drawdown are employed to provide insights into the comparative risk and return profiles of these investment strategies. The findings contribute to a better understanding of the trade-offs between SIP and lump sum investments in different mutual fund categories, aiding investors in making informed decisions based on their risk tolerance, investment objectives, and time horizon

A Study of Financial Planning on Young Individuals in Delhi NCR

This research paper investigates the significance of financial planning for young individuals in achieving long-term financial security and stability. With the increasing complexity of the financial landscape and the challenges posed by economic uncertainties, effective financial planning is indispensable for the younger generation. The paper examines various strategies and tools available for young individuals to manage their finances prudently, including budgeting, saving, investing, and debt management. Additionally, it explores the role of financial education and literacy in empowering young people to make informed decisions about their finances. Through a comprehensive review of existing literature and case studies, this paper highlights the importance of early financial planning in building wealth, mitigating risks, and achieving financial goals. Furthermore, it discusses the potential barriers and challenges faced by young individuals in implementing financial plans, such as student loans, low income, and lack of knowledge. Finally, the paper offers practical recommendations and actionable insights for young individuals to enhance their financial well-being and lay a strong foundation for a secure financial future. Monetary items function as a venture route, providing the financial supporters with the predefined monetary security and upholding the monetary items' gamble return profile. In the past traditionally, In India, banks (credit and store accounts), the Life Insurance Corporation (LIC), and the Post Office (repeating shop, National Saving Certificate, Kisan Vikas Patra) all displayed financial products. However, in recent times, as the financial services sector has advanced, new financial products have been introduced, including common stocks, shares, subordinates, annuity plans, children's education plans, life and non-extra security plans (Unit Linked Investment Plans, or ULIPs), common assets, and shares. Each person behaves differently when contributing, therefore each has a different predisposition towards speculation. A private person's investment behavior is influenced by his own circumstances. With the presumption of producing yields people invest in a few financial goods with the hope of earning sizable returns over time and with varying degrees of risk. The goal of the current analysis is to examine how salaried individuals speculate about financial goods that are supported by various segment elements.

Assessing portfolio diversification via two-sample graph kernel inference. A case study on the influence of ESG screening.

In this work we seek to enhance the frameworks practitioners in asset management and wealth management may adopt to asses how different screening rules may influence the diversification benefits of portfolios. The problem arises naturally in the area of Environmental, Social, and Governance (ESG) based investing practices as practitioners often need to select subsets of the total available assets based on some ESG screening rule. Once a screening rule is identified, one constructs a dynamic portfolio which is usually compared with another dynamic portfolio to check if it satisfies or outperforms the risk and return profile set by the company. Our study proposes a novel method that tackles the problem of comparing diversification benefits of portfolios constructed under different screening rules. Each screening rule produces a sequence of graphs, where the nodes are assets and edges are partial correlations. To compare the diversification benefits of screening rules, we propose to compare the obtained graph sequences. The method proposed is based on a machine learning hypothesis testing framework called the kernel two-sample test whose objective is to determine whether the graphs come from the same distribution. If they come from the same distribution, then the risk and return profiles should be the same. The fact that the sample data points are graphs means that one needs to use graph testing frameworks. The problem is natural for kernel two-sample testing as one can use so-called graph kernels to work with samples of graphs. The null hypothesis of the two-sample graph kernel test is that the graph sequences were generated from the same distribution, while the alternative is that the distributions are different. A failure to reject the null hypothesis would indicate that ESG screening does not affect diversification while rejection would indicate that ESG screening does have an effect. The article describes the graph kernel two-sample testing framework, and further provides a brief overview of different graph kernels. We then demonstrate the power of the graph two-sample testing framework under different realistic scenarios. Finally, the proposed methodology is applied to data within the SnP500 to demonstrate the workflow one can use in asset management to test for structural differences in diversification of portfolios under different ESG screening rules.

Do sustainability attributes play a role for individuals’ decisions regarding unit-linked life insurance? A survey research on German private investors

The aim of this paper is to investigate the relevance of sustainable product attributes as compared to ongoing costs and risk–return profiles when individuals choose funds underlying unit-linked life insurances. Regarding sustainability attributes, we focus on the product classification according to the Sustainable Finance Disclosure Regulation as a European regulatory transparency standard, and on sustainable investment strategies. We conduct two choice-based conjoint analyses using a German panel for unit-linked life insurances as well as fund savings plans as a financial product comparison. We estimate the relative importance, part-worth utilities, and the marginal willingness to pay for changes in product attributes. Our results suggest that private investors of unit-linked life insurances value sustainable product attributes and that they result in a slightly higher marginal willingness to pay, but risk–return indicators and especially ongoing costs are currently more relevant. We find further indications that sustainability attributes are less relevant in the setting of a unit-linked life insurance as compared to a fund savings plans setting.

