Passive Investment Strategies Research Articles

Green Assets and Global Portfolio Tail Risk? A Stress-Testing exercise under multiple asset classes under distinct market phases

Despite a burgeoning literature in the sphere of cryptocurrencies and green assets, yet, as of date, the literature fares poorly in terms of a holistic assessment of all asset classes, let alone stress testing such global portfolio risk under various market conditions. Our paper fulfills such a gap in the literature. Findings reveal that, irrespective of bearish or bullish market phases, green assets should be incorporated to mute down portfolio tail risk. Robustness tests performed either via different distribution type or CVaR analysis do not materially alter the main findings of our paper. The confluence of two forces substantially boosts tail risk, namely, passive investment strategy coupled with a crypto-augmented base model. Overall, our paper advocates the inclusion of green assets not as a choice but as an obligation to portfolio managers in view of curtailing both VaR and CVaR risk levels, all geared towards hitting two birds with one stone-simultaneously buttressing a greener world while effectively mitigating global portfolio tail risk.

Effect of Investment Strategies on Portfolio Performance of Individual Investors in the Nairobi Securities Exchange

This study sought to determine the effect of investment strategies on the portfolio performance of individual investors in the Nairobi securities exchange. A descriptive cross-sectional survey approach was adopted. The population for this study were individual investors in the Nairobi Securities Exchange. A sample of 384 respondents was used. Both primary and secondary data were collected in this study using a questionnaire and data collection tool. Data were analyzed using descriptive and inferential statistics. The strongest correlation was observed between the active investment strategy and portfolio performance, followed by growth, passive and value strategies. From regression analysis, there was a strong positive correlation between investment strategies and performance. The relationship between investment strategies and performance was also found to be significant. It was revealed that growth and active investment strategies were statistically significant predictors of portfolio performance, with positive relationships. Active investment strategy had the largest beta coefficient, indicating that it is the most important of the four strategies in affecting portfolio performance, followed by value investment strategy and growth investment strategy, while passive investment strategy had the least influence on portfolio performance. The study concludes that investment strategies have a strong, positive and significant effect on the portfolio performance of individual investors in the Nairobi Securities Exchange. The study recommends that Nairobi Securities Exchange ought to encourage individual investors to educate themselves about various investment strategies and their potential impact on portfolio performance. It is also recommended that Nairobi Securities Exchange emphasize the importance of diversification to reduce risk.

Sparse Index Tracking With K-Sparsity or ϵ-Deviation Constraint via ℓ0-Norm Minimization.

Sparse index tracking, as one of the passive investment strategies, is to track a benchmark financial index via constructing a portfolio with a few assets in a market index. It can be considered as parameter learning in an adaptive system, in which we periodically update the selected assets and their investment percentages based on the sliding window approach. However, many existing algorithms for sparse index tracking cannot explicitly and directly control the number of assets or the tracking error. This article formulates sparse index tracking as two constrained optimization problems and then proposes two algorithms, namely, nonnegative orthogonal matching pursuit with projected gradient descent (NNOMP-PGD) and alternating direction method of multipliers for l0 -norm (ADMM- l0 ). The NNOMP-PGD aims at minimizing the tracking error subject to the number of selected assets less than or equal to a predefined number. With the NNOMP-PGD, investors can directly and explicitly control the number of selected assets. The ADMM- l0 aims at minimizing the number of selected assets subject to the tracking error that is upper bounded by a preset threshold. It can directly and explicitly control the tracking error. The convergence of the two proposed algorithms is also presented. With our algorithms, investors can explicitly and directly control the number of selected assets or the tracking error of the resultant portfolio. In addition, numerical experiments demonstrate that the proposed algorithms outperform the existing approaches.

