Risk-averse Investors Research Articles

Are Shariah-compliant firms less prone to stock price crash risk? Evidence from Malaysia

PurposeThe term “Shariah compliance” states that a firm conducts business activities within the boundaries stipulated by Islamic law. The purpose of this study is to empirically examine whether a firm’s Shariah compliance helps in reducing firm-specific stock price crash risk (SPCR).Design/methodology/approachUsing the data of 10,391 firm-year observations of non-financial public listed firms in Malaysia from 2001–2017, this study uses the panel data estimation technique for regression analysis. Moreover, a series of alternative estimations has been applied to check the consistency of results.FindingsThe findings reveal a significant negative impact of firms’ Shariah compliance on SPCR. The results indicate that Shariah-compliant (SC) firms are less likely to hoard bad news, ultimately reducing SPCR. The results also unveil a possible mechanism through which SC firms reduce SPCR. The findings reveal that SC firms are less likely to be involved in earnings management, which reduces the risk of a stock price crash in SC firms. It highlights the behavioral differences in financial reporting between SC firms and Shariah non-compliant (SNC) firms.Practical implicationsThis research adds to the existing literature of Islamic capital markets from the perceptive of SPCR. The SPCR exhibits a tail risk of the stocks and is very important for risk management and investment decisions. The findings of this study will help risk-averse investors to include SC firms in their investment portfolios for risk minimization. The results also guide policymakers and regulatory bodies to rethink the monitoring mechanisms of publicly listed firms.Originality/valueThis study is unique, as it highlights that firms’ Shariah compliance reduces SPCR.

Market risk aversion under volatility shifts: An experimental study

We propose an experiment to analyze the relationship between volatility regimes and investors’ behavior and explore the mechanism by which aggregated risk aversion is configured. We design a market in which the volatility of the fundamentals is controlled and exogenously manipulated. Then we analyze the participation and trading behavior of participants under different volatility states. We observe a decrease in the market risk aversion during high volatility periods. In these periods, relatively more risk-averse investors do not participate in the risky market while less risk-averse investors trade. The individual risk aversion level of agents does not change during the experiment which leads us to conclude that the changes in market risk aversion during high volatility periods are mainly due to a participation effect.

The diversification benefits of cryptocurrency asset categories and estimation risk: pre and post Covid-19

We examine the diversification benefits of cryptocurrency asset categories. To mitigate the effects of estimation risk, we employ the Bayes-Stein model with no short-selling and variance-based constraints. We estimate the inputs using lasso regression and elastic net regression, employing the shrunk Wishart stochastic volatility model and Gaussian random projection. We consider nine cryptocurrency asset categories, and find that all but two provide significant out-of-sample diversification benefits. The lower is investor risk aversion, the more beneficial are cryptocurrencies as portfolio diversifiers. During uncertain economic environments, such as the post-Covid-19 period, cryptocurrencies provide the same diversification benefits as in more stable environments. Our results are robust to different portfolio benchmarks, regression technique, transaction cost, portfolio constraints, higher moments and Black–Litterman models.

Financial sustainability: measurement and empirical evidence

Financial sustainability is underrepresented in both the research on and practice of sustainability management and reporting. This article proposes a conceptual measure of financial sustainability and examines its association with capital market returns. The measure is positioned at the intersection of sustainability management, risk management and risk governance. Financial sustainability is regarded as a crucial control parameter complementing shareholder value and can be viewed by risk-averse investors as a secondary condition of investment decisions. It reduces refinancing and insolvency risks, leading to risk-adjusted excess returns in an imperfect capital market with financing restrictions and insolvency costs. We propose measuring a firm’s financial sustainability in terms of four conditions: (1) firm growth, (2) the company’s ability to survive, (3) an acceptable overall level of earnings risk exposure, and (4) an attractive earnings risk profile. We show that the application of a conditions-based investment strategy to European firms with high financial sustainability (i.e., firms fulfilling all four conditions) over the period from July 1990 to June 2019 results in monthly excess returns of 0.39%. This portfolio’s risk is lower than the risk of market investment. We find that the excess returns increase when incrementally adding each of the four conditions to the investment strategy.

