Return Profile Research Articles

A Study on Futures and Options in Derivative

Examining the processes that influence risk and return profiles for market players, this research probes the complicated world of futures and options markets. This study takes a holistic view of the topic, delving into market behavior studies, quantitative models, and historical data to provide a detailed picture of how financial market options and futures work. Part one of the research delves into the theory of futures and options, explaining how these derivative products work. It delves into the ways these monetary instruments help hedgers manage risk, investors make speculative bets, and arbitrageurs use them strategically. Futures and options are both distinguished from one another in the research, with the study elaborating on the specific features and consequences of each. In the future, the study will examine the volatility patterns and risk-adjusted returns of several asset classes' futures and options markets. The research intends to find patterns and outliers that have affected the risk-reward environment for market players by looking at case studies and past market occurrences. Option pricing models and their use in analyzing market expectations and implied volatility are further explored in the paper. The study investigates the effect of market mood on option pricing and uses empirical analysis to assess how well option pricing models capture market dynamics.

Analysing Risk & Return Profiles: A Comparative Study of the Indonesian Stock Market against International Benchmarks

The Indonesian stock market, also known as IDX, has emerged as a prominent player in the financial landscape of Southeast Asia. It has attracted the interest of investors who regard it as a potential source of massive returns. Nevertheless, empirical research has consistently demonstrated that developing nations’ stock markets tend to exhibit a notable degree of volatility. This volatility is well recognised for its propensity to amplify risk levels for domestic investors, potentially leading to a decrease in the demand for stock market investments. The observed phenomenon in Indonesia reveals a very low degree of stock market engagement when compared to benchmark nations. This suggests that the high volatility in the market may be a contributing factor. Understanding the risk-return characteristics of the IDX in comparison to recognised benchmark indexes is crucial for making educated investment decisions. This study will conduct a comparative analysis of the risk-return attributes of the IDX in comparison to six well recognised benchmark indexes, specifically the S&P 500 Index, the Straits Times Index, the FTSE 100 Index, the Shanghai Stock Exchange Composite, the BSE Sensex, and the BOVESPA Index. The study employs several risk and return measures, such as standard deviation, coefficient of variation, and the Sharpe ratio, to assess the relative performance of the IDX. The objective of this study is to evaluate the comparative appeal of the Indonesian stock market when compared to international benchmarks, with a specific focus on risk and return. The aim is to determine the optimal level of stock market involvement and the inclination towards risk aversion or risk-seeking behaviour among retail investors in Indonesia.

Potencijal održivog investiranja u Srbiji - SDG investiciona mapa

The Serbia SDG Investor map is created using an established SDG Investor Map Methodology 2.0 - a comprehensive step-by-step UNDP methodology that combines secondary data research with desk analysis, interviews, and discussions with public and private sector stakeholders to verify findings and contribute new insights. The data are analyzed to distill Investment Opportunity Areas (IOAs) and data-backed business models. The findings on the SDG Investor Maps are uploaded to the SDG Investor Platform, allowing the investors to use extensive functionality to search for market intelligence on Serbia's SDG-aligned investment opportunities by filtering on several criteria of particular interest, including sectors, regions, SDGs as well as return profiles, market size and timeframes of investments. Serbia's proposed SDG investment portfolio consists of thirteen Investment Opportunity Areas, which came out as a result of the process of prioritization of the country's sustainable development needs, the existence of supporting country and sectoral policies, and the identification of appropriate business models for investment development. The total IOA pipeline is estimated at more than $8.3 billion in the next five years.

An Evaluation of Large Cap, Mid Cap, and Small Cap Mutual Funds: Return, Risk, and Investor Considerations

