Strategic Asset Allocation Research Articles

Sustainable Equity Discrimination in Asset Liability Management for Practitioners: A Practical Approach

CONTEXT: As the financial sector increasingly emphasizes responsible investment, insurance companies are actively seeking user-friendly approaches to incorporate sustainability criteria for equities into their Asset and Liability Management processes. OBJECTIVES: This paper aims to introduce a novel practitioner-centric methodology focused on seamlessly integrating publicly available Environmental, Social, and Governance (ESG) criteria. The objective is also to ensure ease of implementation for companies, emphasizing independence from ESG scoring provided by private data providers. METHODS: The proposed approach involves leveraging accessible sustainability data to construct both a sustainable equity index and a complementary index for non-included shares, utilizing clustering techniques. Subsequently, an efficient frontier is generated through the application of the Markowitz methodology. The effectiveness of the method is demonstrated through its application to a real portfolio, showcasing stability with a notable emphasis on sustainable assets, guided by the efficient reallocations suggested by the Markowitz model. RESULTS: Both constructed indices exhibit similar trends, with the ESG index outperforming, albeit with slightly higher volatility. This performance discrepancy is mirrored in the strategic asset allocation, where a preference is given to the ESG class over the non-ESG class. IMPLICATIONS AND LIMITATIONS: The findings suggest the feasibility of a financial institution successfully developing its own cohesive sustainability index using solely publicly available data. While our constructed ESG index demonstrated superior performance in this study, further research involving alternative data sources is essential to generalize this result.

Rebalance Your Investment Portfolio Periodically: Mantra or Myth?

Rebalance Your Investment Portfolio Periodically: Mantra or Myth?

위기상황을 고려한 기관투자자의 허용위험한도 적정성

This study aims to promote efficient asset management performance by analyzing whether the risk tolerance limit set by investment institutions is appropriate considering the economic crisis situation. To this end, this study, under a total of six economic crises over the past 15 years, analyzes the sensitivity of each asset group by measuring the expected change in return for each investment institution's strategic asset allocation plan in the event of a global economic situation. After that, a virtual portfolio according to sensitivity is established, the MVO financial model is applied, and a back test is conducted to analyze the appropriateness of the risk tolerance limit by the investment institution. As a result of the analysis, it is found that the current risk tolerance limit of the Financial Mutual Aid Association, the one-year Shortfall Risk(limit value of 10%), satisfies all risk limits except for systematic risk. However, it is analyzed that the 5-year Shortfall Risk(limit value of 2.5%) satisfies the limit only in some portfolios when invested in a normal market. This means that the limit of the 5-year shortfall risk is set lower than the 1-year shortfall risk. Finally, it is appropriate to maintain the current risk tolerance limit of the Financial Mutual Aid Association, Shortfall Risk(primary≤10.0%) for one year, and Shortfall Risk(CPI≤2.5%) for five years is expected to need to be raised.

The integration of environmental, social and governance criteria in portfolio optimization: An empirical analysis

AbstractThe increasing interest of investors in environmental, social, and governance (ESG) issues has prompted asset managers to develop new approaches to strategic asset allocation that can effectively integrate ESG factors into the optimization process. This study reviews the main techniques of the most recent ESG‐efficient portfolio optimization models. Furthermore, this study conducts an empirical investigation to identify the impact of ESG constraints on mean–variance efficient allocations, and extends existing approaches by incorporating a downside risk framework. Our findings reveal that social and combined ESG ratings mitigate the negative skewness of portfolio returns, and that ESG rating, environmental rating, social rating, and combined ESG rating allow the sustainable investor to incur lower transaction costs.

Optimizing Hajj Fund Management through Strategic Asset Allocation in Islamic Finance Instrument

The management of Hajj funds must be done effectively using a rigorous standardized risk management approach. This study aims to create a Hajj fund management model using Islamic financial instruments through the optimal portfolio method and strategic asset allocation. The model was built using historical data from 2010–2022, involving Islamic deposits, government sukuk (SBSN), corporate sukuk, and Islamic stocks, which were analyzed with the Markowitz portfolio equation in Excel Solver. The result showed that the optimal portfolio yields an 8.50% expected return with a 4.00% risk; strategic asset allocation produces an 8.25% return with a 2.99% risk. The policy implication of this research is the need to review the initial deposit of pilgrims and explore alternative investments to bridge the gap between the actual cost of Hajj and pilgrims' payments while improving returns.JEL Classification: M31, M37, L92 How to Cite:Masruroh, A., Rodoni, A., & Pontjowinoto, I. P. (2023). Optimizing Hajj Fund Management through Islamic Finance Instrument. Signifikan: Jurnal Ilmu Ekonomi, 12(2), 287-306. https://doi.org/10.15408/sjie.v12i2.34403.

