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The purpose of this paper is to examine the asymmetric dynamic rotation of beta coefficients to global investment style factor shocks in the Morgan Stanley Capital International (MSCI) universe of assets and its implications for investment management.

The paper uses an asymmetric extension of the Christodoulakis and Satchell approach of time varying beta coefficients.

Evidence suggests that positive (negative) style factor shocks tend to be associated more with increases (decreases) in beta coefficients rather than the reverse.

There is a need to examine other forms of beta rotation and the degree of common persistence and empirical applications to investment management and portfolio performance attribution.

Forecast the evolution of beta. Persistent positive or negative shocks could spark rotating investment exposures, particularly relevant during turbulent periods in which asset managers may engage onto tactical asset allocation strategies.

The paper explores the asymmetric rotation of style factors in the MSCI universe of assets. The results can be used in applied investment management involving dynamic asset allocation strategies.

This paper aims to enhance a co-skew-based risk measurement methodology initially introduced in Polimenis, by extending it for the joint estimation of the jump betas for two stocks.

The authors introduce the possibility of idiosyncratic jumps and analyze the robustness of the estimated sensitivities when two stocks are jointly fit to the same set of latent jump factors. When individual stock skews substantially differ from those of the market, the requirement that the individual skew is exactly matched is placing a strain on the single stock estimation system.

The authors argue that, once the authors relax this restrictive requirement in an enhanced joint framework, the system calibrates to a more robust solution in terms of uncovering the true magnitude of the latent parameters of the model, at the same time revealing information about the level of idiosyncratic skews in individual stock return distributions.

Allowing for idiosyncratic skews relaxes the demands placed on the estimation system and hence improves its explanatory power by focusing on matching systematic skew that is more informational. Furthermore, allowing for stock-specific jumps that are not related to the market is a realistic assumption. There is now evidence that idiosyncratic risks are priced as well, and this has been a major drawback and criticism in using CAPM to assess risk premia.

Since jumps in stock prices incorporate the most valuable information, then quantifying a stock's exposure to jump events can have important practical implications for financial risk management, portfolio construction and option pricing.

This approach boosts the “signal-to-noise” ratio by utilizing co-skew moments, so that the diffusive component is filtered out through higher-order cumulants. Without making any distributional assumptions, the authors are able not only to capture the asymmetric sensitivity of a stock to latent upward and downward systematic jump risks, but also to uncover the magnitude of idiosyncratic stock skewness. Since cumulants in a Levy process evolve linearly in time, this approach is horizon independent and hence can be deployed at all frequencies.

The assembly is often a weak link in the production process. It is an enterprise activity which is responsible for a substantial part of the production costs and the throughput time. Robot assembly systems in addition offer legitimate possibilities to rationalize the assembly activities, because of the increasing product diversity, and the more severe demands concerning the reliability of delivery. Unfortunately several bottlenecks hinder the widespread application of robot assembly systems. Figure 1 gives an overview of the bottlenecks and the development tendencies in robotic assembly.

This paper aims to study the cross section of expected returns on Shari’ah-compliant stocks in Pakistan by using single- and multi-factor asset pricing models.

To estimate cross section of expected returns of Shari’ah-compliant stocks, the study uses capital asset pricing model (CAPM), Fama-French three-factor model and Fama-French five-factor model. Data for the period 2001-2015 on 217 companies are used. For the market portfolio, PSX-100 and Dow Jones Islamic Index for Pakistan are used.

The study could not find empirical support for CAPM using Lintner (1965), Black et al. (1972) and Fama and Macbeth (1973) approach. Nonetheless, the relation between beta and returns is positive in up-market and negative in down-market. The results of Fama-French three-factor and five-factor models suggest that size premium is positive and significant for explaining the cross section of stock returns of small size stocks, whereas value premium is positive and significant for explaining the cross section of returns of high value stocks.

The results suggest that fund managers can use Shari’ah-compliant stocks for portfolio diversification and for offering specialized investments given the positive market excess returns and the existence of size and value premium on Shari’ah-compliant stocks.

This is the first study on Fama-French (2015) five-factor model for Islamic capital markets in Pakistan.

