Downside Beta Research Articles

Risk Premium for Emerging Market Equities Versus Developed Market Equities

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.

Realized semibetas in the Australian stock market

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.

Does downside beta matter in asset pricing? Evidence from the Egyptian Stock Exchange

Does downside beta matter in asset pricing? Evidence from the Egyptian Stock Exchange

An Analysis of Volatility and Risk-Adjusted Returns of ESG Indices in Developed and Emerging Economies

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

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

Performance of renewable and non-renewable exchange-traded funds during heightened uncertainty

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

This study integrates a threshold-mean equation with an asymmetric power autoregressive conditionally heteroscedastic (APARCH) model to examine the behavior of sector-specific exchange-traded funds (ETFs) during extreme market downturns between December 23, 1998, and November 2, 2022. Thus, predetermined and optimal boundary points are applied to the extreme left tail of the return distribution to assess the extent of downside risk differentials inside and outside the extreme drawdown zone without splitting the sample period. According to the findings, the betas of the ETFs XLI, XLP, XLV, and XLY are comparable under both extreme and nonextreme market conditions. In contrast, XLF, XLE, and XLU have higher downside betas during extreme market conditions compared with their nonextreme betas, while XLB and XLK exhibit the opposite pattern. The results remain robust and consistent regardless of how the boundary points are established. The estimated models in this study were successfully subjected to a series of diagnostic tests, suggesting that the commonly held view about asymmetric responses in different market conditions does not apply to all market segments.

Examining significance of “downside beta” as a measure of risk – evidence from Indian 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.

Does Downside Risk Matter more in Asset Pricing? Evidence from Indonesia

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

A number of studies have found that the cross-section of stock returns reflects a risk premium for bearing downside beta; however, existing measures of downside beta have poor power for predicting returns. This paper proposes a novel measure of downside beta, the ES-implied beta, to improve the prediction of the cross-section of asset returns. The ES-implied beta explains stock returns over the same period as well as the widely used downside beta, but improves the prediction for future returns due to its high persistence. In the empirical analysis, the widely used downside beta shows a weak relation with future expected returns, but the ES-implied beta implies a statistically and economically significant risk premium of 0.6% per month and explains 0.6% of the variation in the cross-sectional returns. The effect cannot be explained by traditional cross-sectional effects and is different from the CAPM beta, the downside beta in Ang et al. (2006), coskewness, and cokurtosis.

Cross‐country evidence on the relationship between global value chain position and the tail risk of insurers

AbstractThis 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.

Conventional and downside CAPM: The case of London stock exchange

Many studies on asset pricing have highlighted the importance of downside risk, in line with the actual losses of investors. In addition, the capital asset pricing model (CAPM), although presented as a universal theory, may provide significantly different rates of return in bull and bear markets. Using the CAPM under different conditions could be regarded as an alternative measurement and valuation approach to downside risk. This paper investigates conventional and downside approaches to risk taking into account different measures of downside beta coefficients. A further contribution of this research is the development of an alternative approach to testing the CAPM relationship. For this purpose, conditional relationships of the CAPM are proposed in which risk premiums are set separately in bull and bear periods. Using equity data and portfolios from the United Kingdom, we obtained positive and statistically significant downside risk premiums. We observed a slight advantage of downside measures over conventional beta measures. Conditional models provide evidence of a positive risk premium in rising markets and a negative risk premium in falling markets. The robustness analysis in subperiods indicates that these findings are largely unchanged for downside beta coefficients, which is not fulfilled by the model in a variance approach.

Drawdown beta and portfolio optimization

This paper introduces a new dynamic portfolio performance risk measure called Expected Regret of Drawdown (ERoD) which is an average of the drawdowns exceeding a specified threshold (e.g. 20%). ERoD is similar to Conditional Drawdown-at-Risk (CDaR) which is the average of some percentage of the largest drawdowns. CDaR and ERoD portfolio optimization problems are equivalent and result in the same set of optimal portfolios. Necessary optimality conditions for ERoD portfolio optimization lead to Capital Asset Pricing Model (CAPM) equations. ERoD Beta, similar to the Standard Beta, relates returns of the securities and those of a market. ERoD Beta is equal to [average losses of a security over time intervals when market is in drawdown exceeding the threshold] divided by [average losses of the market in drawdowns exceeding the threshold]. Therefore, a negative ERoD Beta identifies a security which has positive returns when the market has drawdowns exceeding the threshold. ERoD Beta accounts only for time intervals when the market is in drawdown and conceptually differs from Standard Beta which does not distinguish up and down movements of the market. Moreover, ERoD Beta provides quite different results compared to the Downside Beta based on Lower Semi-deviation. ERoD Beta is conceptually close to CDaR Beta which is based on a percentage of worst case market drawdowns. However, ERoD Beta has some advantage compared to CDaR Beta because the magnitude of the drawdowns is known (e.g. exceeding a 20% threshold), while CDaR Beta is based on a percentage of the largest drawdowns with unknown magnitude. We have built a website reporting CDaR and ERoD Betas for stocks and the SP 500 index as an optimal market portfolio. The case study showed that CDaR and ERoD Betas exhibit persistence over time and can be used in risk management and portfolio construction.

A trading strategy with dual-beta estimates

PurposeThe purpose of this paper is to adopt a trading strategy using upside and downside beta estimates.Design/methodology/approachWith daily data from April 30, 1997 to April 30, 2021, the author utilizes the dual-beta model when estimating upside and downside betas, in constructing and rebalancing a portfolio from a buy list of Dow Jones Industrial Average component stocks. Benchmarks include the S&P 500 Total Return index, Invesco S&P 500 Low Volatility ETF (SPLV) and iShares MSCI USA Min Vol Factor ETF (USMV). The dual-beta portfolio performance is assessed by economic cycles and by the Fama-French five-factor model.FindingsThe dual-beta portfolio outperforms the benchmarks for the whole period under study as well as the majority of sub-periods. It is the only strategy with a statistically positive and economically significant risk-adjusted return.Originality/valueThe author offers a simple stock trading strategy for generating wealth.