Performance of residential property investment returns in an emerging metropolitan area. The awareness, use and gender inequality

This study assessed the performance of residential property investment returns. To ascertain the awareness, use, and gender inequality in the usage of residential performance data by investors. The paper focuses on risk-return features of the tenement, two and three-bedroom property for investment purposes, in order to improve the understanding of the property market mechanism in Kano metropolis, Nigeria. Unraveling empirically risk-return features of residential property in the metropolitan area is unclear hence the speculative decision on residential investment is widespread. Quantitative research was employed using a questionnaire survey to obtain primary data on annual rental and capital values of residential properties from branch managers of estate firms. This data was afterward transformed into total returns and put to Phillip-Perron unit root test (stationarity). The study utilized both descriptive and inferential statistical techniques for analysis. Findings from the study show that total returns for residential property range from 6.99% to 14.44% with risk-return ranging from 20.92% to 51.54% within the property market, Badawa/GRA property has the lowest risk features hence the most secured location for residential investment, the paper also unveils that gender inequity in the usage of residential property investment performance data is high against women. It is on these findings that the study recommended Badawi/GRA property market for risk-averse investors, persistent sensitization program and incentives (reduction in service charge) targeting women in the property market is encouraged.

Reducing transaction costs for interest rate risk hedging with stochastic programming

Traditional methods for hedging interest rate risk do not take transaction costs into account as they aim to eliminate all risk. We propose a two-stage stochastic programming model for hedging interest rate risk where transaction costs are weighed against portfolio variance. High-quality measurements of term structures enable us to extract the systematic risk factors and make precise estimates of the perceived transaction costs. The hedging cost is weighed against the reduction in portfolio variance by using an adjustable hedging parameter. The hedging procedure is simulated on a daily basis in a realistic setting over an out-of-sample period from 2002 to 2018, and the results are compared to traditional hedging methods through detailed performance attribution. Using second-order stochastic dominance, we show that the proposed method is preferred by all risk-averse investors.

Who should buy stocks when volatility spikes?

I find that when volatility spikes, patient and more risk-averse investors should increase their exposure to stocks whereas impatient and less risk-averse investors should decrease it. This is because investors with a greater willingness to bear risk choose a larger exposure to risky assets on average, so volatility shocks affect their wealth relatively more. In general equilibrium, the deterioration of impatient and less risk-averse investors’ wealth implies their ability to hold risky assets gets impaired, and thus they sell their positions to patient and more risk-averse investors at lower prices and higher expected excess returns.

Effect of financial literacy and risk aversion on the relationship between self-control and financial security of individual investors in Tehran Stock Exchange

Capital markets play an important role in the economy and naturally, the proper functioning of the capital market will play a key role in ensuring economic growth. So, if capital markets are efficient, economic development will be ensured. On the other hand, since the Iranian stock market is currently very popular among investors, it is undoubtedly important to examine the behavioral biases of individual investors. Therefore, in this study, the effect of positive self-control behavioral bias on financial security was investigated with the moderating role of financial literacy and risk aversion of individual investors. For this purpose, the statistical population consisted of individual investors, traders and brokers of Tehran Stock Exchange who are directly participating in the market. Also, the statistical sample was calculated to be 421 using Cochran’s formula. A structural equation model using PLS method was used to analyze the data. The results showed that the self-control variable has a significant positive effect on risk aversion and financial security. Also, by using the financial literacy variable as a moderating variable, the intensity of the relationship between self-control and financial security of individual investors increases; that is, the financial literacy of individual stock market investors intensifies the positive relationship between self-control and security of their financial behavior. In addition, by using risk aversion as moderating variable, the intensity of the relationship between self-control and financial security of individual investors is reduced. This means that the risk aversion of individual stock market investors reduces the positive relationship between self-control and the security of their financial behavior.

Evaluation of supply chain routes based on control engineering and DEA considering traffic congestion and uncertainty

In this paper, a mathematical model is proposed to assess the flow distribution based on the traffic criterion. In the mathematical model, the resilience and stability criteria are developed based on the concepts of control engineering and optimal control. The results show that the route stability is dependent on the traffic parameter. Then, considering several factors including stability, safety, resilience, risk-averse investment, the environment and noise, a decision-making model is presented to evaluate the performance of the flow distribution routes during crises. Goal programming and data-oriented modelling are used to solve the mathematical model. Data envelopment analysis (DEA) is used as the data-oriented model to evaluate the performance of scenarios under uncertainty. Furthermore, a decision-making methodology is proposed for ranking the routes. The results show that increasing beta can lead to lower desirability of a route. Finally, a managerial analysis is presented based on efficiency, risk, and PEST measures.