The aim of this study is to examine real estate investment trust exchange-traded funds (REIT ETFs) and test for the existence of the “asymmetric beta puzzle” phenomenon in these financial instruments that are relatively new and are gaining popularity. The “asymmetric beta puzzle” phenomenon is used to identify the hedging and diversification benefits of a financial instrument. “Asymmetric beta puzzle” exists when betas in declining markets are higher than betas in advancing markets.

To study 14 REIT ETFs by using monthly and daily Center for Research in Security Prices (CRSP) data. Capital asset pricing model (CAPM) and Fama–French three-factor model were used to estimate betas in REIT ETFs and those in advancing and declining markets. Both the S&P 500 and the CRSP value-weighted indices were used in the beta estimation. Two hypotheses with regard to betas in both advancing and declining markets were defined and tested to test for the existence of the “asymmetric beta puzzle” phenomenon.

This study confirms the presence of the “asymmetric beta puzzle” in the data of monthly REIT ETFs as documented by Goldstein and Nelling (1999) and Chatrath et al. (2000) for REITs; however, this phenomenon was not found when using daily data, but quite the opposite – REIT ETF betas are higher in advancing markets than they are in declining markets – was found.

Goldstein and Nelling (1999) and Chatrath et al. (2000) identify the phenomenon of “the asymmetric REIT-beta puzzle” in monthly REIT’s returns. This study revisits the phenomenon identified in the aforementioned authors’ studies by using daily data and a relatively new real estate financial instrument – REIT ETFs. Therefore, this paper fills a void in the literature and would benefit both institutional and retail investors in their portfolio designs.

This study seeks to evaluate, in a global context, the impact of Sarbanes Oxley Act on a particular risk measure of importance to investors (risk‐adjusted returns), and two measures of risk due to asymmetry (upside and downside risk). A unique dataset permits a dual evaluation of the law's impact on such measures in leading non‐US economies as well (i.e. “ripple effects”).

Hypotheses are empirically evaluated on a sample (n=712) of the largest US and European firms (control) using daily return data from 1993 through 2009 – one of the most extensive data sets employed in the literature on this topic to date. The reliability of the risk measures is carefully evaluated using multiple approaches, including Fama‐MacBeth regressions. A series of difference‐in‐difference analyses is then employed to empirically assess Sarbanes Oxley's impact on equity risk.

The findings suggest Sarbanes Oxley decreased both risk‐adjusted returns and upside risk, whereas downside risk fails to explain the cross section of returns for the largest US firms. From a global perspective, it is suggested that the enactment of Sarbanes Oxley's in the USA motivated leading non‐US economies to adopt similar regulatory measures, which caused “ripple effects” – e.g. effects similar to those documented in this paper – in leading non‐US economies.

The findings suggest that comprehensive financial regulations, such as Sarbanes Oxley Act, are properly envisaged at the global level, as their impact is not confined to the home country. In an increasingly globalized economy, investor welfare is likely to be influenced – directly as well as indirectly – by economic and financial regulation(s) enacted in foreign economies. Arguably, this suggests the pivotal importance of effective mechanisms of global governance, such that a purely domestic approach to regulation may be short‐sighted. In either case, the findings of this study are entirely relevant if regulators are to consider the broader, global impact of regulation on investor welfare.

This is the first study to empirically analyze, within a global framework, Sarbanes Oxley's risk implications without relying on a series of simple mean variance analyses. Substantive research documents that the methodological approach employed is more precise, reliable as well as “investor relevant”. Furthermore, the authors seek to assess the law's impact on leading non‐US equity markets, a first for the literature. Consequently, this study provides a robust evaluation of the law's (international) impact on firm (equity) risk, making an important contribution to the literature.

This study aims to propose a model-free statistic that tests asymmetric correlations of stock returns, in which stocks move more often with the market when the market goes down than when it goes up, and then empirically analyze the asymmetric correlations of the China stock market and international stock markets, respectively.

Using empirical likelihood method, this study designs and conducts a model-free test, which converges to χ2 distribution under regulated conditions and performs well in the finite sample using bootstrap critical value method.