Investing in mutual funds presents a straightforward entry point into the stock market, particularly for novice investors. Regardless of one’s familiarity with stock markets or age, mutual funds offer accessible investment opportunities. However, selecting the most suitable mutual fund scheme can be challenging, given investors’ varying risk appetites and financial goals. This study aims to assist such investors grappling with scheme selection dilemmas by analysing mutual fund schemes of many types and determining which ones offer superior returns at lower risks. The research evaluates the risk and return profiles of various mutual fund schemes taken up for the study. Utilising various ratio like Jensen’s, Sharpe, and Treynor, present discussion compares the returns by considering the systematic and unsystematic risk of selected schemes within each category. The analysis spans 5 years, from April 01, 2017, to March 31, 2022, drawing data from secondary sources including Moneycontrol, journals, books, and official websites of relevant financial bodies. BNP Paribas Large Cap Fund (G) emerges as a top performer in the sphere of large cap funds according to Sharpe and Jensen’s measures, while Edelweiss Large Cap Fund-A(G) excels by Treynor ratio. Among mid cap schemes, Edelweiss Mid Cap Fund (G) consistently outperforms its peers across all evaluated ratios. In the small cap category, Axis Small Cap Fund-Regular (G) stands out for delivering the highest returns on the basis of Jensen’s, Sharpe and Treynor ratios. Ultimately, this study serves to guide investors 2024in navigating the complexities of mutual fund selection, offering insights into which funds align best with their risk-return preferences and investment objectives. Findings reveal distinct return patterns across fund categories, with specific funds outperforming peers based on various return metrics. The study concludes that while BNP Paribas Large Cap mutual Fund (G) excels in large cap schemes, Edelweiss Mid Cap mutual Fund (G) stands out among mid cap funds, and Axis Small Cap mutual Fund-Regular (G) leads in the small cap mutual funds category. Implications suggest that investors can make informed decisions based on risk-return preferences, with large cap funds offering stability, mid cap funds providing moderate returns, and small cap funds presenting opportunities for better growth with higher risk acceptance capacity.

Excess Return Profiles for Stocks Purchased by Active Equity Managers

Excess Return Profiles for Stocks Purchased by Active Equity Managers

Natural resource efficiency and green economy: Key takeaways on clean energy, globalization, and innovations in BRICS countries

Over the past few years, natural resource efficiency and the green economy have gained increasing attention. BRICS countries face challenges in natural resource efficiency and a green economy. These challenges include limited access to financing for green initiatives, insufficient infrastructure and technology, and competing priorities for economic development. This paper examines whether natural resource efficiency affects green growth under financial development, renewable energy, research and development, and globalization in BRICS countries from 1990 to 2021. Our empirical estimates are based on advanced economic methodologies, including slope heterogeneity, LM Bootstrap panel cointegration, and continuously updated fully modified (CUP-FM) and bias-corrected (CUP-BC) estimators. The result explains that sustainably transforming consumption and production patterns is supported to facilitate multi-stakeholder partnerships to encourage a green economy. Moreover, green fields' risk and return profiles differ from traditional industries under existing private financing mechanisms. Policymakers in the BRICS countries are suggested to promote the efficient use of natural resources, renewable energy sources, sustainable land use practices, sustainable urbanization, and adopting green technologies to ensure sustainable development through green growth.

Penyusunan Portofolio Saham Lindung Nilai Berdasarkan Principal Component Analysis Pada Indeks LQ45 Indonesi

Stock investment carries significant risks, making hedging strategies essential. Research on hedging in the Indonesian stock index is limited. This study aims to construct a hedging portfolio using a linear combination of principal components to create orthogonal components for stocks in the LQ45 index. A 5-year time series dataset from 2018 to 2022 is employed. Analysis reveals four principal components explaining 84% of the total data variance, with a Kaiser-Meyer-Olkin (KMO) value of 90%. This indicates successful separation of stocks with different cumulative return patterns, return profiles, and risks. ANOVA statistical tests confirm significant differences between stock groups at a 95% confidence level. The portfolio built from these four components provides excellent hedging, as indicated by a high Sharpe Ratio. Even stocks with negative returns are offset by those with positive returns within the portfolio. Backtesting and forward testing demonstrate that this portfolio outperforms the combined stock index. This research reinforces that a PCA-based hedging approach with generated principal components can mitigate risk and enhance investment returns in volatile market conditions.

Asymmetric liquidity risk and currency returns before and during COVID-19 pandemic

Motivated by the asymmetric nature of liquidity and currency return, we set out a new liquidity-adjusted extreme risk asset pricing model. Our model estimates asymmetric risk using downside beta, downside co-skewness, and excess co-kurtosis. The empirical finding strongly supports the extreme liquidity risk measures to explain the carry trade. Thus confirming that to capture better the extreme risk exposure in liquidity and currency return, it is necessary to highlight asymmetries across up and down markets using downside co-skewness and excess kurtosis. Further, we found their effect to be more pronounced during the COVID-19 period. Therefore, ignoring these exposures, especially during crises, will lead to risk and return profile, deviating from its true nature.