Optimal investment strategy to maximize the expected utility of an insurance company under Cramer-Lundberg dynamic

In this work, we examine the combined problem of optimal portfolio selection rules for an insurer in a continuous time model where the surplus of an insurance company is modelled as a compound Poisson process. The company can invest its surplus in a risk free asset and in a risky asset, governed by the Black-Scholes equation. According to utility theory, in a financial market where investors are facing uncertainty, an investor is not concerned with wealth maximization per se but with utility maximization. It is therefore possible to introduce an increasing and concave utility function $\phi(x,t)$ representing the expected utility of a risk averse investor (insurance company). Therefore, the goal of this work is not anymore to maximize the expected portfolio value or minimize the ruin probability or maximizing the expectation of the present value of all dividends paid to the shareholders up to the ruin, but to maximize the expected utility stemming from the wealth during the life contract [0,T]. In this direction, using the Dynamic Programming Principle of the problem, we obtain the Hamilton-Jacobi-Bellman equation by our optimization problem (HJB). Finally, we present numerical solutions in some cases, obtaining as optimal strategy the well known Merton's strategy.

Forecasting the European Monetary Union equity risk premium with regression trees

This paper investigates whether classification and regression trees ensemble algorithms such as bagging, random forests and boosting improve on traditional parametric models for forecasting the equity risk premium. In particular, we work with European Monetary Union (EMU) data for the period from its foundation in 2000 to 2020. The paper first compares the monthly out-of-sample forecasting ability of multiple economic and technical variables using univariate linear regression models and regression tree techniques. The results obtained suggest that regression trees do not show better forecasting ability than a first-order autoregressive benchmark model and univariate linear regressions. The paper then analyses asset allocation strategies with regression trees and checks whether these can select the best economic predictors to form dynamic portfolios composed of two assets: a risk-free asset and an equity index. The results indicate that trading strategies built with two or three economic predictors selected with boosting and random forest algorithms can generate economic value for a risk-averse investor with a quadratic utility function.

Risk Factors in the German Stock Market: Can Sentiment Improve the Performance of Traditional Multifactor Models?

Capital market research usually focuses on the investment decision of a risk-averse investor, who determines the relationship between risky assets and risk-free investment. Furthermore, numerous capital market models assume normally distributed security returns and rational investors. In this framework, ex-ante investment decisions depend solely on the expected return, risk of investment opportunities, and investor risk affinity. For decades, empirical research findings have criticized this idealized framework. New risk factors were empirically confirmed and established. This study attempts to shed light on this issue. A comparative analysis considers the Fama-French and Carhart factors and a principal component analysis based sentiment-risk factor considering 76 sentiment indicators to examine the possible explanatory contribution to German stock market returns.

Effects of Exchange Rate Volatility on Economic Growth: Evidence from West Africa

The implications of exchange rate movement for economic growth have become a growing focus of attention in the recent policy debate and the debate concentrate on the degree of volatility in the exchange rate. Exchange rate volatility is usually a risk that will result in higher costs for risk-averse investors, who may adopt a wait-and-see policy until the uncertainty subsides, thereby leading to reduced employment opportunities and slower growth. Thus, in judging the desirability of exchange rate volatility, this paper studies the effects of exchange rate volatility on economic growth for twelve West African countries: The Gambia, Ghana, Cote d'Ivoire, Mali, Niger, Nigeria, Senegal, Togo, Benin, Burkina Faso, Guinea Bissau, and Sierra Leone. Furthermore, the almost complete neglect of the financial sector development in the growth prospect of West African countries is still rather surprising since economic intuition and theory suggest that the growth of the financial sector by means of indebtedness and credit expansion does provide an average GDP growth rate. However, the financial markets and institutions in the West African countries are narrow and shallow. Thus, these countries do not have the tools to hedge exchange rate risks. Hence, fluctuating exchange rates often generate uncertainty, which leads to a decline in economic activity. Therefore, this study also analyzes the role of financial sector development on the impact of exchange rate volatility on economic growth of the West African economies. The random-effects and the two-step difference Generalized Method of Moment GMM estimation techniques are used in this analysis. The “Ad hoc method” is employed by using the lagged term of exchange rate movements for a robustness check in the random-effects model. The results support that the depreciation of the real effective exchange rate volatility has a contractionary effect on economic growth in West African countries and this contractionary effect decreases with countries’ financial sector development. Our results are also support the random effect “Ad hoc methodology” and the GMM procedure implying that they are robust to the cross-section correlation and reverse causality considerations. We also showed that depreciation of real exchange rate is again contractionary for the West African countries in the short run as well as in the long run using GMM procedures. The study recommends that the authorities in the West African countries should speed up the development of their financial sector to decrease the negative effects of exchange rate volatility thereby encouraging economic growth.