Comparative Analysis of Risk and Return of Manufacturing Companies: A Five-Year Study-(2019-2023)

The study employs both quantitative and qualitative research approaches to assess the historical performance of a selected group of Manufacturing companies in terms of risk-adjusted returns. In order to evaluate the risk and return profiles of Manufacturing companies, a number of financial measures are looked at, such as ROI, beta coefficients, and stock price volatility. To further assist investors, financial experts, and policymakers, the study also investigates the connection between economic and financial variables and stock returns. The research process includes gathering information from primary and secondary sources, choosing Manufacturing firms according to predetermined standards, and using statistical analysis tools like regression and correlation analysis. The results underscore the variation in the financial performance and risk profiles of Manufacturing firms, underscoring the significance of making well-informed investment decisions tactics and market forecasts in the ever-changing manufacturing industry. For investors looking to maximise their investment returns inside the Manufacturing Companies, the findings provide practical insights.

Wealth as a moderating effect on gender differences in portfolio holdings

Using a unique data set of 6556 investment advisory clients at a large European wealth management institution we reveal how wealth trumps gender in determining the investment risk taking behaviour of women. While overall the advisory portfolios held by women contain less equity exposure and therefore have lower risk and return profiles than those held by men, this effect is attenuated when controlling for portfolio size. The portfolios of women with less than EUR200,000 invested contain higher equity allocations, i.e., more risk, and achieve greater returns, but they do not incur higher advisory fees compared to women with larger portfolios. These results confirm the moderating effect of wealth on gender. Furthermore, across both genders these smaller investors absorb more risk and have higher returning portfolios than investors with larger portfolios. Contributing to research on the role of gender in financial advice and investment decision making, our results are relevant to financial advisors and their clients.

Comparative Analysis of Risk and Return of IT Companies

The study focuses on evaluating the historical performance of selected IT companies in terms of risk-adjusted returns, utilizing both quantitative and qualitative research methods. Various financial metrics, including stock price volatility, beta coefficients, and return on investment (ROI), are examined to assess the risk and return profiles of IT companies. Additionally, the study explores the relationship between economic and financial indicators and stock returns to provide insights for investors, financial analysts, and policymakers. The research methodology involves data collection from primary and secondary sources, selection of IT companies based on specific criteria, and statistical analysis techniques such as regression analysis and correlation analysis. The findings highlight the diversity in financial performance and risk profiles among IT companies, emphasizing the importance of informed decision-making for investment strategies and market predictions in the dynamic landscape of the IT sector. The findings offer actionable insights for investors seeking to optimize their investment outcomes within the IT Companies

Returns and Risks in Dynamic Stocks

In the current scenario of high volatility in the stock exchange, it's crucial for investors to make informed decisions. The surge of millennial investors into the market, aiming for substantial returns, highlights the importance of a solid grasp of statistical tools and measures for sound decision-making. This study delves into the risk and return analysis of various stocks alongside their benchmark indices to decode the stock movements in relation to the market. The primary goal for any investor is to amplify profits while minimizing risks. This research aids investors by offering insights into various statistical methods for analyzing stock risks and returns. The research concentrated on gathering daily data, including the closing prices of stocks from 2019 to 2023, from the stock market. It calculated the daily returns of these stocks and measured their standard deviations, focusing on key sectors such as Automobile, Banking, Finance, FMCG, and IT. These sectors are pivotal in reflecting the country's economic health. Further analysis was conducted using beta and regression analysis to assess the risk associated with the indices compared to market indices like NIFTY AUTOMOBILE, BANK NIFTY, NIFTY FINANCE, NIFTY FMCG, and NIFTY IT Service. This helped in understanding the indices' performance versus the benchmark indices and integrating various statistical tools to differentiate the risk and return profiles across sectors. The study aims to identify which sector presents a favorable investment opportunity in terms of risk and return.

Investigating Risk and Return Dynamics in Equities of Selected 10 Firms: A Five-Year Study (2019-2023)

This five-year study (2019-2023) delves into the intricate dynamics of risk and return within equity markets, focusing on ten selected firms listed on the National Stock Exchange (NSE). Through meticulous analysis, leveraging existing literature and empirical evidence, the research aims to empower stakeholders with evidence-based insights to optimize portfolio performance and manage risks effectively. Employing descriptive research methodology, secondary data was collected from various sources including the NSE website, publications, and journals. Statistical tools such as standard deviation and correlation matrices were utilized to assess risk and return profiles. The findings reveal diverse performance trajectories among the selected companies, with some exhibiting stable returns while others experiencing significant fluctuations. The scatter plot analysis highlights a potential positive correlation between risk and return, underscoring the importance of considering both factors in investment decisions. Additionally, the correlation matrix heatmap aids in identifying pairs of companies with complementary return patterns, facilitating portfolio diversification.The study recommends cautious consideration of the risk-return tradeoff, emphasizing the need for investors to align investment strategies with their risk tolerance and financial objectives. By bridging the gap between theory and practice, this research contributes to a deeper understanding of equity market dynamics, providing actionable insights for investors to navigate volatile market conditions effectively.