Emerging market analysis of passive and active investing under bear and bull market conditions

PurposeStirred by scant regard for market phases in portfolio performance assessments, the current paper investigates the active versus passive investment strategies under the bull and bear market conditions in emerging markets focusing on South Africa as a case study.Design/methodology/approachMethodologically, the measures of Jensen's alpha and Treynor index are applied to the monthly returns of 20 funds from January 2010 to June 2022.FindingsThe results are enlightening; though they contradict developed market evidence, they are consistent with emerging market trends. The findings show that actively managed funds outperform the market benchmark and passive investing style under bear and normal market conditions. Passive investment strategy outperforms both market benchmark and actively investing style under bull market conditions.Practical implicationsIn the face of improved market efficiency, increased liquidity and recent technological impact, the findings of this study have practical application. The study outcomes should inform and update global investors, especially asset managers interested in emerging markets; however, the limitations of the study should also be considered.Originality/valueWhile limited studies consider market conditions when comparing and contrasting the performance of passive versus active investing, such consideration is lacking in emerging markets. The current study corrects this literature imbalance.

Penalized enhanced portfolio replication with asymmetric deviation measures

Passive investment strategies, such as those implemented by Exchange Traded Funds (ETFs), have gained increasing popularity among investors. In this context, smart beta products promise to deliver improved performance or lower risk through the implementation of systematic investing strategies, and they are also typically more cost-effective than traditional active management. The majority of research on index replication focuses on minimizing tracking error relative to a benchmark index, implementing constraints to improve performance, or restricting the number of assets included in portfolios. Our focus is on enhancing the benchmark through a limited number of deviations from the benchmark. We propose a range of innovative investment strategies aimed at minimizing asymmetric deviation measures related to expectiles and quantiles, while also controlling for the deviation of portfolio weights from the benchmark composition through penalization. This approach, as compared to traditional minimum tracking error volatility strategies, places a greater emphasis on the overall risk of the portfolio, rather than just the risk relative to the benchmark. The use of penalization also helps to mitigate estimation risk and minimize turnover, as compared to strategies without penalization. Through empirical analysis using simulated and real-world data, we critically examine the benefits and drawbacks of the proposed strategies in comparison to state-of-the-art tracking models.

Trading Strategies Using Technical Indicators: An Active Portfolio Management Approach

The study aims to evaluate the effectiveness of active trading strategies developed using technical indicators against the buy-and-hold passive investment strategy. It uses the simple moving average (SMA), Bollinger band (BB), and moving average convergence divergence (MACD) as technical indicators to generate the buy and sell signals. The study uses the data of treasury bills as a proxy for a risk-free portfolio and the Nifty Total Return Index (TRI) as a proxy for a risky equity portfolio in daily frequency from June 30, 1999 to March 31, 2021. It creates the cumulative wealth index for the sample period using active portfolio management based on the buy and sell signals generated using various technical indicators. The findings suggest that SMA and MACD trading strategies provide better risk-adjusted returns than the buy-and-hold and Bollinger band trading strategies. Also, the shorter days moving average outperforms the longer days moving average trading strategy. The trading strategies perform better during the bear market than the bull market.

Climate uncertainty and information transmissions across the conventional and ESG assets

This paper examines the effect of climate uncertainty on the spillover effects across the European conventional and environmental, social, and governance (ESG) financial markets via novel measures of physical and transitional climate risk proxies obtained from textual analysis. Analyzing daily data for stocks in the MSCI Europe ESG Leaders Index and various Euro based ESG bond indexes over the period January 3, 2014–September 30, 2021, we show that the shock transmissions between the conventional and ESG assets are significantly lower during periods of high climate uncertainty, suggesting that ESG investments can offer conventional investors diversification benefits against climate-driven shocks. Further comparing a forward-looking investment strategy conditional on the level of climate risk against the passive investment strategy, we show that investors who are worried about physical climate risks could utilize ESG equity sector portfolios as a diversification tool against physical climate uncertainty. In contrast, ESG bonds are found to be particularly useful in managing transition risk exposures that are associated with policy uncertainty and/or business transitions with respect to environmental policies. The findings have important implications regarding the role of climate uncertainty as a driver of informational spillovers across the conventional and ESG assets with important insights to manage climate risk exposures.