Polynomial affine approach to HARA utility maximization with applications to OrnsteinUhlenbeck [formula omitted] models.

This paper designs a numerical methodology, named PAMH, to approximate an investor’s optimal portfolio strategy in the contexts of expected utility theory (EUT) and mean-variance theory (MVT). Thanks to the use of hyperbolic absolute risk aversion utilities (HARA), the approach produces optimal solutions for decreasing relative risk aversion (DRRA) investors, as well as for increasing relative risk aversion (IRRA) agents. The accuracy and efficiency of the approximation is examined in a comparison to known closed-form solutions for a one dimensional (n=1) geometric Brownian motion with a CIR stochastic volatility model (i.e. GBM 1/2 or Heston model), and a high dimensional (up to n=35) stochastic covariance model. The former confirms the method works even when the theoretical candidate is not well-defined, while the latter illustrates low errors (up to 8% in certainty equivalent rate (CER)) and feasible computational time (less than one hour in a PC).Given the potential of this method, we investigate a relevant practical setting with no closed-form solution, namely when assets follow an OrnsteinUhlenbeck 4/2 stochastic volatility (SV, i.e. OU 4/2) model. We conduct sensitivity analyses of the optimal strategies for DRRA and IRRA investors with respect to key parameters; (e.g. risk aversion, minimum capital guarantee and 4/2’s parameters). In particular, the efficient frontier for the IRRA case is presented. A comparison to important sub-optimal strategies in terms of CER is performed, indicating low CER performances due to ignorance of stochastic volatility for CRRA investors, i.e. a myopic strategy would be even better than ignoring SV. The analyses highlight the importance of efficient and precise numerical methods to obtain substantially higher CERs.

Portfolio optimization with optimal expected utility risk measures

The purpose of this article is to evaluate optimal expected utility risk measures (OEU) in a risk-constrained portfolio optimization context where the expected portfolio return is maximized. We compare the portfolio optimization with OEU constraint to a portfolio selection model using value at risk as constraint. The former is a coherent risk measure for utility functions with constant relative risk aversion and allows individual specifications to the investor’s risk attitude and time preference. In a case study with three indices, we investigate how these theoretical differences influence the performance of the portfolio selection strategies. A copula approach with univariate ARMA-GARCH models is used in a rolling forecast to simulate monthly future returns and calculate the derived measures for the optimization. The results of this study illustrate that both optimization strategies perform considerably better than an equally weighted portfolio and a buy and hold portfolio. Moreover, our results illustrate that portfolio optimization with OEU constraint experiences individualized effects, e.g., less risk-averse investors lose more portfolio value in the financial crises but outperform their more risk-averse counterparts in bull markets.

Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets

Using one-minute oil, gold and copper futures price from September 27, 2009, to July 1, 2020, this paper examines the effects of systematic and idiosyncratic (market-specific risk) jumps on intraday correlations, portfolio allocation decisions, and diversification benefits. We identify that these commodities contain high proportions of market-specific price discontinuities, which do not translate into systematic jumps. Co-jumps in the same direction lead to higher correlations and imply reduction in diversification benefits, while co-jumps in the opposite direction reduce correlations and positively affect diversification, similar to the idiosyncratic jumps. The results also demonstrate that the risk-averse investor’s gold portfolio allocations are not affected by co-jumps and are free from the non-diversifiable risks in oil and copper markets. However, idiosyncratic jumps in oil and copper markets increase allocations to gold. In contrast, allocations to copper and oil are significantly affected by the systematic risks outlined in copper–gold and oil–gold pairs, pushing risk-averse investors to oil from copper–gold and copper from oil–gold systematic risks. Finally, diversification benefits from price discontinuities are overall positive and driven by the idiosyncratic jumps in oil and copper markets when the minimum variance portfolio allocations are used.

Price impact, strategic interaction and portfolio choice

This paper studies the portfolio choice of two large investors who act strategically because their trading affects interest rates. Each investor chooses her optimal portfolio conditional on the portfolio of the opponent. Equilibrium portfolios and their performance depend on the investor’s characteristics (risk aversion and return impact) and on the characteristics of the opponent (risk aversion and return impact). Depending on the interplay among these characteristics, strategic interaction can (i) increase or decrease risk taking incentives, as compared to the Merton-style portfolio, (ii) induce the more risk-averse investor to invest relatively more in the risky asset and (iii) change the role of inflation-linked bonds from hedging instrument to borrowing opportunity.