Revisit the Use of Index Returns as the Proxy of Market Return in CAPM

This study compares the performance of the capital asset pricing model (CAPM), which uses a mean-variance optimal portfolio, and the Jakarta Composite Index (JCI) as the market return proxy. The data samples are monthly stock returns of Kompas 100, LQ45, and IDX30 index from September 2012-August 2022. The expected returns of assets are calculated using the CAPM with rolling regression methodology based on each index's 2-5 years period. The mean-squared errors for each sample group are calculated to determine the CAPM performance. Although the market indexes have a sub-optimal risk and return profile according to their position on the efficient frontier diagram, this study finds that the JCI as the market proxy results in better CAPM performance than the optimal portfolio. However, the beta results from using JCI as the market proxy are also consistently higher than those using an optimal portfolio, leading to the overestimation bias of the asset risk. Since most studies in CAPM testing use the market index as the market return proxy, particularly JCI in Indonesia, this study provides new insight into the challenges of using the optimal portfolio as the market return proxy.

Building an Optimal Portfolio: Exploring Risk and Return in Five Distinct Sectors

Abstract: This study uses a quantitative research design to examine the risk and return characteristics of assets in five diverse sectors and build an optimal investment portfolio. To fulfil the research objectives, historical data and financial measurements were used. Standard financial performance indicators have been created to analyse the risk and return characteristics of assets within each sector. The metrics were utilized to analyse the data in this study are expected return, standard deviation, beta and Treynor ratio. Comparative evaluations have been performed to compare each sector's risk and return profiles. Statistical tests, such as Covariance, used to find significant differences in returns and risk measures between sectors. To create optimal investment portfolios, efficient portfolio creation approaches such as mean-variance optimization have been used. The goal is to find asset allocations that maximize returns for different levels of risk tolerance. Portfolios were built using various asset pairings from the five sectors.

Risk return profile of commodity derivatives: an investors perception

This article provides an overview of the literature on the commodity market, with a particular focus on the risk of commodity investment. The sources of return in the commodity market are examined, as well as the impact of various macroeconomic factors such as interest rates and inflation on the return. The commodity market is an increasingly popular investment opportunity for investors looking to diversify their portfolio. However, investing in commodities is not without risk. The volatility of commodity prices can lead to significant losses for investors, especially those who are not familiar with the market. One of the primary sources of return in the commodity market is through price appreciation. This is driven by supply and demand factors, such as changes in weather patterns, geopolitical events, and changes in consumer tastes. In addition, commodities can also generate returns through passive income, such as through rental income from real estate or dividends from stocks. Interest rates and inflation are two key macroeconomic factors that can have a significant impact on the return of commodity investments. Higher interest rates can lead to lower commodity prices, as investors seek out higher yield investments. Inflation can also impact the return of commodity investments, as it can lead to higher prices for raw materials and other inputs. For wheat, corn, and soybean futures, seasonality of return is an important consideration for investors. The prices of these commodities are often influenced by seasonal factors, such as weather patterns and harvest cycles. Understanding these seasonality patterns can help investors make more informed investment decisions. In conclusion, this study is mostly descriptive in nature, providing an overview of the literature on the commodity market and the risks associated with commodity investment. The impact of various macroeconomic factors, such as interest rates and inflation, on the return of commodity investments is also examined. Finally, the seasonality of return for wheat, corn, and soybean futures is discussed as an important consideration for investors.

A study of derivatives market (with reference to futures and options)

To find the gap between what potential the derivative market offers & how much investors are aware & willing to take benefit of the same. In the era of growing importance of savings & investment, Derivatives is a source of investment & risk management tool which is not explored to its full horizons & capabilities. My study on focuses on 2 major types of derivatives i.e. futures & options, there risk & return profiles & the investment motives & returns that investors have earned from their investment. It analyses the gap between the potential of derivatives market & how much are investors able to take the benefit of the same. The derivatives market, its functionality, practical approach & implementation is studied by considering 3 sectors - Fashion and Retail Industry, Financial Services and IT Industry & 3 industries in each of these 3 sectors. A primary data is also collected by collecting responses from investors via a Questionnaire. The questions in the Questionnaire were related to investors awareness, their risk appetite, their choice of derivative investment & returns earned by them in their investments. The primary & secondary data is then compared & based on this suggestions & findings of the study are given in this report. The result of factoral anova test shows that there is an interaction present between the no. of times an investor invests & the risk capacity possessed by him / her. The chi-square test shows that there is a relationship between the income & investment pattern of investors. So, it is identified from the study that there is a huge gap between what the derivative market has to offer, its potential and investor perceptions & choices in the market & investors awareness about this market.