The Death of Active Management Has Been Greatly Exaggerated

Over the past decade, the asset management industry witnessed a significant migration of capital from active investment strategies into passive investment strategies. Undoubtedly, the structural change is shaking the active management–dominated mutual fund industry to its core. A closer scrutiny of active management suggests that the performance of active managers is mainly a function of both stock selection and portfolio construction. As other studies have already provided evidence of successful stock selection strategies via factor premiums, the author focuses on examining the impact of portfolio construction on portfolio performance. The author finds that active managers’ failure to incorporate risk during portfolio construction overwhelms the expected return signal from stock selection.

Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum

Abstract This article sheds new light on the informational efficiency of the cryptocurrency market by analyzing investment strategies based on structural factors related to on-chain data. The study aims to verify whether investors in the cryptocurrency market can outperform passive investment strategies by applying active strategies based on selected fundamental factors. The research uses daily data from 2015 to 2022 for the two major cryptocurrencies: Bitcoin (BTC) and Ethereum (ETH). The study applies statistical tests for differences. The findings indicate informational inefficiency of the BTC and ETH markets. They seem consistent over time and are confirmed during the COVID-19 pandemic. The research shows that the net unrealized profit/loss and percent of addresses in profit indicators are useful in designing active investment strategies in the cryptocurrency market. The factor-based strategies perform consistently better in terms of mean/median returns and Sharpe ratio than the passive “buy-and-hold” strategy. Moreover, the rate of success is close to 100%.

Sparse Index Tracking Portfolio with Sector Neutrality

As a popular passive investment strategy, a sparse index tracking strategy has advantages over a full index replication strategy because of higher liquidity and lower transaction costs. Sparsity and nonnegativity constraints are usually assumed in the construction of portfolios in sparse index tracking. However, none of the existing studies considered sector risk exposure of the portfolios that prices of stocks in one sector may fall at the same time due to sudden changes in policy or unexpected events that may affect the whole sector. Therefore, sector neutrality appeals to be critical when building a sparse index tracking portfolio if not using full replication. The statistical approach to sparse index tracking is a constrained variable selection problem. However, the constrained variable selection procedure using Lasso fails to produce a sparse portfolio under sector neutrality constraints. In this paper, we propose a high-dimensional constrained variable selection method using TLP for building index tracking portfolios under sparsity, sector neutrality and nonnegativity constraints. Selection consistency is established for the proposed method, and the asymptotic distribution is obtained for the sparse portfolio weights estimator. We also develop an efficient iteration algorithm for the weight estimation. We examine the performance of the proposed methodology through simulations and an application to the CSI 300 index of China. The results demonstrate the validity and advantages of our methodology.

Are Investment Managers Worth Their Keep? A 7-year Evaluation of Active and Passive Investment Performance of a University Endowment

This study examined the financial performance of Schreiner University’s actively managed endowment and compared the performance to a hypothetical passive investment strategy. From 2014 to 2020, the actively managed endowment produced a cumulative return of 71.7%. In comparison, the passive, index-based portfolio produced a cumulative return of 72.9%. The actively managed portfolio outperformed the passively managed portfolio in four out of seven years but underperformed overall. The performance results of the assets classes were inconsistent throughout the seven-year period. Additionally, a passive strategy of 60% US equities and 40% US bonds would have resulted in a cumulative return of 98.9% over seven years.

Introduction

Well-functioning securities markets are critical to the stability of the U.S. financial system, yet they are changing rapidly. Both securities markets and investors have new complexions, adding to the conventional picture of domestic public trading. For example, an increasing number of transactions today are private. Worldwide, private investment grew more than 250% between 2010 and 2019 before dipping with the COVID-19 pandemic, and in the United States, Regulation D offerings roughly doubled in the decade from 1997 to 2017. Simultaneously, cross-border asset holdings have risen: between 2012 and 2021, American holdings of foreign securities have increased by about 100%, while foreign holdings of American securities have increased by about 125%. New investment strategies have gained popularity, too. Capital increasingly flows through institutions—which, in the United States, in 2019 held assets equal to 291.3% of U.S. GDP, up from 249.3% of GDP in 2012—and into passive investment vehicles. Now, passive investment strategies tracking various indices of market or industry performance and traditional active management strategies each direct about 15 trillion in assets. Both retail and environmental, social, and governance investing, though heretofore less successful in generating investment, have made notable strides of late, as well.