A Bayesian Decision Model for Optimum Investment and Design of Low-Impact Development in Urban Stormwater Infrastructure and Management

Uncertainties concerning low-impact development (LID) practices over its service life are challenges in the adoption of LID. One strategy to deal with uncertainty is to provide an adaptive framework which could be used to support decision-makers in the latter decision on investments and designs dynamically. The authors propose a Bayesian-based decision-making framework and procedure for investing in LID practices as part of an urban stormwater management strategy. In this framework, the investment could be made at various stages of the service life of the LID, and performed with deliberate decision to invest more or suspend the investment, pending the needs and observed performance, resources available, anticipated climate changes, technological advancement, and users’ needs and expectations. Variance learning (VL) and mean-variance learning (MVL) models were included in this decision tool to support handling of uncertainty and adjusting investment plans to maximize the returns while minimizing the undesirable outcomes. The authors found that a risk-neutral investor tends to harbor greater expectations while bearing a higher level of risks than risk-averse investor in the VL model. Constructed wetlands which have a higher prior mean performance are more favorable during the initial stage of LID practices. Risk-averse decision-makers, however, could choose porous pavement with stable performance in the VL model and leverage on potential technological advancement in the MVL model.

Stock Portfolio Optimization Using a Combined Approach of Relative Robust Risk Parity

Risk parity is perceived as one of the stock portfolio selection models that have received a lot of attention since the US financial crisis in 2008. The philosophy of this model is to allocate the same amount of portfolio risk between the constituent assets. In the present study, the combined portfolio selection model of relative robust risk parity is introduced, which uses the worst-case scenario approach on the covariance matrix parameter appearing in the robust risk model in portfolio robustness. According to historical data, several scenarios are considered for the covariance matrix. The objective function value of the hybrid model for each portfolio (feasible point) is the worst result (with most volatility) among the set of scenarios. Finally, the model selects a portfolio for which the worst possible result has the least relative volatility. The research portfolio consists of 8 industries from Tehran Stock Exchange in the period 2011 to 2020. This portfolio has a higher Sharpe ratio than conventional models of mean-variance and weight parity, and is more resilient to market declines than the two models and produces less loss. Therefore, risk-averse investors are advised to use this stock portfolio selection model as a cover to face severe market declines.

Chinese securities investment funds: the role of luck in performance

Purpose The Chinese fund market has witnessed significant developments in recent years. However, although there has been a range of studies assessing fund performance in developed industries, the rapidly developing fund industry in China has received very little attention. This study aims to examine the performance of open-end securities investment funds investing in Chinese domestic equity during the period May 2003 to September 2020. Specifically, applying a non-parametric bootstrap methodology from the literature on fund performance, the authors investigate the role of skill versus luck in this rapidly evolving investment funds industry. Design/methodology/approach This study evaluates the performance of Chinese equity securities investment funds from 2003–2020 using a bootstrap methodology to distinguish skill from luck in performance. The authors consider unconditional and conditional performance models. Findings The bootstrap methodology incorporates non-normality in the idiosyncratic risk of fund returns, which is a major drawback in “conventional” performance statistics. The evidence does not support the existence of “genuine” skilled fund managers. In addition, it indicates that poor performance is mainly attributable to bad stock picking skills. Practical implications The authors find that the top-ranked funds with positive abnormal performance are attributed to “good luck” not “good skill” while the negative abnormal performance of bottom funds is mainly due to “bad skill.” Therefore, sensible advice for most Chinese equity investors would be against trying to “pick winners funds” among Chinese securities investment funds but it would be recommended to avoid holding “losers.” At the present time, investors should consider other types of funds, such as index/tracker funds with lower transactions. In addition, less risk-averse investors may consider Chinese hedge funds [Zhao (2012)] or exchange-traded fund [Han (2012)]. Originality/value The paper makes several contributions to the literature. First, the authors examine a wide range (over 50) of risk-adjusted performance models, which account for both unconditional and conditional risk factors. The authors also control for the profitability and investment risks in Fama and French (2015). Second, the authors select the “best-fit” model across all risk-adjusted models examined and a single “best-fit” model from each of the three classes. Therefore, the bootstrap analysis, which is mainly based on the selected best-fit models, is more precise and robust. Third, the authors reduce the possibility that findings may be sample-period specific or may be a survivor (upward) biased. Fourth, the authors consider further analysis based on sub-periods and compare fund performance in different market conditions to provide more implications to investors and practitioners. Fifth, the authors carry out extensive robustness checks and show that the findings are robust in relation to different minimum fund histories and serial correlation and heteroscedasticity adjustments. Sixth, the authors use higher frequency weekly data to improve statistical estimation.