Growth opportunities and asymmetric risk: An empirical investigation of upside and downside Beta

ABSTRACT This study investigates how institutional ownership (IO) and free float (FF) jointly affect firms’ systematic risks. It contends that larger institutional stakes increase the dollar imbalance subject to common flows, whereas a greater tradable float broadens the set of funds that can trade synchronously. Both channels should increase the stock market beta. Using a cross-section of 12,655 non-financial firms from 93 countries, unconditional, downside (β−), and upside (β+) capital asset pricing model betas over two-, three-, and five-year windows are analysed. The results confirm that IO and FF are positively and significantly associated with unconditional and downside betas. These relationships remain robust after controlling for firm size, valuation, profitability, leverage, liquidity, and industry fixed effects, indicating that the ownership and tradability channels explain systematic risk beyond standard fundamentals. The impact of IO is pronounced for upside beta. Two-stage least squares regressions corroborate the baseline results while addressing endogeneity concerns. Additional tests show that the IO effect is concentrated in advanced economies, while the FF effect remains robust across geography, development status, and firm size. This study evinces the trading flow hypothesis that ownership concentration and tradability are the additive drivers of systematic risk.

Purpose This study aims to investigate the asymmetric responses of the sectoral exchange-traded funds in the USA to extreme market conditions by estimating upside and downside betas across the left and right tails of the market return distribution. The authors identify which sectors exhibit defensive or aggressive characteristics during market downturns and upturns. Design/methodology/approach Using daily return data from January 1, 1999, to October 17, 2023, the study applies threshold regression models to estimate sector-specific betas under three tail-risk scenarios: 5%, 10% and an optimally determined threshold. The analysis is conducted across the full sample and sub-periods (pre- and post-global financial crisis) to assess robustness and structural shifts. Findings The results reveal that consumer staples, health care and utilities consistently exhibit downside betas below unity, confirming their defensive nature. In contrast, financials and technology demonstrate higher upside betas, indicating strong performance during market rallies. Particularly, technology is the only sector with an upside beta consistently exceeding its downside beta across all thresholds and periods. Originality/value To the best of the authors’ knowledge, this study is the first to assess sectoral ETF behavior under extreme market conditions using multiple tail thresholds and long-term high-frequency data. By distinguishing between upside and downside risks, it offers insights for passive and institutional investors seeking to optimize portfolio performance during volatile market phases.

Forecasting downside betas with multi-period components

Abstract Using monthly data from July 2011 to July 2024, we estimate and compare the upside and downside betas across eleven well-established real estate exchange-traded funds (ETFs), alongside an aggressive growth (tech) fund and a defensive (utility) fund. We also examine the return per unit of risk using the Calmar, Martin, Omega, Sharpe, and Sortino ratios, with a particular emphasis on extreme downside risk. Furthermore, we employ a non-radial directional distance model to rank the risk-adjusted return inefficiency of the sampled funds relative to a best-practice frontier constructed from the above complementary measures. This approach provides a comparative understanding of how these metrics can better capture the complexities of downside risk and inform investment decisions in the real estate sector. It is found that the most inefficient funds also exhibit the highest downside betas, revealing a critical vulnerability in their performance during adverse market conditions. Not all real estate funds are created equal, as some demonstrate a greater ability to manage downside risk and maintain efficiency relative to the best-practice frontier. Given the importance of raising capital in the equity market for both residential and commercial real estate, our results offer valuable insights for making investment decisions within a multidimensional benchmarking framework.

Abstract In four large online experiments, we study how investors assess the relationship between stock portfolios and the market. Participants select or are randomly assigned a portfolio of stocks from a market index. They state portfolio return expectations conditional on different market outcomes, revealing implied beliefs about portfolio beta. We find general underestimation of beta which is stronger for downside beta. This asymmetry is amplified for participants who select their portfolio. They believe their portfolio goes up with the market but does not come down with it. We confirm biased beliefs about beta with financial professionals, monetary incentives, and alternative belief elicitation methods.