The Spin Maneuver

The financialization of commodity markets has recently become a broadly discussed phenomenon, but its implications for commodity investors to a large extent remain unknown. This article focuses on whether the potential benefits of passive investment strategies in the commodity futures markets are expected to continue with increased financialization of the commodity futures markets. First, a regression analysis is conducted in order to examine the correlation between financialization and the disappearance of roll yields. Second, after finding such a correlation, we assume that this correlation is driven by increased financialization, which <i>causes</i> the decline in roll yields. Third, simulation-based methods are implemented to examine the revised efficient frontiers after accounting for the potential impact of financialization on roll yields. Our empirical research is based on returns on various asset classes and other related variables over the period 1990–2012. As noted, our computations indicate that market financialization may have resulted in a decline in roll returns. This decrease in roll yields, should it continue, is of a potential magnitude such that therationale for including commodity futures in traditional stock-and-bond portfolios would be seriously undermined. <b>TOPICS:</b>Commodities, futures and forward contracts, simulations, performance measurement

Discussion of “Obfuscation in mutual funds”: The role of financial advisers

The authors find that disclosure complexity strongly negatively relates to S&P 500 index fund returns. Because those returns are largely determined by fund fees, their evidence suggests that fund managers obfuscate to drive mutual fund investors into poor investment choices. However, the use of a passive (indexed) investment strategy can overlap with another prominent feature of the mutual fund industry: financial advisers (i.e. “money doctors,” Gennaioli et al., 2015) who assist with investment planning and implementation. The overlap can generate perverse inferences of consumer choice – seeming indifference to substantially different fees for substantially similar investments. The evidence suggests that obfuscation plays an important supporting role in the symbiosis between mutual funds and financial advisers.

Algorithmic Trading and Efficiency of the Stock Market in Poland

The aim of the article is to investigate the impact of algorithmic trading on the returns obtained in the context of market efficiency theory. The research hypothesis is that algorithmic trading can contribute to a better rate of return than when using passive investment strategies. Technological progress can be observed in many different aspects of our lives, including investing in capital markets where we can see changes resulting from the spread of new technologies.&#x0D; The methodology used in this paper consists in confronting a sample trading system based on classical technical analysis tools with a control strategy consisting in buying securities at the beginning of the test period and holding them until the end of this period.&#x0D; The results obtained confirm the validity of the theory of information efficiency of the capital market, as the active investment strategy based on algorithmic trading did not yield better results than the control strategy.

Accumulative pension system: current issues

Problem setting. The pension system is an area in which economic and social relations are intertwined. Its functioning depends on external and internal factors, at the same time the pension system itself has a very diverse impact on various processes of society, including the processes of reproduction of labor. We must state that the process of reforming the pension system in Ukraine has always been too politicized, which has led to inconsistent actions and unsatisfactory results in the long run. None of the Ukrainian governments has been able to achieve a decent standard of living for the elderly at an affordable price. The large deficit of the Pension Fund - the gap between pension obligations to retirees and income, continues to threaten economic stability and push to the background the necessary investments in health care, education, infrastructure and defense. Target of research is to reveal current issues related to the introduction of the funded pension system. Analysis of resent researches and publications. Researchers such as V. Zhernakov, V. Kostyuk, O. Protsevsky, A. Slyusar, M. Shumylo, V. Shcherbyna, and others were engaged in research in the field of pension provision. Article’s main body. The article covers the issues of levels that exist in the pension system of Ukraine. The essence of the functioning of the solidary pension system is revealed. These problems that currently exist regarding the pension provision of citizens are mentioned. The system of voluntary non-state pension provision is described, it is indicated that it is based on non-state pension funds. It is determined that the accumulative pension system is based on mandatory pension insurance, which is based on the principles of the distributive and accumulative pension system. Emphasis is placed on the fact that the funds that will accumulate in the pension accounts of citizens will be the property of these citizens. It is concluded that the process of reforming the pension system in Ukraine has always been too politicized, which has led to inconsistent actions and unsatisfactory results in the long run. The author outlines a number of fundamental issues regarding the construction and implementation of the funded pension system in Ukraine. It is noted that funded pension systems of the second level with defined contributions can demonstrate different construction options, active or passive investment strategies, investment choice options and investment managers and payment options. It is concluded that mandatory pension systems, both state solidarity and fully or partially accumulative, are only tools that determine the method of distribution of future consumption between economically active and inactive members of society. There are a number of prerequisites that are necessary for the effective implementation of the mandatory funded pension system. Conclusions. Our state must still introduce a funded pension system, because the solidarity system has experienced a crisis, and the pension provision of our citizens must be decent. There must be a reasonable approach to its effective implementation, and, of course, citizens' awareness and confidence in their retirement future.