Downside Beta and Downside Gamma: In Search for a Better Capital Asset Pricing Model

In the financial world, the importance of “downside risk” and “higher moments” has been emphasized, predominantly in developing countries such as Pakistan, for a substantial period. Consequently, this study tests four models for a suitable capital asset pricing model. These models are CAPM’s beta, beta replaced by skewness (gamma), CAPM’s beta with gamma, downside beta CAPM (DCAPM), downside beta replaced by downside gamma, and CAPM with downside gamma. The problems of the high correlation between the beta and downside beta models from a regressand point of view is resolved by constructing a double-sorted portfolio of each factor loading. The problem of the high correlation between the beta and gamma, and, similarly, between the downside beta and downside gamma, is resolved by orthogonalizing each risk measure in a two-factor setting. Standard two-pass regression is applied, and the results are reported and analyzed in terms of R2, the significance of the factor loadings, and the risk–return relationship in each model. The risk proxies of the downside beta/gamma are based on Hogan and Warren, Harlow and Rao, and Estrada. The results indicate that the single factor models based on the beta/downside beta or even gamma/downside gamma are not a better choice among all the risk proxies. However, the beta and gamma factors are rejected at a 5% and 1% significance level for different risk proxies. The obvious choice based on the results is an asset pricing model with two risk measures.

The Relationship between Asymmetric Downside Beta and Stock Returns : Evidence from the Korean Stock Market

The Relationship between Asymmetric Downside Beta and Stock Returns : Evidence from the Korean Stock Market

Anomalies in Commodity Futures Markets

In recent years, commodity markets have become increasingly popular among financial investors. While previous studies document a factor structure, not much is known about how prominent anomalies are priced in commodity futures markets. We examine a large set of such anomaly variables. We identify sizable premia for jump risk, momentum, skewness, and volatility-of-volatility. Other prominent variables, such as downside beta, idiosyncratic volatility, and MAX, are not priced in commodity futures markets. Commodity investors should rebalance their portfolios regularly. Returns for annual holding periods are substantially weaker than for monthly rebalancing.

Portfolio Upside and Downside Risk—Both Matter!

Traditional performance measures do not distinguish between <i>upside risk</i> and <i>downside risk</i>. Downside risk is based on returns that are below a target rate, below zero, below average, or below a benchmark, and vice versa for upside risk. Downside risk measures and the “duality” of beta have been discussed extensively in literature related to public markets but have not been applied to the analysis of private equity real estate in the academic literature. This article examines the measures that can distinguish between upside and downside risk that are commonly used in public markets, such as upside and downside beta and the Sortino ratio for downside analysis, and applies them to different property sectors and Core-Based Statistical Areas in the NCREIF Property Index. In addition, these measures are used to analyze gateway versus nongateway markets’ historical performance on both an upside and downside risk basis. The same techniques are applied to perform an attribution analysis of a portfolio’s alpha into upside and downside components. <b>Key Findings</b> ▪ The authors show that downside risk measures such as the Sortino ratio and downside beta can provide insights into what drives returns for different property sectors and Core-Based Statistical Areas, as well as gateway versus nongateway markets. ▪ Using the upside to downside beta ratio, the authors show how property sectors and markets vary as to whether beta is magnifying return on the upside and/or minimizing declines on the downside. ▪ By using the duality of beta, the authors show how to decompose the risk-adjusted overperformance or underperformance into upside and downside alpha earned by a portfolio, a complement to traditional Brinson attribution analysis.

Do Asymmetries in the Indian Equity Market Exist during the COVID-19?

ABSTRACT This paper investigates the presence of asymmetry in correlations, betas and covariances between the market excess return and the excess return on each of the eleven industry, ten size, ten momentum and ten book-to-market portfolios. We arrive at three main findings. First, there is strong evidence of asymmetric covariance while the evidence for asymmetric correlations is weakest during COVID-19 period. Second, momentum and book-to-market portfolios exhibit strong evidence of asymmetry relative to the size and industry portfolios. Third, regardless of a single exceedance level or four exceedance levels, the downside correlations, betas and covariances are higher than the upside correlations, betas and covariances.

A remark on mean‐semivariance behaviour: Downside risk and capital asset pricing

AbstractIn the conventional capital asset pricing model (CAPM), standard deviation as a measure of risk penalizes both upward and downward movements. However, while downward movements in investments are risky, upward movements are favourable. Therefore, standard semideviation that treats only those negative differences in returns over the benchmark as risky was proposed as a measure of downside risk. Attempts have been made to obtain the formulation of beta in this context, called downside beta. In this work, CAPM in the mean‐semivariance framework (D‐CAPM), with semivariance measured in terms of negative deviation around expected return, is derived and established that the model proposed earlier with a version of downside beta with respect to this definition of semivaraince is invalid. The appropriate version of downside beta is obtained, and under the rectified formulation, the validity of the true D‐CAPM is empirically tested during July 2013–July 2018. The solution to the tangent point is also obtained. The proportion of investment in the stocks in the tangent portfolio and the downside beta for the stocks in the tangent portfolio are determined. We find that there is no evidence to disprove that D‐CAPM holds true considering either Nifty 50 or S&amp;P BSE Sensex as market portfolio.