Strategic asset allocation with distorted beliefs

We propose an approximate solution for the asset allocation model in which the dynamics of the investment opportunity set are subject to regime shifts and the regime updating/predicting procedures are contaminated by psychological biases, including optimism, pessimism, conservatism, representativeness, momentum, and reversal. We employ monthly U.S. data to study the model and find that the optimistic investor earns higher returns and outperforms the rational (Bayesian) investor. We find that the outperformance of optimism results from the return predictability and that learning errors of optimism are offset by the information contained in the data sample. Psychological biases that can generate a large variability in beliefs or state uncertainty induce the investor to tilt toward cash and bonds.

Strategies for Creating Value: Portfolio Optimization in the Indian Automotive Sector

Abstract: This study investigates strategies for creating value through portfolio optimization in the dynamic Indian automotive industry. This research focuses on the creation of portfolios that effectively balance risk and return in an industry subject to constant change and global economic factors. Using modern portfolio theory, the study collect and analyze financial data from a subset of automotive manufacturers, focusing on past stock performance, volatility, and correlations[1]. The study construct efficient portfolios suited to various risk-return preferences, ranging from conservative to aggressive, through rigorous analysis. This research reveals the complex differences of the automobile industry, where company performance is influenced by macroeconomic variables and market trends[2]. The constructed portfolios illustrate the benefits of diversification and the returns-and-risk balancing act. It discuss the implications for investors, with an emphasis on the importance of strategic asset allocation for managing sector-specific risks. This research equips investors and financial experts with crucial tools and insights for optimizing their portfolios in the automotive industry. It contributes to a broader comprehension of portfolio management in sector-specific contexts and provides practical advice for navigating an industry that is constantly evolving

Performance of Risk Parity Strategy in Developed Markets

This study examines the performance and effectiveness of the Risk Parity (RP) strategy in strategic asset allocation specifically utilizing the inverse volatility (IV) approach. The study utilizes data from 13 developed countries, encompassing stocks and government data, to analyze the performance of RP portfolio. A comparative analysis is conducted between the RP portfolio, traditional 60/40 and equal-weighted portfolios across significant market crises, including the dot-com crisis, financial crisis, sovereign debt crisis, and COVID-19 pandemic. This study reveals that inverse volatility approach or a portfolio with a higher weight towards safer assets compared to riskier assets delivers superior risk-adjusted returns. It presents evidence that challenges the notion of the market or 60/40 portfolio as an efficient portfolio and suggests that an alternative portfolio such as RP may offer superior efficiency in terms of risk and return. Moreover, the study examines the role of leveraging in RP portfolios, highlighting how investors can align risk levels with benchmark portfolios while achieving higher risk-adjusted returns. The findings highlight the substantial impact of leveraging on RP portfolio performance, demonstrating their resilience and superiority even in challenging market conditions.

Transitory and permanent shock transmissions between real estate investment trusts and other assets: Evidence from time‐frequency decomposition and machine learning

AbstractWe evaluate asset returns and volatility connectedness using the time‐frequency connectedness model and machine learning approaches. Using 48 years of monthly indices of equity real estate investment trusts (EREITs), mortgage real estate investment trusts (MREITs), stocks, commodities, and bonds, we find that shocks to EREIT, and MREIT returns have a transitory impact on other assets. However, asset volatility connectedness among assets occurs at lower frequencies as markets slowly process pricing information. Therefore, shocks to EREIT and MREIT decay gradually and spill over to the other three assets for long periods. We also find that the intensity of the time‐frequency connectedness of returns and volatility varies with business cycles and significant domestic and global non‐recession events. We attribute the dominance of real estate investment trusts (REITs) in destabilising the financial system through long‐term volatility transmission to the heavy linkage of REITs to highly illiquid underlying direct real estate markets and high REITs leverage, making them more sensitive to real estate fundamentals, monetary shocks and macroeconomic risks than stocks and bonds. The result of the algorithm‐based machine learning model broadly supports the dominance of EREITs in the transmission of returns and volatility and shows that commodities have more explanatory power in the transmission of volatility than in returns. The empirical findings have implications for strategic and tactical asset allocation and policy design for market stability.