Neural network with fixed noise for index-tracking portfolio optimization

Index tracking portfolio optimization is popular form of passive investment strategy, with a steady and profitable performance compared to an active investment strategy. Due to the revival of deep learning in recent years, several studies have been conducted to apply deep learning in the field of finance. However, most studies use deep learning exclusively to predict stock price movement, not to optimize the portfolio directly. We propose a deep learning framework to optimize the index-tracking portfolio and overcome this limitation. We use the output distribution of the softmax layer from the fixed noise as the portfolio weights and verify the tracking performance of the proposed method on the S&P 500 index. Furthermore, by performing the ablation studies on the training-validation dataset split ratio and data normalization, we demonstrate that these are critical parameters for applying deep learning to the portfolio optimization problem. We also verify the generalization performance of the proposed method through additional experiments with another index of a major stock market, the Hang Seng Index (HSI).

Metaheuristics for Sparse Index-Tracking Problem: A Case Study on FTSE 100

Passive management contributes a more stable return than an active management strategy over the long term. Index-tracking is one of the passive investment strategies that attempt to replicate market indexes to reproduce the performance. Sparse index-tracking considers a subset of market index stocks to minimize the difference between the market index and the replicated index. In this paper, two metaheuristics are applied to solve this problem. The sparse index-tracking problem formed by the objective function of the empirical tracking error with the penalty values that result in an NP-hard problem. The penalty value is used to restrict the numbers of the considered stocks. To show the performance of the metaheuristics, various penalty values are investigated, and they produce approximation solutions to the index-tracking problem. Among them, particle swarm optimization shows better or statistically similar performance to GA in solving the sparse index-tracking problem.

AN ARGUMENT AGAINST STOCK-PICKING AND MARKET-TIMING: AN EMPIRICAL APPROACH

This paper’s objective is to demystify the world of investing, first by showing and exposing the results the greatest money managers in the Wall Street have obtained over the last years compared to the performance of their benchmark indexes. Index investing represents a passive investment strategy of holding hundreds of stocks instead of the active management approach used by these experts. After exposing said results, a theoretical framework will be presented that explains why money managers have such a difficult time outperforming their benchmark indexes. Later on, a back-test experiment will be presented and thoroughly explained showing five different hypothetical investment scenarios over several 20-year periods with the attempt to quantify the potential benefit of perfectly timing the market and compare it to the cost of waiting for a better time to invest. The results find shows that the cost of waiting is much greater that the potential benefit of perfectly timing the market and the best alternative would be to invest available cash immediately regardless of market or economic outlook.

The role of institutional investors in pension risk transfers

Risk transfers represent a preferred method for removing pension liabilities from corporate balance sheet. We examine the role of institutional shareholders on firm’s decision to offload pension liabilities to professional risk managers. We find that the likelihood of pension risk transfers is higher for firms with higher level of institutional ownership and independent institutional owners. Firms with higher concentration of institutional ownership adopting a passive investment strategy are less likely to complete pension risk transfers. We also document the plan and sponsor-level factors affecting firms’ decision to undertake pension risk transfers.