This study includes alternative portfolio construction approaches consistent with the Modern Portfolio Theory (MPT) and Postmodern Portfolio Theory (PMPT). We propose a weighting strategy based on Sharpe and Sortino optimization, and unlike MPT, we create PMPT portfolios using downside metrics, such as downside risk, downside beta, and downside capital asset pricing model (D-CAPM). Portfolios consist of stocks in the Borsa Istanbul Participation 30 Index (XK030), with the stocks in the portfolio having been revised according to screening periods. In addition, we created an equally weighted portfolio and used XK030 as a benchmark for comparative analysis. The sample period covers 527 trading days between May 6, 2022, and June 28, 2024. The results show that the Sharpe portfolio consistently follows the benchmark index throughout the observation period. Sortino outperforms both the benchmark and conventional market index in some specific periods when the market has an upward trend, especially. This study provides evidence that the MPT and PMPT approaches and measures can be used in asset allocation and portfolio management. Investors can manage their assets and balance portfolio weights by implementing the models in different market conditions.

Investors are exploring new ways to navigate the constantly changing equity markets in emerging economies. Smart beta strategies, which use rule-based algorithms to boost returns and manage risk, are emerging as a promising solution. This research investigates how effective smart beta strategies are for retail investors. In contrast to a benchmark index, the study evaluates various smart beta strategies, including high alpha, beta, low volatility, value, growth, quality, momentum investing and combination strategies that consist of more than one factor. Based on the daily data from 1 October 2009 to 31 March 2023 of these strategic indices, the findings reveal that all strategies excluding the beta factor strategy consistently outperform benchmark index on various risk-adjusted return metrics. Notably, the momentum strategy closely followed by the alpha strategy is the best-performing approach for medium- and long-term horizons. Based on the data, these smart beta strategies have a greater downside beta than an upward beta, which suggests that they are more sensitive to declining markets. Comparatively, the combination strategies exhibit reduced sensitivity to declining markets, highlighting the safety and benefits of diversification among smart beta strategies. Furthermore, many of these techniques regularly outperform market returns and show effective market timing. These insightful observations help investors understand how smart beta strategies can be beneficial and strategically used in volatile market environments.

Purpose- The purpose of this study is to construct a portfolio based on downside beta as a measure of downside risk. The analysis uses data from all listed companies on the Pakistan Stock Exchange (PSE) over the period from January 2000 to December 2021. Study Design/Methodology/Approach - The study employs a rolling window approach with 36 consecutive months to estimate downside beta values for portfolios ranked from lowest to highest downside beta. Portfolio returns are evaluated using the Generalized Method of Moments (GMM) in conjunction with the Capital Asset Pricing Model (CAPM) and the Fama-French three- and five-factor models. A six-month Treasury bill rate is used as the risk-free rate. Findings- The study reveals a significant spread between the downside beta values of the constructed portfolios, confirming that downside risk can be effectively captured through this approach. The hypothesis of equal mean downside beta across the portfolios is rejected, indicating that portfolios based on downside beta exhibit different risk-adjusted returns. Furthermore, the rejection of the alpha equal to zero hypothesis suggests that these risk-adjusted returns are statistically significant. However, the study finds that lower partial moments do not fully explain the variation in downside risk. Practical Implications- These findings are particularly relevant for investors focused on managing downside risk. The study offers alternative methods for constructing portfolios that account for downside risk, which could enhance risk management strategies. However, the reliance on historical data from the PSE may limit the generalizability of these findings to other markets. Originality/Novelty - This study contributes to the literature by constructing portfolios grounded in downside beta as a measure of downside risk, offering a novel approach to portfolio formation and risk-adjusted return evaluation. It highlights the importance of incorporating downside risk in portfolio management and presents an innovative application of downside beta within the context of emerging markets.