A Deep Trend-Following Trading Strategy for Equity Markets

In this article, the authors present a new deep trend-following strategy that selectively buys constituents of the S&P 500 Index that are estimated to be upward trending. Therefore, they construct a binary momentum indicator based on a recursive algorithm and then train a convolutional neural network combined with a long short-term memory model to classify periods that are defined as upward trends. The strategy, which can be used as an alternative to traditional quantitative momentum ranking models, generates returns up to 27.3% per annum over the out-of-sample period from January 2010 to December 2019 and achieves a Sharpe ratio of 1.3 after accounting for transaction costs on daily data. The authors show that volatility scaling can further increase the risk–return profile and lower the maximum drawdown of the strategy.

Metal price behaviour during recent crises: COVID-19 and the Russia–Ukraine conflict

Orientation: Commodities are a prominent feature of the global economy. A substantial component of the income and welfare of both commodity-producing and commodity-consuming countries is highly dependent on the prices of commodities, such as metals. Metal prices are driven by economic growth and provide important insight into the state of the global economy: this behaviour is inextricably linked with the transitory shocks.Research purpose: Understanding recent metal price behaviour provides information about the economic implications of the coronavirus disease 2019 (COVID-19) pandemic as well as the Russia–Ukraine conflict. This research engages with the notion of the ongoing upward swing of the post-2000 super-cycle in the metals market.Motivation for the study: An analysis of metal price behaviour during COVID-19 and the Russia–Ukraine conflict describes the consequences of market shocks on commodity prices and examines the role played by super-cycles within metal markets. This work measures the optimal performances of portfolios comprising precious and nonprecious metals.Research approach/design and method: Portfolio optimisation using Lagrangian calculus under various constraints. The article argues that transitory shocks from pandemics and conflicts have a positive relationship with risk–return profiles of relevant portfolios.Main findings: A positive correlation was found between transitory shocks and prices of both precious and nonprecious metals. There is also evidence regarding the continuation of the post-2000 super-cycle in the metals market.Practical/managerial implications: Better knowledge of these relationships allows commodity traders to confidently assert that metal commodities will deliver healthy returns at moderate risk levels during periods that are characterised by different transitory shocks. Metals exist and exhibit safe haven properties during periods governed by economic uncertainty.Contribution/value add: Metals have exhibited strong economic performances in an economic landscape where little has flourished. This consequently affirms their importance and outlines their investment viability during volatile and uncertain periods.

Is There Value in Large Cap Index Selection?

The rise of passive investing is shining a new light on the world of Indexing. Indexing is all around us today, whether being discussed by a media outlet showing the movements of the day or a newly launched passive ETF that tracks a recently created index. But there is little research on whether picking one index over another provides value to the investor when the indexes all share very similar index construction methodologies. Is there value in selecting one over the other or should investors choose the one that is the most accessible or cheapest to access? This article aims to fill that gap by conducting a comparative analysis of US Large Cap indexes that are substantially similar in their construction methodologies. As expected, the indexes selected perform very similar to one another based on the quantitative methods used within the analysis. Other than number of securities, the largest difference among the indexes is their exposure to Mid-Cap stocks. The decision of which index to select is dependent on the application being selected. This article focuses on the four purposes outlined by DiBartolomeo (2019) which are: journalistic, representation of an asset class, a fair benchmark, and basis of passive investment. In most cases, each index is a reasonable substitution for the others. Given that risk and return profiles are similar, factors such as number of securities, licensing costs, and brand value are the most significant to consider. This is especially true when selecting an index as the basis of a passive product, where those factors affect the product cost and capacity that can determine the success or failure of a passive product.