By analyzing the authors' model-free test, the authors find that compared with Hong et al.'s test that closely relates to the authors, both of the tests are under rejected using asymptotic critical value. However, using the bootstrap critical value method can greatly improve the performance of the two tests. Second, investigating the power of the two tests, the authors find that the proportion of rejections of the authors' test is roughly 10-20 percent larger than Hong et al.'s test in mixed copula model setting. The last finding is the authors find evidence of asymmetric for small-cap size portfolios, but no evidence for middle-cap and large-cap size portfolios in the China stock market. Besides, the authors test asymmetric correlations between the USA and Japan, France and the UK; the asymmetric phenomenon exists in international stock markets, which is similar to Longin and Solnik's findings, but they are not significant according to both the authors' test and Hong et al.'s test.

The findings in this study suggest that both the authors' test and Hong et al.'s test are under rejected using asymptotic critical value. When applying these statistics to test asymmetric correlations, the authors should take care with the choice of critical value.

The empirical analysis has a significant practical implication for asset allocation, asset pricing and risk management fields.

This study constructs a model-free statistic to test asymmetric correlations using empirical likelihood method for the first time and corrects the size performance by bootstrap method, which improves the performance of Hong et al.'s test. To the authors' knowledge, this is the first study to test the asymmetric correlations in the China stock market.

This study aims to investigate the risk-return trade-off in the Indian equity market at both the aggregate equity market level and in the cross-sections of stock return using alternative risk measures.

The study uses weekly and monthly data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019. The study evaluates the risk-return trade-off at the aggregate equity market level using the value-weighted and the equal-weighted broader portfolios. Eight different risk proxies belonging to the conventional, downside and extreme risk categories are considered to analyse the cross-sectional risk-return relationship.

The results show a positive equity premium on the value-weighted portfolio; however, the equal-weighted portfolio of these stocks shows an average return lower than the return on the 91-day Treasury Bills. The inverted size premium mainly causes this anomaly in the Indian equity market as the small stocks have lower returns than big stocks. The study presents a strong negative risk-return relationship across different risk proxies. However, under the subsample of more liquid stocks, the low-risk anomaly regarding other risk proxies becomes moderate except the beta-anomaly. This anomalous relationship seems to be caused by small and less liquid stocks having low institutional ownership and higher short-selling constraints.

The findings have important implications for investors, managers and practitioners. Investors can incorporate the effects of different highlighted anomalies in their investment strategies to fetch higher returns. Managers can also use these findings in their capital budgeting decisions, resource allocations and other diverse range of direct and indirect decisions, particularly in emerging markets such as India. The findings provide insights to practitioners while valuing the firms.

The study is among the earlier attempts to examine the risk-return trade-off in an emerging equity market at both the aggregate equity market level and in the cross-sections of stock returns using alternative measures of risk and expected returns.

Many 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.

This is an empirical study done by using ranked portfolio return analysis and regression analysis methodologies.

The 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.

The 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.

This 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.

The purpose of this paper is to investigate the pricing of European real estate equities. The study examines the main drivers of real estate equity returns and determines whether loadings on systematic risk factors – the excess market return, small minus big (SMB), HIGH minus low (HML) – can explain cross‐sectional return differences in unconditional as well as in conditional asset pricing tests.

The paper draws upon time‐series regressions to investigate determinants of real estate equity returns. Rolling Fama‐French regressions are applied to estimate time‐varying loadings on systematic risk factors. Unconditional as well as conditional monthly Fama‐MacBeth regressions are employed to explain cross‐sectional return variations.

Systematic risk factors are important drivers of European real estate equity returns. Returns are positively related to the excess market return and to a value factor. A size factor impacts predominantly negatively on real estate returns. The results indicate increasing market integration after the introduction of the Euro. Loadings on systematic risk factors have weak explanatory power in unconditional cross‐section regressions but can explain returns in a conditional framework. Beta – and to a lesser extent the loading on HML – is positively related to returns in up‐markets and negatively in down markets. Equities which load positively on SMB outperform in down markets.

The implementation of a liquidity or a momentum factor could provide further evidence on the pricing of European real estate equities.

The findings could help investors to manage the risk exposure more effectively. Investors should furthermore be able to estimate their cost of equity more precisely and might better be able to pick stocks for time varying investment strategies.

This is the first paper to examine the pricing of real estate equity returns in a pan‐European setting.