Risk and Return Trade off: A Study of Indian Pharmaceutical Sector's Stocks

The Pharmaceutical sector experienced major shifts and obstacles as a result of the COVID-19 pandemic. In the post-pandemic era, the industry's continued significance and prominence can be attributed to a multitude of factors. The market prices of Pharma equities have risen substantially as a result of the expansion of the Pharmaceutical industry, which has also garnered the interest of numerous investors. Policies and efforts taken by the government include increasing foreign direct investment, research and development, and a focus on healthcare infrastructure has led to the tremendous growth of Pharmaceutical businesses in India. In order to make well-informed investment decisions, investors, financial analysts, and decision-makers rely heavily on the risk and return characteristics of businesses. The utilisation of risk and return profiles enables stakeholders and investors to assess the long-term financial performance of a company. 17 Pharmaceutical companies out of 20 Pharmaceutical companies in India's Indexed Nifty Pharma Index are included in the sample. The daily returns of a subset of companies were evaluated for the years 2013 to 2023. The retrieved data was used to compute the daily average return, standard deviation, variance, and beta for each selected company, in addition to the Nifty Pharma Index. The correlation coefficient was also computed for each individual stock and the NSE Nifty Pharma Index. Utilising the Sharpe ratio, Treynor, Jensen Alpha, and M square formulas, the most volatile stocks were determined in the Pharmaceutical sector.

Bitcoin replication using machine learning

Cryptocurrencies are characterized by high volatility and low correlations with traditional asset classes, and present an intriguing investment opportunity. However, their inherent risks and regulatory uncertainties make direct investment challenging for many investors. This paper addresses this challenge by proposing a replication framework that employs machine learning to create synthetic portfolios that replicate the risk-adjusted return profile and diversification benefits of Bitcoin, by far the largest cryptocurrency by market share. We show that the synthetic portfolios offer a compelling alternative to direct investment in Bitcoin, delivering superior risk-adjusted returns net of trading costs while mitigating the risks that are associated with holding Bitcoin directly. Furthermore, the synthetic portfolios provide better diversification benefits and lower tail risk.

Are Industry Returns Informative about Other Industries and Fundamentals?

<p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">This paper examines the information content of selected US industries focusing on the dynamic linkages among these industries, the stock market and a number of fundamental variables. The period of investigation spans from January 1960 to December 2021. The empirical strategy includes several methodologies such as regressions, vector autoregressions and volatility models. The idea is to investigate the dynamic linkages among these series at both the mean and the volatility levels. The results point to significant industry returns’ explanatory power for many predictors of economic activity including the stock market. Further, time-varying analysis of the linkages among the industries and the stock market’s returns reveal that certain industries such as <em style="mso-bidi-font-style: normal;">Oil</em> and <em style="mso-bidi-font-style: normal;">Financials</em> provide consistent information leadership over other industries and across decades. Further, upon assessing the industry–market return volatility spillovers, it was found that a market risk–return profile may not always be economically significant and timely for investors. Finally, crises, financial or otherwise, affect industries but to differing degrees.</span></p>

Exploring Sustainable Finance: A Qualitative Inquiry into Responsible Investment and ESG Risk Evaluation

This research explores the landscape of sustainable finance, responsible investment, and ESG (Environmental, Social, and Governance) risk evaluation, aiming to understand their complexities and implications for financial markets and sustainability outcomes. Employing a qualitative research approach, the study conducts a comprehensive review and synthesis of existing literature, drawing insights from academic databases, journals, reports, and other relevant sources. The research design involves purposive sampling of literature based on relevance, rigor, credibility, and significance criteria. Data collection comprises systematic review and analysis of scholarly literature, while thematic analysis is employed for data interpretation. The findings underscore the growing recognition of ESG factors' importance in investment decision-making processes, driven by their materiality to financial performance and sustainability outcomes. Institutional investors play a pivotal role in mainstream adoption of responsible investment practices, driven by the acknowledgment of ESG factors' impact on investment risk and return profiles. However, methodological challenges related to ESG data quality, measurement, and comparability persist, hindering effective ESG integration and risk assessment. Regulatory initiatives like the United Nations Principles for Responsible Investment (PRI) and the Task Force on Climate-related Financial Disclosures (TCFD) have contributed to mainstreaming ESG considerations but face challenges of regulatory fragmentation and inconsistencies. Addressing these challenges requires collaborative efforts from stakeholders to develop standardized ESG reporting frameworks, enhance stakeholder engagement, and promote regulatory coherence. This study contributes to understanding sustainable finance dynamics and calls for interdisciplinary collaboration to bridge financial theory, sustainability science, and regulatory policy.