Risk spillover in China’s real estate industry chain: a DCC-EGARCH-ΔCoVaR model

Real estate’s role in the financial crisis has forced central banks and academics to focus on the real estate risk’s spillover effects. However, findings on this matter are erratic and could differ from country to country. Prior research mostly ignored risk contagion at the level of the real industry and instead concentrated on real estate and financial institutions. Therefore, to analyze the risk spillover of China’s real estate industry from a novel perspective of the industrial chain, a mixed model (DCC-EGARCH-CoVaR model) is proposed in this work. It fixes the flaw in existing models’ inability to account for asymmetries and the weakness of traditional methods in explaining the time-varying and nonlinear risk infection process. The findings demonstrate that China’s real estate industry has a noticeable risk spillover effect on upstream and downstream industries. The downstream industry is the one most affected by risk spillover from the real estate sector, followed by the upstream industry, and the banking sector is the least affected. The risk spillover effects of macro uncertainties like the COVID-19 outbreak, the financial crisis, and the stock market fall on real estate vary significantly. These findings are helpful for regulators to prevent systematic financial risks and for institutional investors to make timely strategic asset allocations and adjustments.

Timing and Sizing Skills of Systematic Strategies across Time and Economic Regimes

The authors first characterize a variety of systematic strategies in terms of timing and sizing skills based on their frequencies and magnitudes of gains and losses over time and then move on to analyze how these characteristics differ over macroeconomic regimes, such as inflationary and recessionary periods. The results are based on new methodologies for significance testing of gain- and loss-based performance measures and complement previous results based on analysis of the Sharpe ratio of these strategies. The empirical results have implications for outcome-orientated portfolio construction as well as strategic and tactical asset allocation, because strategies that have desirable properties—as well as strategies with problematic performance—are identified under each regime. This approach also allows for identification and attribution of the inherent sources of these differences.

Strategic Asset Allocation and Inflation Resilience

Inflation risk poses a significant challenge to strategic asset allocators and is forcing many to reevaluate the suite of quantitative tools they use. In particular, standard simulation methods are inadequate for modeling inflation dynamics and do not generate uncertainty in long-term average inflation. Furthermore, despite low-frequency regime switching between negative and positive stock–bond correlation regimes, linked to inflation dynamics, standard methods do not incorporate this either. Finally, when markets are undergoing long-term structural changes, modeling choices should be able to integrate the forward-looking expectations of subject matter experts on joint economic and market dynamics. This article describes a simple way of retrofitting these features to an existing simulation engine.

Practical Applications of Emerging Market Investing: A Multi-Asset, Granular, and Dynamic Portfolio Approach

In <b><i>Emerging Market Investing: A Multi-Asset, Granular, and Dynamic Portfolio Approach</i></b>, from the September 2022 special issue on emerging markets of <b><i>The Journal of Portfolio Management</i></b>, authors <b>Josh Davis</b> (of <b>PIMCO</b>), <b>Grace Qiu </b>(of <b>GIC Private Limited</b>), <b>German Ramirez</b>, <b>Helen Guo</b> (both of <b>PIMCO</b>), <b>Ding Li</b>, and <b>Zhihui Yap</b> (both of <b>GIC</b>) challenge the popular perception that emerging market (EM) securities are not worth including in a strategic asset allocation. The authors propose an EM investment strategy that consists of two portfolio building blocks. The first diversifies the portfolio by equalizing the risk coming from regions and asset classes, while the second tilts investment toward assets giving strong market signals. The authors backtest this strategy and demonstrate that from 2007 to 2020, it would have produced significantly higher risk-adjusted returns than index investing. Skepticism of EMs comes from the perception that they are high risk and perform poorly. The authors counter that the indexes used to track EM performance are poorly constructed and not well diversified, concentrate risk in a few countries, and select securities based on market capitalization (which is not optimal in EMs). This makes the indexes unreflective of EMs’ true potential.

Integrating sustainability into Strategic Asset Allocation: Time for action

Integrating sustainability into Strategic Asset Allocation: Time for action

Return and volatility connectedness between gold and energy markets: Evidence from the pre- and post-COVID vaccination phases

Using a two-step VAR asymmetric BEKK GARCH model, this research explores the asymmetric return and volatility connectedness between gold and several energy markets during three subperiods: pre-COVID, before vaccination, and after vaccination. Gold’s returns and volatility spillover are generally found to be time- and energy-dependent. In addition, the optimal weights, hedge ratios, and hedging effectiveness of energy commodity and gold pairs are calculated during the three subperiods. The results of optimal weights show that investors should increase their investment in energy commodities more than gold (energy commodities) during the after-vaccination period (the pre-vaccination period). Moreover, the hedging strategy would only be effective within the COVID-19 vaccination period, which could have implications for the strategic asset allocation of policy-makers and international investors. Finally, we examine the potential determinants of conditional correlations between gold and energy markets. VIX, EPU, and new confirmed cases are found to be the main predictors of correlations for most energy commodity–gold pairs during the examined period.