The paper provides the most recent view on the difference in ERP (Equity Risk Premiums) across various economic regions, analyzing data sets from the early 2000s to May 2023. The study demonstrates a significant shift in the relationship between ERPs in emerging and developed markets over the past two decades, which runs contrary to the existing research on the matter. The author estimated the average ERPs per country and economic region, analyzed ERPs on the industry level, and conducted the regression analysis using macroeconomic factors and analysis of upside and downside betas. The research established that, following the 2008 economic crisis, developed markets displayed greater resilience to negative economic shocks. Moreover, investing in emerging markets entails higher risks, characterized by elevated negative beta and higher volatility, but also increased upside beta. The regression analysis revealed negative associations between ERP and higher GDP growth and local interest rates, while a positive correlation emerged with a higher unemployment rate. Additionally, the paper incorporates the Democracy Index, indicating that less democratic countries tend to exhibit higher ERPs.

ABSTRACT This study examines the explanatory power of the CAPM and downside risk asset pricing models (the downside beta and the realized semibeta models) for the next-month firm-level cross-sectional stock return variation in the Australian stock market. We show that the CAPM beta, downside beta, semibeta BetaNP, and semibeta BetaNN negatively predict future stock returns, which is inconsistent with the findings in the original study by Bollerslev, Patton, and Quaedvlieg (2022). The BetaNN measures the individual stock movement in the same direction as the downward stock market, while BetaNP measures individual stock downward with the upward stock market. These findings are robust, not subsumed by conventional cross-sectional asset pricing factors, and consistent with the existing Australian downside risk study.

Several scholars pinpointed many predicaments in Sharpe's (1964) beta leading to the introduction of downside framework by Markowitz (1959). Subsequently, later studies investigated downside beta and its effectiveness in developed and developing markets. Egypt, an emerging market, exhibits characteristics such as thin trading, illiquidity, small number of listed firms, and relatively weaker corporate governance enforcement, which impacts its market efficiency. Thus, conventional beta designed and tested in developed markets may fail to account for these unique circumstances that exist in emerging countries as Egypt. This study aims to address this gap in the literature by testing the validity of conventional and downside risk measures using data from 55 Egyptian equity funds from 2012 to 2022. Fama & MacBeth's (1973) two-stage regression was employed. In the first stage, the downside beta was employed using Estrada's (2002) approach. Afterwards, the funds' excess returns over risk-free rate are regressed on the funds' risk measures. Results suggest a slight advantage for downside beta, indicated by a higher adjusted Rsquared. Moreover, a robustness check was employed by dividing the sample into two sub-periods. The findings revealed that the conventional beta is unstable, while downside beta demonstrated consistent and significant results. These empirical findings align with previous studies by Yildiz et al. (2022 ), Ruthkowska-Ziarko et al. (2022 ), and Alrabadi et al. (2022) .

The importance of Environmental, Social, and Governance (ESG) aspects in investment decisions has grown significantly in today’s volatile financial market. This study aims to answer the important question of whether investing in ESG-compliant companies is a better option for investors in both developed and emerging markets. This study assesses ESG investment performance in diverse regions, focusing on developed markets with high GDP, specifically the USA, Germany, and Japan, alongside emerging nations, India, Brazil, and China. We compare ESG indices against respective broad market indices, all comprising large and mid-cap stocks. This study employs a variety of risk-adjusted criteria to systematically compare the performance of ESG indices against broad market indices. The evaluation also delves into downside volatility, a crucial factor for portfolio growth. It also explores how news events impact ESG and market indices in developed and emerging economies using the EGARCH model. The findings show that, daily, there is no significant difference in returns between ESG and conventional indices. However, when assessing one-year rolling returns, ESG indices outperform the overall market indices in all countries except Brazil, exhibiting positive alpha and offering better risk-adjusted returns. ESG portfolios also provide more downside risk protection, with higher upside beta than downside beta in most countries (except the USA and India). Furthermore, negative news has a milder impact on the volatility of ESG indices in all of the studied countries except for Germany. This suggests that designing a portfolio based on ESG-compliant companies could be a prudent choice for investors, as it yields relatively better risk-adjusted returns compared to the respective market indices. Furthermore, there is insufficient evidence to definitively establish that the performance of ESG indices varies significantly between developed and emerging markets.