Quantitative Portfolio Management Through Carbon Budgeting in a PSX Perspective

Portfolio management requires investment managers to consider investor preferences before taking any investment decisions. Some of the investors might be interested in building a clean, environmentally friendly, and carbon-free portfolio, assuming it as their corporate social responsibility (CSR) or owing to some fear of future loss arising from the ban on environment-hampering companies that might not be following the environmental, social, and governance (ESG) requirements. Historically, we have seen a ban on Chinese products because of the issues of carbon emissions. Similarly, during SMOG, many brick kilns and iron foundries are closed in Pakistan every year. The carbon budgeting on the portfolio can help achieve the CSR and sustainability goals of investors. The study attempts to develop a portfolio based on historical data, which could yield optimum results while remaining carbon conscious. The study aims to find the best-performing portfolio that could be more ESG compliant and may achieve CSR objectives to protect the environment and investors’ interests simultaneously. The findings show that companies segregated based on carbon footprint can create a carbon-free portfolio (approximately 25%) without a material impact on the expected risk and return profile. To be more ESG compliant, an investor can compromise slightly on returns, that is, only compromising 3% of the profit, we can maintain a 50% compliant portfolio in Pakistan’s environment. The study tries to improve the understanding of regulatory requirements but would also help us gain the confidence of investors who are keen to see carbon-free portfolios or in other words want to ensure investments in environmentally friendly industries.

Practical Applications of Allocating to Green Bonds

In <b><i>Allocating to Green Bonds</i></b>, from the Summer 2022 issue of <b><i>The Journal of Alternative Investments,</i></b><b>Laurens Swinkels</b> of <b>Robeco Institutional Asset Management</b> and <b>Erasmus University</b> addresses the question of where green bonds fit in fixed-income portfolios. He first examines the growth in assets and characteristics of the Bank of America’s Green Bond Index (GREN) over time to understand if such qualities are static or changing and which historical returns might be representative of future returns. His analysis covers only returns since 2015 because of the changes to the index over time. He compares the historical returns and features of the GREN to six other traditional global- and euro-based bond indexes, where the features examined included credit rating, currency, sectors, and maturity. Swinkels concludes that investors could replace a traditional aggregate fixed-income allocation with green bonds without impacting a portfolio’s risk–return profile. His asset pricing tests indicate that default and term spreads are major drivers of green bond returns.

The added value and differentiation among ESG investment strategies in stock markets

AbstractEnvironmental, social, and governance (ESG) investment strategies have garnered increasing attention in stock markets worldwide. The number of related funds and their money inflow, for instance, have more than doubled over the past 3 years. Yet, one fundamental question remains unanswered in the specialized literature: has there been any added value and statistical differentiation among ESG strategies in stock markets? We contribute to this discussion by assessing a range of ESG investment strategies across the globe. Daily closing prices of ESG best practices indices are collected for the period between 2011 and 2021, along with proxies for the market portfolio and the risk‐free rate. Empirical assessments are then conducted using classic and modern portfolio metrics as well as nonparametric tests. The results indicate a considerable degree of differentiation of the governance factor in every region studied, while the environmental and social agendas have remained considerably intertwined, with their theoretical portfolios showing similar risk–return profiles and high levels of correlation. The relative performance of ESG factors across regions has also varied considerably, with most developed economies prioritizing the environmental and social agenda for investments, and the governance factor providing better risk‐adjusted returns in emerging markets and in the Unites States. Implications and an agenda for future research are further discussed.

Is cross-hedging an effective strategy in equity futures market?

This paper aims to evaluate whether the cross-hedging strategy with Nifty 50 and single stock futures is an effective tool to hedge the price risk of single stock investors. The risk reduction potential of different hedge portfolios derived from the optimal hedge ratios is evaluated using the Diagonal BEKK GARCH model. The results reveal that cross-hedging is an effective risk reduction strategy for investors exposed to specific securities devoid of futures. Investors can construct cross-hedging portfolios with futures having closely matching return profiles and hold these positions for a longer trade horizon to achieve higher risk reduction.

A Study on Cryptocurrency Investors’ Purchase Intentions: Revisiting the Brand Personality Theory

This paper aims to identify the factors affecting the investment decision of retail investors to add crypto assets to their portfolios. The personality theory and the innovation diffusion theory are used in this study to understand the characteristics that influence investors' buying intentions. The study results show that the retail investors' purchase intentions are influenced by familiarity with the asset, trust, risk and return profile of the asset class, and the perceived security of the investor. The study also examines the role of innovativeness as a moderating variable in the relationship between purchase intentions and the primary variables. The study confirms that innovativeness has a significant mediating role in the relationship between purchase intentions and trust and also in the relationship between purchase intentions and perceived security. The results indicate that innovativeness has no significant moderating impact on the relationship between purchase intentions and familiarity and also on the relationship between purchase intentions and risk and return consciousness.