Gold in A Portfolio: Why, When, and Where?

In this article, we assess the safe-haven, hedging, and diversifying properties of gold for investors located in various countries and under various economic scenarios. Specifically, we focus on G7 countries plus China and India over the 20-year period ranging from 2000 to 2020. Our empirical results show that gold is a safe haven in five out of nine countries, namely Canada, Germany, Italy, the UK, and the US. We also show that the benefits of gold depend on the existing market environment as proxied by market volatility and interest rates dynamics. Overall, our results show that gold is relevant for strategic asset allocation as it may offer investors in some countries protection against significant equity market corrections. Our empirical analyses are also relevant for tactical asset allocation as we show that the safe-haven properties of gold are time-varying and may depend upon volatility state and interest rates dynamics.

The Optimal Investment Portfolio Management for Insurance and Reinsurance Companies in Gulf Cooperation Council (GCC)

This study aims to find the optimal investment portfolio management for the insurance and reinsurance companies in GCC. The researcher collected the data from the annual reports of the 30 companies listed in the respective stocks exchange from 2016 to 2020, based on the top five company's GWP from each GCC country as of 2020. Descriptive analysis for each country and each year of the study period was used to find the mean ROI and the average level of the strategic asset allocation; the pairwise correlation was used between the ROI and Libor. The results indicate the mean ROI for the insurance and reinsurance companies, the average level of SAA allocation by country and by year, the investment income has enormous effects on the performance of the insurance and reinsurance companies, the investment allocation to risky assets does not necessarily generate a high ROI, the thirty sampled insurance and reinsurance companies have generated ROI above 3%. This study contributes to the foundation of the investment portfolio management studies for insurance and reinsurance companies in the GCC countries.

Forecastability of Agricultural Commodity Futures Realised Volatility with Daily Infectious Disease-Related Uncertainty

Given the food supply chain disruption from COVID-19 lockdowns around the world, we examine the predictive power of daily infectious diseases-related uncertainty (EMVID) on commodity traded futures within the agricultural bracket, sometimes known as the softs, using the heterogeneous autoregressive realised variance (HAR-RV) model. Considering the short-, medium-, and long-run recursive out-of-sample estimation approach, we estimate daily realised volatility by using intraday data within the 5 min interval for 15 agricultural commodity futures. During the COVID-19 episode, our results indicated that EMVID plays an important role in predicting the future path of agricultural commodity traded futures in the short, medium, and long run, i.e., h = 1, 5, and 22, respectively. According to the MSE-F test, these results are statistically significant. These results contain important implications for investors, portfolio managers, and speculators when faced with investment risk management and strategic asset allocation during infectious disease-related uncertainty.

Strategic Asset Allocation of a Reserves’ Portfolio: Hedging Against Shocks

Central bank reserves function as a liquidity buffer to mitigate country exposure and vulnerability to external shocks. Emerging Market Economies are the countries most exposed to the volatility of capital flows and have usually preferred to build up large war-chests of international reserves as a self-insurance mechanism, as it is under their full discretion. Nevertheless, the standard practice of immobilizing large amounts of “cash” to insure against jumps in volatility and risk-aversion could be enhanced. The inclusion of hedging strategies in the strategic asset allocation decision can help to enhance the risk management of the national balance sheet, transferring funds to those scenarios when reserves are most needed. This paper presents a practical approach that we propose to enhance the analysis of the strategic asset allocation of a central bank, and to explore the benefits of including in the construction of the efficient portfolio the analysis of correlations between the reserves’ portfolio and the country’s main vulnerabilities to external shocks.

Tactical Asset Allocation in Stock Indices: A Kelly Criterion–Based Approach

The study shows how index funds and exchange-traded funds (ETFs) can be used for tactical asset allocation by using a modified Kelly criterion. Index funds and ETFs are good for strategic asset allocation, but there is little room for tactical asset allocation. This study nevertheless demonstrates how to use index funds and ETFs to do tactical asset allocation. People who invest in index funds or ETFs can get better risk-adjusted returns on their money no matter what kind of risk they are willing to take. The study uses the Kelly criterion in the Indian context to find portfolios that have better risk-adjusted returns.