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

ABSTRACT This study adopts a composite threshold model that differentiates between the upside and downside betas of the major US-based renewable and non-renewable exchange-traded funds (ETFs) during heightened uncertainty. It is found that downside betas for both renewable and non-renewable energy ETFs are significantly greater than upside betas. However, in a highly uncertain market, renewable energy ETFs tend to enjoy higher upside gains than the fossil-fuel ETFs. The results suggest that renewable energy ETFs have great potential to generate high returns, but the downside risk associated with renewables should be mitigated by government incentivizing the use of renewables in both domestic and foreign markets. Investing in renewable energy is not only good for the environment but also compared to other investment alternatives (including fossil fuels) it provides better risk-adjusted returns. During the last 5 years, some renewable energy ETFs have even outperformed several well-established sectoral ETFs. This paper finds that there is a more favourable business case for investing in renewables than common perception would suggest.

Asymmetric downside risk across different sectors of the US equity market

PurposeMany studies have shown that from a theoretical and empirical point of view, downside risk-based measures of risk are better than the traditional ones. Despite academic appeal and practical implications, downside risk has not been thoroughly examined in markets outside developed country markets. Using downside beta as a measure of downside risk, this study examines the relationship between downside beta and stock returns in Indian equity market, an emerging market with unique investor, asset and market characteristics.Design/methodology/approachThis is an empirical study done by using ranked portfolio return analysis and regression analysis methodologies.FindingsThe study results show that downside risk, as measured by downside beta, is distinctly priced in the Indian equity market. There is a direct positive relationship between downside beta and contemporaneous realized returns, indicating a premium for downside risk. Downside risk carries a higher weightage than upside potential in the aggregate return of the stock portfolios. Downside beta is a better measure of systematic risk than conventional market beta and downside coskewness.Practical implicationsThe empirical results support the adoption of downside beta in practice and provide a case for replacing traditional beta with downside beta in asset pricing applications, trading and investment strategies, and capital allocation decision-making.Originality/valueThis is one of the first in-depth studies examining downside beta in Indian equity markets using a broad sample of individual stock returns covering a wide time range of 22 years. To the best of our knowledge, this study is the first one to compare downside beta and downside coskewness using individual stock data from the Indian equity market.

This study examines downside risk matters in asset pricing, particularly evidence from Indonesia. Using ten reference indexes for passive instruments and 674 companies listed on the Indonesia Stock Exchange between 2020-2021. The four measurements are the traditional families (beta and standard deviation/risk) and downside risk families (semi-deviation and downside beta). For those, we divide 674 stocks into quintiles (5 groups). Every quintile is investigated by four measurements using Fama-Macbeth regression. semi-deviation in those close to standard deviation. Standard deviation affects semi-deviation portfolios in quintiles 1 and 2 and portfolios sorted beta and downside beta in quintile 2. Beta does not affect all portfolios. Eighth, semi-deviation affects portfolios sorted semi-deviation in quintiles 1,2,3,and 5. Downside beta does not affect all portfolios.

A novel downside beta and expected stock returns

Abstract This study investigates the relationship between insurance sectors' global value chain (GVC) positions and insurance firms' tail risk. Using a sample of 208 insurers from 25 countries between 2000 and 2015, we find that insurers' tail risk (i.e., expected shortfall, downside beta, and marginal expected shortfall) increases when an insurance sector's GVC upstreamness indices increase. This result suggests that when an insurance sector becomes more upstream in the global production network, the comovement between insurers' stock returns and the market returns become stronger and insurers become more exposed to market tail risk. By testing over a subsample of non‐US insurers and a sample period excluding the 2008 Global Financial Crisis, we show that our main results remain unchanged. We also use 2SLS with instrumental variables to address the potential endogeneity problem. Using the nonfinancial sectors' GVC positions as the instrumental variable, we find that the main results are robust to the bias associated with any endogeneity problem. This paper provides the first empirical evidence that highlights the role of GVC linkages in tail risk spillover among insurers around the globe. Our findings have important policy implications for the regulation of insurance firms.